Understanding and improving the quality of primary care for people in prison: a mixed-methods study

Article history

The research reported in this issue of the journal was funded by the HSDR programme or one of its preceding programmes as award number 17/05/26. The contractual start date was in August 2019. The draft manuscript began editorial review in August 2022 and was accepted for publication in June 2023. The authors have been wholly responsible for all data collection, analysis and interpretation, and for writing up their work. The HSDR editors and production house have tried to ensure the accuracy of the authors’ manuscript and would like to thank the reviewers for their constructive comments on the draft document. However, they do not accept liability for damages or losses arising from material published in this article.

Copyright statement

Copyright © 2024 Bellass et al. This work was produced by Bellass et al. under the terms of a commissioning contract issued by the Secretary of State for Health and Social Care. This is an Open Access publication distributed under the terms of the Creative Commons Attribution CC BY 4.0 licence, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. See: https://creativecommons.org/licenses/by/4.0/. For attribution the title, original author(s), the publication source – NIHR Journals Library, and the DOI of the publication must be cited.

2024 Bellass et al.

Structure of the report

Chapter 2 reports the findings of the scoping review of quality indicators in the prison setting.

Chapter 3 outlines an expert consultation process on indicator prioritisation.

Chapter 4 presents the findings from the qualitative work package (WP) (objective 2), exploring barriers and enablers to quality care from the perspectives of healthcare staff and people who have lived in prison.

Chapter 5 describes findings relating to the third objective, the quantitative analysis of healthcare records from 13 prisons in the North of England.

Chapter 6 integrates the findings from all prior WPs.

Chapter 7 describes the findings from the additional MH workstream, involving supplementary quantitative and qualitative analyses.

Chapter 8 brings the findings from across all WPs together and discusses what they mean on a higher level, with reference to the literature, and briefly concludes the whole report.

Introduction

A scoping review was undertaken to identify and synthesise previous work conducted on quality indicators and performance measurement in the prison setting. The focus of the review was on the selection, development, implementation and review of quality indicators and performance measures. Our research question was: what is known from the research literature about the development and selection of quality indicators for primary health care in the prison setting?

Some material from this chapter has been reproduced from Bellass et al. (2022).

Bellass S, Canvin K, McLintock K, Wright N, Farragher T, Foy R, Sheard L. Quality indicators and performance measures for prison healthcare: a scoping review. Health Justice 2022;10(1):13. https://doi.org/10.1186/s40352-022-00175-9

This article is licensed under a Creative Commons Attribution 4.0 International License (CCBY 4.0) which permits use, sharing, adaptation, distribution and reproduction in any medium or format, provided the original work is properly cited. See http://creativecommons.org/licenses/by/4.0/. The text below includes minor additions and formatting changes to the original text.

Method

Scoping reviews are increasingly being used in health research to map the contours of knowledge on a particular topic. 22,23 However, in comparison to systematic reviews, which benefit from clearly articulated and replicable procedures, scoping review methodology has historically been less well-defined, resulting in considerable variability in approach and rigour. 23–27 In addressing the lack of consensus around scoping review methods, Arksey and O’Malley24 established a six-stage framework for conducting a scoping review, comprising identifying the research question, literature searching, selection of studies, charting the data, collating and reporting the results, and an optional stage of validating the review findings through stakeholder consultation. In comparison to systematic reviews, they suggest, scoping reviews typically have broader, more exploratory questions, are more inclusive in terms of study designs, and do not exclude studies based on an assessment of methodological rigour.

Other authors since have sought to expand Arksey and O’Malley’s work,24 offering further detail to the stages within the framework,25,27 for example, emphasising clarification of the focus of the question and the rationale of the study, and recommending a combination of independent reviews and team discussions to enhance the rigour of the process. Tricco et al. 26 called for standardised reporting of scoping reviews to increase transparency, which has resulted in the publication of the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews [PRISMA-ScR (www.prisma-statement.org/Extensions/ScopingReviews)],28 an adaptation of the PRISMA statement originally created for systematic reviews and meta-analyses (www.prisma-statement.org/). The PRISMA-ScR items were used to guide the scoping review reported here.

Eligibility criteria

The following criteria were developed to determine which sources would be eligible for inclusion in the review:

Inclusion criteria:

• any type of literature that relates to the selection, development, implementation or review of quality indicators in the prison setting (either adult or juvenile);

• in empirical papers, any research method employed;

• any health condition;

• published between January 2004 and December 2019;

• English language only;

• international literature.

As the specific focus of the review is performance measurement and the use of quality indicators in prisons, literature meeting the following criteria were excluded:

Exclusion criteria:

• community criminal justice settings;

• literature relating to the transition from prison to the community.

Information sources and search strategy

A published search strategy aimed at identifying primary care quality indicators for people with serious mental illness using three key concepts (primary care, quality indicators and serious mental illness)29 was adapted by an Information Specialist to include search terms relating to prison settings and exclude those relating specifically to serious mental illness. Hence, the search strategy (see Appendix 1 for the MEDLINE and CINAHL versions) was structured around three key concepts: quality indicators, primary care and prison. Boolean operators were used to combine synonyms in the concept groups with OR prior to combining the three groups of search results with AND.

It should be noted that in American literature, the term ‘prison’ is used differently to the UK context. In the USA, ‘prison’ typically refers to a confinement facility operated by the state or the Federal Bureau of Prisons, and usually houses people convicted of serious crimes. In contrast, jails in the USA are governed locally and accommodate people on remand or convicted of less serious crimes who are therefore likely to have short stays. The term ‘corrections’ is used in the USA to encompass both prisons and jails. The use of the term ‘prison’ in this review relates to the UK context and acts as an equivalent to the US word ‘corrections’.

Six databases were selected by the Information Specialist for their likelihood to index articles relating to quality indicators or to health quality in prisons: CINAHL, MEDLINE, Criminal Justice Abstracts, EMBASE, PsycINFO and Scopus. Searches were conducted separately for each database, using the Ebsco search for Criminal Justice Abstracts, the Ovid search for PsycInfo and EMBASE, and then adapting the search syntax for Scopus. Searches were conducted up to April 2021 by the Research Fellow (SB).

Additional methods of literature identification were conducted to augment the electronic search strategy. Four key journals (International Journal of Prisoner Health, Journal of Correctional Health Care, The Prison Journal and British Journal of General Practice) were hand-searched. In addition, the institutional profiles of seven key authors were examined for further relevant publications. Finally, forwards and backwards citation tracking was conducted on an initial group of 12 influential papers.

Search results were managed and de-duplicated in EndNote X9.

Study selection

The de-duplicated search results were divided equally between the Research Fellow (SB) and the Programme Manager (KC). Both researchers reviewed the abstracts of papers excluded by the other. As an additional check, a further search using the EndNote Quicksearch function was undertaken in the excluded groups using keyword/key phrase searches (e.g. performance measurement, quality indicators) to ensure that no papers containing these terms had been erroneously excluded.

Abstracts of literature that were identified from supplementary searches, that is, journal searches, author searches and citation tracking, were reviewed by both researchers. Where there was disagreement over the selection of sources, an inclusive approach was taken and the paper was put through to the full-text review stage. Both researchers reviewed the full-text articles, resolving any disagreements through consultation with a co-Principal Investigator (LS).

In accordance with the inclusive stance of scoping review methodology,23,24 and in contrast to systematic review methodology,30 papers were not excluded on the basis of a formal critical appraisal of study methodology, since the purpose of this review was to provide a descriptive overview of the literature on quality indicators in the prison setting, rather than to assess the robustness of clinical evidence underpinning the indicators.

Data charting and data items

A data charting table (see Appendix 2), was constructed using generic study features informed by the Joanna Briggs Institute Reviewer’s Manual https://wiki.joannabriggs.org/display/MANUAL/11.2.7+Data+extraction), and bespoke elements informed by detailed reading of six of the texts selected after full-text review. The chart was constructed by the Research Fellow and reviewed by the Programme Manager and a co-Principal Investigator (LS), and was adapted in an iterative process by the Research Fellow following further reading. The charting table facilitated comparison between studies.

Data items relating to the features of the study were extracted, such as the country of origin, the year, the study type and the funder. In addition, contextual elements relating to the development of quality indicators were charted, including drivers for the development of performance measurement, the challenges and constraints of the prison environment, issues relating to the transfer of performance measures from a community setting, and stakeholder engagement in decision-making processes.

Synthesis

Results were synthesised into the following groups, studies that: (1) reviewed quality indicators, (2) developed or recommended the use of explicit quality indicators or less explicit performance measures and (3) implemented quality indicators. Additionally, trends in performance measurement over time were synthesised.

Findings

Study selection

A PRISMA flow chart of the study selection process is shown in Figure 1. Of the 1271 sources identified from electronic searches and supplementary searches, 24 were assessed as eligible for full-text review following abstract screening. Nine of these were excluded due to lack of a focus on quality indicators, being policy- rather than care-oriented, or for focusing on data collection rather than analysis. Fifteen sources were included in the final synthesis.

FIGURE 1.

Selection of sources of evidence: Preferred Reporting Items for Systematic reviews and Meta-Analyses flow diagram. QI, quality indicator.

Study characteristics

The characteristics of the included studies are shown in Appendix 3, Table 14. All the studies were American in origin, bar one UK study. 31 Six studies developed quality indicators or performance measures,32–37 two sources reviewed indicators or approaches to performance measurement,38,39 while a further two described implementation,31,40 and one commentary paper advised on implementation. 41 One study developed and implemented indicators in a prison setting,42 while two described approaches to developing and testing indicators across US prisons,43,44 and one tested performance measurement of diabetes screening in one prison. 45

Three studies originated from the same research programme and were published in the same 2011 issue of the Journal of Correctional Health Care. The programme aim was to assess quality of healthcare measurement in California Department of Corrections and Rehabilitation (CDCR) and other prison systems and to recommend a portfolio of performance measures. The three studies were: an expert consultation process (reported in Asch et al. ,35 with the resulting list of indicators published by Teleki et al. 39) interviews, site visits and document reviews within CDCR,39 and a review of performance measurement activities in six correctional systems. 38

Types of quality indicators and performance measures

Most of the literature included quality indicators or performance measures, although the content varied widely from a few illustrative examples,32,35,40,41,43 to extensive lists. 33,34,36,39,44 Further variation was found in the format of measures, with some authors providing ‘explicit’ quality indicators33,35,39,40,44 – defined by Damberg et al. 38 as objective, EB measures that provide a standardised means of measuring quality across prisons – while others provided more broadly stated performance measures. 32,34,36,41,43 Explicit indicators, Damberg et al. 38 suggest, are distinguishable by their format; they have a clearly expressed denominator, that is, the number of people eligible for a particular measure, and a specified numerator, that is, the number of people from the denominator who satisfy the measure. Further parameters are often included, such as a reporting period, for example, the last 12 months, or particular diagnostic codes. The measure is then expressed as a percentage, calculated by dividing the numerator by the denominator and multiplying by 100. Explicit quality indicators are typically classified as ‘process’ indicators, that is, those focusing on care delivery, or outcome indicators, which measure the achievement of a particular health outcome, as demonstrated in Table 1.

In this body of literature, performance measures provided ways to assess prison healthcare quality, but the numerators, denominators and reporting periods were typically not specified, though often implied. For example, Greifinger36 appended a list of questions that could identify areas for clinical performance improvement through the interrogation of randomly selected small samples of healthcare records. For example, taking 10 records of people with positive tests for syphilis, gonorrhoea and chlamydia, Greifinger suggested that a measure of quality would be those who had received an appropriate prescription to treat their condition within 3 days. Similarly, Hoge et al. 34 suggested that people in prison who screen positive on a validated suicide risk assessment measure should ‘receive a referral to a MH staff member for evaluation. All inmates deemed to be an acute risk should be placed on suicide watch immediately and be immediately referred to the MH team’ (p. 643). Thus, the numerators and denominators are implicit in these measures of healthcare quality, but further work would be required to clarify the parameters of the metrics before they could be implemented in practice; clarifying denominators in the prison population, for instance, is particularly challenging given the transience of the population as people move between the community and the prison estate, or are transferred between prisons.

Studies focused on chronic care quality measurement

Four studies (Kountz and Orsetti,42 Castro,45 Booles31 and Kintz)37 were included in this review to give specific insights into quality assessment of chronic condition (CC) management in prison settings. Booles31 and Castro45 focused solely on diabetes, exploring, respectively, care processes and risk assessment. Booles31 conducted a survey of diabetes care quality in UK prisons, with 19 respondents, while Castro45 retrospectively analysed 50 health records of people diagnosed with diabetes during their prison term and held a consultation exercise to choose the most appropriate clinical guidelines for diabetes screening in prisons.

Kountz and Orsetti42 and Kintz37 explored quality of care for diabetes and other CCs [asthma and hypertension42 and asthma, human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS), hypertension/cardiovascular disease (CVD), lipid disorders, seizures, hepatitis, severe mental illness (SMI) and hepatic cirrhosis]. 37 Kountz and Orsetti42 developed and implemented a quality assessment tool, and Kintz,37 following Damberg et al. ,38 conducted a study of prison nurses’ perceptions of quality of care for chronic health conditions.

All of the authors identified the lack of standardised guidelines or their inconsistent application as causes of variability in care processes, which contributed to increased risks of sentinel events42 and diabetic complications. 31,45 Booles,31 for instance, in his survey of diabetes care in UK prisons, found that only 14 of the 19 prisons that responded were conducting routine monitoring of the diabetic patients, and only 37% of the sample had provided a mobile retinal screening service. Similarly, Kountz and Orsetti,42 when extracting a random sample of 10 medical charts, found that four people with diabetes were not receiving standard care. They also found that the lack of baseline data on CCs hampered efforts to identify high-risk patients and prevent sentinel events.

Castro,45 in her dissertation study on retrospectively identifying diabetes risk in 50 people subsequently diagnosed with diabetes in a US correctional facility (CF), found a lack of consistency in diabetes screening. For example, only 3 of 13 people with prediabetic impaired fasting glucose had subsequent HbA_1c tests, although whether appointments were arranged but not attended is unclear.

Kintz,37 in her interview study with eight prison nurses, offered some insights into the barriers to quality health care for people in prison with CCs. Alongside confusion about which standards to apply, nurses reported that constrained resources resulted in acute care taking priority over long-term condition care. Inadequate data systems and poor levels of staff retention, education and appreciation of the value of performance measurement were other barriers that impeded efforts to provide quality of care. Kountz and Orsetti42 similarly found a reluctance among staff to employ the audit method they devised, with only two-thirds of the charts being completed on intake.

Methods of selecting performance measures or quality indicators

Several papers in the review described methods of selecting performance measures or quality indicators,32–36,44 with the quality indicators resulting from Asch et al. ’s35 consultation process being reported in the sister Teleki et al. 39 paper. There was noticeable variation in methodological rigour. For example, work that selected quality indicators varied significantly in the approach taken; there was a sharp contrast between the robust expert consensus processes employed by Asch et al. 35 and single individuals recommending indicators in Greifinger36 and Laffan. 41 None of the papers included in this review explicitly included the patient perspective, drawing instead on researcher, care provider or care manager input. However, it was noted by one group of authors, Asch et al. ,35 that people on the receiving end of care may have different priorities for performance measures, perhaps placing more value on outcome indicators which measure changes in health status, than those relating to care processes.

Challenges and constraints of implementing quality assessment in the prison setting

Authors of papers in this review described a range of challenges to the implementation of performance measurement in prisons, including changing demographics of the prison population, the functionality of the data system, staffing and resourcing issues, and challenges to standardising quality of care measurement across different organisations.

Conclusion

While this review found limited evidence on the development and implementation of quality indicators and performance measurement in prison health care, and the evidence was virtually entirely restricted to the US context, a number of significant issues have been identified. These include the demographics of the prison population, the functionality of the data system, the format of quality indicators, stakeholder engagement, the choice of standards, target setting and staff engagement.

Introduction

Measurement is a cornerstone of quality improvement in health care. Measures of the quality of care can be used to identify priorities for improvement, drive change through feedback to clinicians and healthcare organisations, and assess the impact of improvement strategies. In WP1, we set out to identify and select quality indicators that could be assessed using routinely collected data for use in the prison estate. We subsequently applied and analysed achievement of the selected indicators in our statistical analysis WP (see Chapter 5). This chapter describes the process by which we identified and developed the indicators.

Methods

Design

Our four-stage process comprised (1) identification and screening of candidate indicators from guidance and wider literature, (2) shortlisting and selection with a stakeholder consensus panel, (3) specifying eligible populations and criteria for achieving each indicator and (4) piloting data extraction to assess feasibility and refine indicators (Figure 2). We chose a modified RAND consensus process for shortlisting and selection to promote transparency in decision-making, and because it allowed interactions between participants which can help judgements requiring some degree of deliberation. 46

FIGURE 2.

Flow chart of the four-stage indicator selection and development process.

Stage 1: identification and screening of candidate indicators

We identified candidate indicators from guidance from the National Institute for Health and Care Excellence (NICE) including the QOF,47 clinical guidelines48–50 and the General Medical Service contract,51 and local quality indicators selected from local quality requirements from the NHS Standard Contract for prison health care 2019–20 for the North East, North West, and Yorkshire and Humber (set by the Commissioning Team under Schedule 4). We also drew on three studies that produced lists of indicators for use in primary care settings. 29,52,53 Our indicators were intended to measure individual-level care rather than organisational-level features and performance, which we allowed for in the analysis. Therefore, we did not draw upon Care Quality Commission (CQC) inspection standards.

We screened candidate indicators to prevent placing an excessive burden on the stakeholder consensus panel. An academic general practitioner (GP) (RF) conducted a preliminary screen of the full list of indicators and excluded those that were not relevant to primary care or had been superseded by new indicators. Four clinical team members, comprising RF, a former prison nurse and healthcare manager (MC), and two prison GPs (KM and NW), further screened the indicators. In an online survey, they independently screened according to two criteria: (1) likely amenability to measurement using routinely collected data and (2) potential for significant patient or population benefit. We collated the scores assigned by the clinical team members and then ranked the indicators. The full project team then systematically worked through the list of indicators during an internal workshop and discussed borderline indicators, discrepant ratings, and options for composite (combined) indicators.

Stage 2: shortlisting and selection with consensus panel

We had planned to recruit a panel of 11 participants, with a range of prison-specific, clinical and academic experience, recognising that consensus groups gain relatively little in reliability beyond this number. 46 We aimed to balance familiarity with day-to-day decision-making in community primary care with an appreciation of issues specific to the delivery of health care in the prison setting and the needs of the prison population. We invited several people with lived experience of prison to join the panel, but none accepted. Eight professionals from a range of criminal justice, health and MH backgrounds (including general practice, psychiatry, clinical psychology and nursing) accepted the invitation to participate.

We asked panellists to rate each candidate indicator independently online using a 1–9 Likert scale (where one is low and nine is high) according to the single criterion of ‘potential for significant patient benefit’. We provided instructions on rating and the list of indicators in a PDF by e-mail with a printed copy by post to use as a reference. To make the process accessible for panellists without relevant clinical training or former knowledge of quality indicators, we constructed a glossary of terms and plain-language descriptions of the indicators. We encouraged stakeholders to rate every indicator but provided a ‘don’t know’ option for all indicators. We piloted the functionality of the online survey with a project team member prior to sending to panellists. We also shared the original long list of indicators with the panel so they could highlight any indicators screened out earlier by the research team for reconsideration and asked them to suggest any indicators that we had not identified. We briefed the panel that we were ultimately aiming to provide a balanced suite of indicators which covered different aspects of primary care in prisons.

We calculated median scores for each rating using Microsoft Excel. We ordered indicators according to their median score for ‘potential for significant patient benefit’ and levels of discordance for presentation at a face-to-face panel meeting. We presented median ratings for each indicator. One of the authors (RF) facilitated a structured discussion which focused on indicators with the most discordant ratings. Low discordance was defined as all ratings for each indicator being three or fewer points apart, medium discordance at all ratings being between four and six points apart, and high discordance as at least two ratings between seven and nine points apart.

We gave panellists the opportunity to seek clarification about any aspects of indicators and to discuss their reasons for low or high ratings. Immediately after this discussion, panellists independently rated each indicator again. Five panellists completed both rounds, one of whom could not attend the face-to-face meeting and therefore completed ratings remotely. Our smaller than planned panel still collectively possessed a diverse range of perspectives,54 despite the difficulty in attracting busy clinicians and professionals to take part in this half-day exercise.

Stage 3: review and refinement

We reviewed and updated the list of indicators, considering them both individually and as a set. We disaggregated composite indicators and removed duplicates and low-rated indicators. We also conducted a sense-check to review face validity for individual indicators and as a set of indicators. Before moving to stage four, we conducted initial feasibility investigations; to be eligible for inclusion in our suite of indicators, data had to be routinely collected and coded in templates. If not, they could not be operationalised.

Stage 4: specifying eligible populations and criteria for achieving each indicator

We developed a template for each indicator which specified the eligible population (the denominator) and what criteria would need to be met for achieving the indicator (the numerator). The templates further included information on indicator sources and notes on development. We held several clinical team meetings (involving RF, KM and NW) to refine the indicators and monthly ‘troubleshooting’ meetings (involving RF, NW, KM, KC, PH, SR and TF) to develop and agree the data queries for each indicator. We designed data searches based upon existing algorithms, such as those used for QOF, wherever possible, to permit later comparisons with indicator achievement in community settings. The data specialist (SR) extracted anonymised individual patient-level data for the 13 prisons where health care was provided by Spectrum Community Health Community Interest Company (CIC) from SystmOne electronic health records. We reviewed descriptive summaries of the extracted data prepared by the statistician (TF) for apparent anomalies and discrepancies at the troubleshooting meetings. The data specialist subsequently refined searches until final versions were agreed.

Results

Interpretation of findings

Our suite of indicators includes topics especially relevant to the prison population (MH, drug misuse and communicable diseases) and covers potentially overlooked ‘mundane’ aspects of primary care, such as the management of hypertension and asthma. Our indicators consider equity explicitly (e.g. in including those uniquely relevant to women and older people) and implicitly (e.g. analyses can examine differences in achievement according to age, coded ethnicity and sex). We recognise that the indicators cannot cover all aspects of care, including processes and outcomes which are not routinely captured and coded in electronic health records and important features of holistic care (such as communication skills). Therefore, their application needs to be complemented by other sources of data on quality of care.

We generally balanced three other characteristics of our indicators. First, we had a range of process and outcome indicators. Process indicators should ideally have a strong evidence base so that following the process predictably leads to improved outcomes [e.g. prescribing of secondary preventive treatment following myocardial infarction (MI)]. 62 The evidence base for several process indicators is less certain, but these can still be recognised as signals of good-quality care (e.g. processes of care for diabetes). 63 Indicators solely focusing on processes of care rather than health outcomes may not help overcome therapeutic inertia – the failure to intensify treatment in patients not meeting clinical goals of treatment (e.g. recommended blood pressure control in diabetes). 64 Outcome indicators are subject to higher ‘noise to signal’ ratios, whereby a range of factors beyond professional practice influence outcomes (e.g. varying patient concordance with blood pressure treatment). 65 Second, we included a range of single and composite indicators. We generally used composites for indicators assessing several, closely linked processes of care (e.g. for diabetes) and disaggregated them when considering outcomes (e.g. blood pressure control). Offering a battery of single, simpler indicators is more likely to be feasible in practice compared to more complex indicators and better direct specific actions to improve quality of care (e.g. in specifying gaps in attainment of specific aspects of diabetes care such as blood pressure control). 66 Third, most of our indicators focused on relatively common conditions or problems affecting people in prison (e.g. drug misuse). However, we recognised that solely focusing on common problems might marginalise rarer but clinically important needs. We therefore included some indicators that were important to the management of long-term conditions for older people (e.g. dementia, heart failure).

Summary of main findings

We have identified and developed a set of indicators, largely drawn from EB guidance, to assess the quality of primary care delivered in prisons. They are largely drawn from evidence-based guidance and, if followed, can deliver population benefits. The indicators cover both specific priorities for the prison population and core priorities of community primary care, thereby allowing assessments of care equivalence across settings. The indicators are based upon routinely collected data, thereby allowing efficient and scalable application beyond the research context to inform and drive quality-improvement strategies.

Introduction

The qualitative study aimed to explore perceptions of the quality of prison health care from two perspectives: prison leavers (hereon referred to as patients) and prison healthcare staff. Specifically, the study aimed to identify barriers and facilitators of care delivery in prison, and to map these data to a multilayer theoretical framework to develop detailed understandings about prison healthcare quality.

Some material from this chapter has been reproduced from Sheard et al. (2023):

Sheard, L, Bellass S, McLintock K, Foy R, Canvin K. (2023) Understanding the organisational influences on the quality of and access to primary care in English prisons: A qualitative interview study. British Journal of General Practice, 100166

This article is licensed under a Creative Commons Attribution 4.0 International License (CCBY 4.0) which permits use, sharing, adaptation, distribution and reproduction in any medium or format, provided the original work is properly cited. See http://creativecommons.org/licenses/by/4.0/. The text below includes minor additions and formatting changes to the original text.

Methods

Findings

Barriers and facilitators analysis

For a brief summary of the barriers and facilitators, see Table 6.

Summary

Introduction

It is accepted that people detained in prison are entitled to a standard of care at least equivalent to that available in the wider community,68 and that neglecting the health needs of people detained in prison has negative implications, not only for the individual, but also for society. 69,70 While the delivery of care may differ, with services tailored to meet the various requirements of the patient, level of security and prison regime, the principle of equivalence is intended to promote equitable health outcomes for this group of people. 68 Concerns raised about access and quality of health care in prisons suggest equivalence is not always achieved. 7,70

Recent research in prisons has focused on important issues such as public health, social care, dementia and mental health and neurodiversity,70–77 but less attention has been paid to the quality of ‘routine’ primary care provision. We aimed to assess the quality of primary care provided to prisoners through analysis of routinely collected healthcare data. We measured gaps between recommended and actual care, and analysed variations in adherence to recommended practice.

Methods

Data sources

SystmOne Prison is used in all prisons in England. This clinical system includes prisoner demographic data via integration with the Prison National Offender Management Information System (NOMIS), health screening data from the reception assessments, and data related to ongoing care including data on diagnoses (clinical codes), pathology results and prescribing. SystmOne Prison can be used by all healthcare services within a prison, displays all prison medical record data held for each person (including across multiple custodial sentences) and is transferable between prisons.

The data specialist (SR) extracted anonymised individual patient-level data for the 13 prisons from SystmOne Prison electronic health records. We reviewed a summary of the extracted data prepared by the statistician (TF) for apparent anomalies and discrepancies in team meetings. The data specialist iteratively refined searches until final versions were agreed.

Statistical analysis

Descriptive statistics for each indicator were produced by year for each of the explanatory variables. This permitted initial summaries of variation in attainment of each of the quality indicators and review for apparent anomalies and discrepancies.

For most indicators, higher proportions of achievement were desirable. For the indicators examining psychotropic, opioid and gabapentin prescribing, there was no specific criterion against which prescribing levels were compared; generally lower prescribing levels were desirable.

Multilevel mixed-effects logistic regression models were developed for each indicator to explore whether the explanatory variables were associated with achievement of the quality indicator. Achievement of the indicator was the outcome in each indicator model. Achievement was considered ‘met’ (i.e. coded 1 vs. 0 not met) whether it had occurred in an individual’s current prison or in a previous establishment within the time frame of the indicator. As we have repeated measures for people across and within years, for example, someone could have attended multiple prisons in the same year and different years, we had two levels – person identifier and year. Year was included in each of the QI models as both a random and fixed effect to account for the correlation between years and to explore the variation in achievement over the 3 years. In those QI indicator models with only one financial year of data, year was excluded, and for these QI indicators logistic regression models were used. Each of the explanatory variables was included univariately into the indicator models as fixed effects to explore its association with achievement of the indicator. Results from these univariate multilevel mixed-effects logistic regression models were presented as odds ratios (ORs) and accompanying 95% confidence intervals (CIs). No modelling was presented for seven indicators as the number of eligible patients and achievement was too small for meaningful analysis.

The explanatory variables were then included in multivariable multilevel mixed-effects logistic regression models to explore whether variation in achievement of the indicator remained after accounting for other explanatory variables, that is, other individual and prison-specific factors. Results from these multivariable multilevel mixed-effects logistic regression models were presented as ORs and probability of achievement of the indicator, with accompanying 95% CIs for both estimates. Prison category was not included in the multivariable models given close correlation between category and prison identity. Where numbers in subcategories were too small to produce robust estimates, or where the explanatory variable was removed from the model, these ORs and probabilities are not presented. These results from the univariate and multivariable multilevel mixed-effects logistic models were summarised (as outlined in the Results by quality indicator section) by the following themes: communicable disease, MH, prison-specific, diabetes, asthma and epilepsy care, screening and CVD.

All appropriate assumptions were checked and were met for each quality indicator (univariate and multivariable) multilevel mixed-effects logistic regression models:

• There was no multicollinearity in the multivariable models. Prison category was not included in the multivariable models given close correlation between category and prison identity and so negated the potential issue of multicollinearity between these two explanatory variables.

• Residuals were checked for normality, homoscedasticity and no outliers identified.

• All individual and prison-specific factors were included as categorical variables and so checking for a linear relationship between continuous predictors was not applicable.

Generalised estimating equations (GEEs) might have been another modelling approach rather than multilevel mixed-effects and these are usually equivalent for linear models; this is not the case for binary outcomes. The fundamental difference between the two is in this interpretation of the (fixed) effects. GEEs produce population-averaged effects, while multilevel mixed-effects logistic regression models produce subject-specific effects. 78,79

We originally proposed to develop latent variable models. We hypothesised that there would likely be strong associations between the different indicators and these models could identify explanatory variables common across all indicators. This unifying model would have explored which factors are associated with quality in care in prisons as measured by all these indicators. However, from the development of the searches for each of the indicators, it became clear that eligibility often varied among indicators. Therefore, there was not a common eligible (denominator) population to include in the latent model and so conducting this analysis was not possible. These models would also have supported the estimation of the attainment false negative and positive rates using a Bayesian analysis framework. As no latent variable models were developed, the Bayesian analysis could not be done. All statistical analyses were carried out using Stata 16 software. 80

Ethical approval

We gained approval for this statistical WP from the University of Leeds SoMREC on 17 July 2019 (ref. no. 18-093). We approached HMPPS regarding approval for this WP and we were issued with an exemption notice dated 19 March 2019 which exempted us from applying for NRC approval as our quantitative analysis was based on routinely collected and anonymised data.

Results

Results by quality indicator

All results are based upon a total study population of 25,811 people in 2019–20, unless otherwise stated. Variations in achievement between prisons were calculated as a ratio of the ORs for lowest and highest achievement (presented within brackets). Notable variations in achievement from multivariable multilevel logistic regression models are provided as ORs with 95% CIs (presented within brackets). The most recent comparisons in achievement from community settings are highlighted where available. These often came from QOF indicators. 81–84 It was not possible to use robust methods in this comparison (e.g. adjusting for demographic differences in the populations). Descriptive statistics pertaining to achievement for each quality indicator and comparisons with community populations where applicable are provided in Appendix 6, Table 16. The multilevel mixed-effects logistic regression models results are provided in Appendix 7, Table 17 and summaries of the model results by themes in Appendix 8, Tables 18–23.

Interpretation of findings

Conclusion

To the best of our knowledge, this is the first study to examine the quality of primary care across multiple prisons and a range of indicators. We found substantial scope for improvement and marked variations in the quality of primary care, as measured using routinely collected data, examining a total of 25,811 records from 13 prisons in the North of England. Gaps and variations in care spanned different domains, both for indicators that reflected particular needs of the prison population (e.g. MR) and those reflecting more general primary care needs (e.g. diabetes care).

The extent of variations between prisons was not accounted for by differences in available prison population characteristics, though length of stay and ethnic group were associated with some differences in indicator achievement. This suggests that much variation is attributable to local differences in healthcare organisation and delivery.

We found encouraging trends suggesting improvement over time for several indicators, such as improving hepatitis B vaccination and falling gabapentinoid prescribing, and strengths in performance, such as for secondary prevention of stroke. However, we identified areas of concern, where overall achievement had declined over a 3-year period, notably declining antipsychotic monitoring and rising opioid prescribing.

Relatively short lengths of stay were frequently associated with lower achievement across prison-specific, long-term conditions and screening domains. Shorter stays could represent missed opportunities for health intervention and may accompany recidivism, reflecting the negative health impact of repeated incarceration.

Introduction

In earlier WPs, we identified a suite of quality indicators which could be applied using routinely collected data, assessed adherence to these indicators across 13 prisons, and explored barriers to and enablers of high-quality care. This WP aimed to integrate these findings through structured stakeholder deliberations to prioritise quality indicators and quality-improvement interventions that are likely to be relevant and feasible to deliver in prison settings and can be monitored by our suite of indicators.

Methods

We convened a three-part stakeholder panel, inviting people involved in commissioning and delivering primary care in prisons, as well as advocates for people in prisons.

Participant identification and engagement

We identified stakeholders through professional networks of project team members and oversight committee members. Invited stakeholders were those responsible for commissioning or delivering prison healthcare services in England (Table 9). We e-mailed an invitation to our first workshop to all on the list, with recipients encouraged to cascade it to other interested parties. We also promoted our first workshop at relevant dissemination events, including the Royal College of General Practitioners Secure Environments Group meeting (September 2021) and the Health and Justice Summit (October 2021).

Procedure

We took the panel through the following steps:

• Reviewing findings from WP3 (statistical results) to identify priorities for improvement based on scope for improvement for each indicator, that is, low performance; groups of prisoners associated with lower achievement of indicators, such as older people, longer- or shorter-term prisoners.

• Considering findings from WP2 (qualitative findings) to understand barriers to and enablers of good quality of care, considering levers for change at individual, team, organisational and wider system levels.

• A briefing summarising the range of approaches (interventions) potentially available to support the implementation of quality indicators, drawn from a broad overview of systematic reviews89–94 and a scoping review.

• Mapping of implementation interventions to identified barriers and enablers. For example, if clinical staff or teams were unaware of their poorer performance relative to other clinical staff and teams, then audit and feedback comparing data on performance can help identify erroneous perceptions and use social comparisons and goal-setting to motivate change.

• Application of APEASE criteria (affordability, practicability, effectiveness, acceptability, safety and equity),95 in considering the likely intervention adaptability to and sustainability within the prison healthcare environment.

We had originally planned to cover these steps over three face-to-face workshops, each lasting 4–6 hours, to allow sufficient time for discussion and consensus. However, we shifted to online meetings because of the COVID-19 pandemic. We redesigned the workshops to take place using Microsoft Teams. In light of recent empirical research, which has identified sustaining attention as a major contributor to videoconferencing fatigue,96 we restricted the duration of Teams meetings to a maximum of 2 hours each. We therefore had to focus and limit some of the aforementioned steps for the panel. Regrettably, the expert-by-experience (FB) was unable to attend the online workshops as planned. We therefore devised an alternative way to include him and to incorporate his views and comments.

Figure 3 summarises our modified approach. Steps 1–6 outline the process for stakeholder involvement, and steps A–F outline the process via which we involved the expert-by-experience. In short, we recorded all three workshops, capturing the presentations and subsequent discussions and the expert-by-experience watched the recordings at his own pace, pausing to audio-record ‘voice notes’ on his smartphone. His comments and observations are integrated into the discussion reported below. For ease of reading, we will further detail some of our procedures in Results.

FIGURE 3.

Stakeholder engagement workflow.

Results

Inter-workshop activity: quality indicator prioritisation online survey (Round 1)

After the first workshop, participants were invited to take part in an online survey (Round 1 survey). We made the survey available immediately after the first workshop for a period of 2 weeks. We recognised that it would not be feasible for prison providers to target improvement on all 30 indicators simultaneously. We further anticipated that there would be insufficient time within the second workshop to allow any meaningful discussion of all indicators. Accordingly, this survey differed to the rating exercises in the stakeholder consensus exercise conducted in WP1 (see Chapter 3) in several ways. Rather than aiming to discard indicators, the purpose of this rating exercise was to identify a manageable number of indicators from our final suite of 30 for discussion in workshops 2 and 3 and to prioritise one or two for subsequent development as illustrative quality-improvement strategies. This time participants were asked to rate our suite of indicators on a scale of 1–9 (where 1 indicated strongest disagreement, and 9 strongest agreement) according to two criteria: the importance of the indicator, and the feasibility of achieving change. As detailed above, participants who had attended workshop one, viewed the recording or read the indicator booklet (see Appendix 9) were apprised of the findings from our analysis, which may have informed their views about importance and feasibility and subsequently their ratings.

Twelve stakeholders participated in this survey, including representation from prison healthcare providers and clinical leads, healthcare commissioners, PHE and Health and Justice leads. We collated and summarised scores for each indicator. We assessed levels of discordance between participants, with the intention of focusing later discussion on those with maximal discordance, defined as at least two participants rating an indicator feature 1–3 and at least three rating 7–9. Appendix 10, Table 24 summarises Round 1 findings. We therefore developed rulesets (see Appendix 11, Table 25) to exempt indicators from further workshop discussions based on Round 1 ratings. We applied a ruleset which exempted indicators with median scores of < 8 for importance regardless of perceived feasibility. This led to the exclusion of six indicators: hepatitis B vaccination; antipsychotic monitoring; cognitive testing in over 55s; laboratory tests in diagnosis of dementia; prescribing of an ACE-I or ARB for heart failure; and prescribing of an ACE-I or ARB and a beta-blocker for heart failure.

Workshop 2

We held the second workshop on 23 November 2021. We invited participants to re-rate the quality indicators during the workshop based on feedback and a discussion of the Round 1 survey ratings.

Workshop 3

The third and final workshop considered the applicability of six candidate implementation interventions identified by high-quality systematic reviews89–94 to the prison setting. Our deliberations were guided by the APEASE framework, which considers Affordability, Practicability, Effectiveness, Acceptability, Safety and Equity. 95 We asked for suggestions for further interventions and levers for change, and presented a suggested illustrative strategy for one indicator.

Introduction

In our analysis of routinely collected healthcare data (reported in Chapter 5), we found variation in the quality of primary care for physical health problems between prisons. In this chapter, we focus our attention on mental illness. It is widely accepted that both people in prison and people with mental illness experience health inequalities. In the general population, there exists a ‘mortality gap’ for people with SMI or a history of substance misuse. 98 This gap is associated with increased rates of suicide, accidental or violent death, increased prevalence of risk factors such as smoking and obesity and consequent comorbid physical health problems (which are associated with diagnoses and drug treatments for mental illness), reduced uptake of physical health care and screening, and ‘diagnostic overshadowing’ (misattribution of symptoms of physical illness to mental illness). 99 The prevalence of long-term physical and mental illness and disability is higher in the prison population compared to equivalent community populations. 100–103 In prison, rates of mental illness, including psychosis, depression, personality disorder and drug and alcohol dependency, are higher than in the community. 104–106 As with physical illness, people in prison present with multiple and complex conditions, with reportedly 70% of prisoners meeting the criteria for two or more psychiatric diagnoses. 107 The prison setting, however, is not conducive to mental healthcare provision108 and may even exacerbate mental distress. 109 Self-injurious behaviours are common in prison110 and suicide rates are higher than those in the community. 111 Unsurprisingly, people in prison are higher users of healthcare services, which may be linked to reduced physical activity, the quality of nutrition, and access to over-the-counter medications, social care and self-directed support. 112,113

In this chapter we report secondary analyses undertaken with a focus on mental health. Our aim was twofold: (1) to deepen our understanding of mental illness and mental health care in prison by revisiting the qualitative data from interviews with healthcare professionals and prison leavers, and (2) to analyse quality of care for subgroups of people in prison with a diagnosed mental illness compared to those without.

Qualitative analysis

Analysis of electronic health records

Our analysis of routinely collected data (detailed in Chapter 5) found that the quality of primary care varied between prisons. The data also provide an opportunity to understand variations related to mental illness. This additional analysis aimed to investigate whether achievement of the quality indicators assessed in Chapter 5 are associated with MH groups, and explore the degree to which any variations can be accounted for by recorded prison and population characteristics.

Methods

We identified three MH groups based on the two indicators related to the MH diagnosis subgroup of the opioid prescription indicator and the antipsychotic prescription indicator, as outlined in Table 11.

To explore the associations between the indicators and the MH groups, multilevel logistic regression models were developed. Separate models for each indicator were developed with achievement of each indicator as the outcome and year included as fixed and random effects to account for the correlation between people with multiple stays across the 3 years. Inclusion of the MH group variable as a fixed effect provided ORs (and accompanying 95% CIs) with No MH as the comparator group. The models were developed further by inclusion of the other characteristics to explore whether any associations between the MH group and achievement of the indicators were accounted for by other individual and prison factors. The resultant adjusted ORs and 95% CIs are presented.

Results

Of the 69,587 prison stays over the 3 years, 13.7% of stays had a MH diagnosis while 1.5% had a psychotropic drug prescription (see Appendix 15, Table 29). In the first 2 years, the patterns of the distribution between the MH groups are similar. However, in the third year, more stays (16.8%) had a coded MH diagnosis than in the previous 2 years (12% in 2017–8).

There were differences in the proportions with a MH diagnosis (with and without psychotropic drugs) between prisons, prison category, gender, age, length of stay and ethnic group. For example, 36.4% of stays by women have a MH diagnosis compared to 11.9% of stays by men, while MH diagnoses were most common in white ethnic group stays (17%) compared with other ethnic groups. These differences in proportions by MH groups and the characteristics indicated that these factors might account for any differences in achievement of the indicators by MH groups. Therefore, we adjusted for these factors in the subsequent models.

From the summary of the proportions of achievement of each indicator by MH group, there is an indication of variation in MH and the indicators (Table 12), which was better explored in the multi-level logistic models (see Appendix 16).

Most communicable disease, MH and prison-specific indicators were associated with MH (see Appendix 16). Generally, the odds of achievement of these indicators were higher in those with a MH diagnosis (with and without psychotropic drugs) compared to those with no MH diagnosis, even with adjustment for other factors (see Appendix 16, Table 30). For example, the odds of receiving one hepatitis B vaccination in the preceding 12 months was 90% higher for those with a MH diagnosis without psychotropic drugs compared to those with no MH diagnosis, adjusting for other factors (OR 1.90; 95% CI 1.78 to 2.02), and 65% higher in those with MH diagnosis with psychotropic drugs (1.65; 1.41 to 1.94).

Few of the Diabetes, Asthma and Epilepsy Care, Screening and CVD indicators were associated with mental health. Where associations existed, the odds of achievement of these indicators were generally higher in those with a MH diagnosis without psychotropic drugs compared to those with no MH diagnosis, even with adjustment for other factors. For example, the odds of people aged 79 years or under, with CHD, hypertension, stroke, transient ischaemic attack or peripheral arterial disease, having a blood pressure of 140/90 mmHg or less in the preceding 12 months was 25% higher in those with a MH diagnosis without psychotropic drugs compared to those with no MH diagnosis, adjusting for other factors (1.25; 1.02 to 1.53), and 68% higher in those with MH diagnosis with psychotropic drugs (1.68; 0.96 to 2.96). In only one of these indicators is the association in those with MH with psychotropic drugs. In those with a MH diagnosis and psychotropic drugs, the odds of the last HbA_1c being 58 mmol/mol or less in the preceding 12 months in people with diabetes without moderate or severe frailty were 2.2 times higher than those with no MH diagnosis (2.18; 1.32 to 3.59).

In two indicators, the odds of achievement of the indicators were lower in those with a MH diagnosis without psychotropic drugs compared to those with no MH diagnosis, even with adjustment for other factors. Firstly, in those with a MH diagnosis and without psychotropic drugs, the odds of people who had had a MI being prescribed three cardiovascular medicines (out of the following: ACE-Is or ARBs, antiplatelet therapy, beta-blockers and statins) was 47% lower than those with no MH diagnosis (0.53; 0.37 to 0.74). Secondly, the odds of eligible women aged 50–70 having a breast screen in the preceding 3 years was 53% lower for those with MH diagnosis and not prescribed psychotropic drugs than those with no MH diagnosis (0.47; 0.28 to 0.79).

Interpretation

Across most indicators, achievement was generally higher for stays of prisoners with coded mental illness than for those without. Achievement also tended to be higher for stays of prisoners with coded mental illness and prescribed antipsychotics. At face value, these findings may appear counterintuitive considering there is a significant evidence base highlighting how people living with severe and enduring mental illness in the community have poorer physical health outcomes. 115 However, people in prison with mental illness are more likely to experience comorbidities and have more frequent encounters with health care, which in turn provides more opportunities for delivering and recording processes of care. What we cannot tell from our data is to what extent actual individual needs were met and whether care delivered improved outcomes.

Nevertheless, we still identified examples where prisoners with coded mental illness were less likely to experience recommended care than those without, namely breast screening for women aged 50–70 years and drug treatment following MI. Furthermore, we found increased likelihoods of opioid prescribing, gabapentinoid prescribing and psychotropic polypharmacy for stays of prisoners with coded mental illness compared to those without. Although such patterns might broadly be expected, the magnitude of such risks was striking, with a more than 17-fold likelihood of being prescribed four or more psychotropic drugs for people prescribed antipsychotics and a more than 4-fold likelihood for other people with coded mental illness.

What have we learnt about the quality of prison health care?

In this section, we draw together the high-level take-home messages from across all WPs to provide an overall account about the quality of prison health care grounded in the empirical data. In doing so, we have derived five broad headline discursive-level ideas of interest which comment on the state of play regarding prison health care. As our empirical chapters focus on data sets which are UK-specific, we use this section to mostly comment on ideas of interest which are context-bound to the UK setting. While our scoping review (see Chapter 2) predominantly identified work from the USA, we will include findings from this WP as and when applicable. The five ideas of interest are:

1. measurement and monitoring

2. variability

3. health inequalities

4. prison organisation and system

5. prison–community interface.

Prison organisation and system

The entire healthcare system in the UK, both inside and outside the prison gates, is under extreme pressure. Hospitals and community primary care are struggling to meet demand from a growing and ageing population. While demand for health care has risen significantly in the past 15 years, since 2010 it has been coupled with a prolonged squeeze on funding which has seen the system straining to meet increased demand with fewer resources. 135 This is coupled with a loss of medical and nursing staff from the NHS due to burnout and stress, with a national GP vacancy rate at 14%136 and a 96% reduction of European Union (EU) nurses joining the UK nursing register after the UK left the EU. 137 The prison system faces similar problems in workforce recruitment and retention, but these are exacerbated by prisons being perceived as an unattractive environment to work in, given the complexity of the patient population and the constraints of the physical conditions in which clinicians deliver care. The Royal College of Nursing (RCN) found that two-thirds of prison nurses who took part in a survey said the care they provided on their last shift was compromised and that the quality of care was poor. 138 The RCN has called for better investment in the prison nursing workforce to raise standards of care delivery and patient safety. A recent academic study from the USA found the main challenges as described by the prison healthcare workforce in one State were constraints around being able to deliver care effectively and safely. 139 This was mainly attributed to understaffing, high numbers of vacant positions and lack of resources. Ismail129 had noted that funding for prison healthcare services in the UK have been ring-fenced by the NHS, but day-to-day delivery has been compromised by a 22% reduction in funding for the prison service itself between 2010 and 2017. This has created a severe staffing deficiency in the prison officer workforce which has then led to deteriorating conditions in healthcare provision. A prominent issue of note here is missed medical appointments (‘DNA’) inside the prison ranging from 20% to 30% of all primary care appointments. 123 This is often attributed to a lack of prison officers to unlock prisoners from their cells and escort them to the healthcare wing, demonstrating a system-wide access problem attributable to workforce outside the healthcare department. Additionally, the extent to which the priorities of the prison regime heavily influence aspects of the delivery of health care must not be underestimated. There is an over-riding concern with security issues which have no equivalent comparison with health care delivered in the community. Edge et al. 140 in their qualitative study with people in prison in England found that security concerns over-rode healthcare needs and created humiliation and fear alongside delayed access to health care and reduced patient autonomy.

Our qualitative work offered the most useful insights about how the prison system and workforce issues influence quality of health care. In our qualitative findings chapter, we present the descriptive findings under four levels: individual, team, organisation and system. In this current section, we take a deeper, more discursive look at the importance of organisational-level factors. We found what could be described as a compounded problem, with the main umbrella issue of understaffing of the healthcare workforce causing knock-on effects and unintended consequences, creating a vicious circle through which the workforce was further depleted (Figure 4). There was a clear acknowledgement by healthcare staff participants of there not being enough staff on the ground on a day-to-day basis and a significant amount of the workforce being locums or from agencies. Understaffing had a demonstrable impact on both patients and staff. Patients described healthcare appointments as being ‘rushed’, not feeling they were getting the time or attention they needed and having to stand in lengthy, unpleasant queues to obtain medication at the medication hatch. We were told in one instance of a patient who had decided to stop taking his medication as he did not want to get involved in the fighting and drug-dealing which was occurring on a daily basis in the medication queue. Healthcare staff spoke about the impact that a sizable locum workforce had on the service, with minimal ability to deliver service improvement or development when substantive and permanent staff were lacking.

FIGURE 4.

Diagram of organisational-level factors.

Related to the above, healthcare delivery was implicitly critiqued by both groups as being reactive and crisis-led. This took varying forms. As staff were often firefighting their way through a large and complex caseload, patients’ perceived minor problems were sometimes put off or ignored until they became major issues which staff were then forced to deal with in an urgent manner. A pertinent example of this is medication continuity. We found that patients who had long-term health conditions but were in prison on short sentences sometimes fared worse than similar patients who were serving a long-term sentence. Those with short-term sentences often had to advocate for themselves and continually remind staff and officers about their condition and required medicines, as they were not well known to healthcare staff or the healthcare department.

We also found there was a lack of responsibility for effective communication, often leading to breakdowns in communication about health care. A prime example of this was the poor communication mechanisms for patients being informed of healthcare appointment times and dates. After requesting a healthcare appointment, some patients did not receive a date but were never told why. A recurrent problem we were told about is an appointment being booked for a patient with the healthcare department but the patient never being reliably informed of this outcome and therefore erroneously missing the appointment as they were unaware of it. Frustratingly, some patients knew they had an appointment but were not unlocked from their cell in time by an officer in order to make the scheduled appointment (this issue represents a significant number of healthcare ‘DNAs’ and is a national-level problem, as described above). The above-described organisational-level communication issues were a persistent source of tension which led to patients, healthcare staff and prison officers becoming angry and frustrated with each other.

It is useful to understand the findings from our other WPs regarding the prison setting as an organisation and system in relation to quality of care. Our scoping review found that prison quality indicators in the USA focused on process rather than structure. Where organisational issues were considered, this constituted only a small number of published papers, with only one research team drawing attention to the fact that high staff turnover may jeopardise measurement of the quality of health care. 34 As a result of our stakeholder consensus process in WP1B, we realised that most of the shortlisted indicators focused on healthcare conditions and processes rather than indicators pertaining to structure or organisation. This could be due to various reasons: a facet of structural indicators is that they are much lower in volume when compared to process or outcome indicators, structural indicators may generate ‘noise’ (disputable findings) that is not considered useful or valuable for clinicians or managers to work with, and the notion that indicators need to be based on information that is concretely and routinely coded, which is likely to be less the case for structural level aspects of health care. In our analysis of routinely collected data (WP3), one of the most interesting findings in relation to organisational-level factors was the substantial variation between different prisons for certain indicators, even when prison population characteristics were adjusted for. This suggests that variation is largely attributable to the local delivery and organisation of health care at the level of the individual prison. Factors outside the healthcare department may be important here, as for the most part it was one healthcare provider that served all 13 prisons whose data was interrogated in WP3. The findings of WP3 alerted us to a lower achievement in indicators for those people in prison with shorter sentences (< 1 month). This is reinforced in the qualitative findings, where patients had to be vocal about making themselves and their medical needs known to the healthcare department. Given that understaffing is one of the major organisational issues flagged by participants in our qualitative study, it is interesting that there is not a quality indicator in our shortlist regarding this. However, this could relate to England having no legal minimum staffing levels (for hospital, community or prison health care) but rather suggested ratio levels which are often discounted given persistent staffing shortages. In the WP4 workshops, participants discussed workforce issues when examining indicators related to prescribing. This was interesting as participants voiced how achieving consistency in the workforce may promote better prescribing practices, and how regular use of a large locum workforce limits clinician accountability. A system-level issue raised was the competitive tendering process for prison healthcare contracts and how this served to inhibit a collaborative relationship between providers, alongside an inefficient reinvention of clinical practices with each new contract cycle. However, this landscape is changing with the creation of Integrated Care Systems, which may reduce the need for competition in this manner.

Strengths and limitations

Here, we bring together the strengths and limitations from each of the WPs to provide a summative account.

Patient and public involvement

Given the stigma and exclusion faced by individuals with experience of imprisonment, the primary aim of our PPI strategy was to ensure that experts-by-experience would be involved in meaningful ways at various levels of the project, in different roles and making various types of contribution. Our intention was that involvement would be of mutual benefit to them and the project. To achieve this, we set out to make involvement as accessible as possible by devising a multifaceted, flexible PPI strategy that could be adapted to the needs of the project and those wishing to be involved. To facilitate the involvement of experts-by-experience, we offered support (e.g. training, mentoring, signposting, advice, co-facilitation) and payment. We produced an information sheet featuring an overview of the project, the members of the team and the role of PPI. We also produced a plain-English list of the quality indicator shortlist. We made these materials available to everyone involved in the project and freely accessible copies were hosted on our website and promoted via the project Twitter account (@Qual_P). The website has a dedicated section for ‘community’ posts which invites people to make comments and suggestions and to ask questions. All recruitment efforts emphasised that there were a range of ways to get involved, each involving different levels of commitment.

A total of seven experts-by-experience were involved in the project in different roles. People with lived experience of prison were involved at all stages, from development to dissemination, to governance. We developed the initial project application with input from two people with lived-experience of imprisonment. We also engaged three experts-by-experience (MB, MC, PP) to collaborate with us on the development of recruitment materials, the recruitment and sampling strategy and the qualitative interview schedule, to facilitate recruitment and interviewing (see Chapter 4) and another (FD) to contribute to the workshops in the integration WP (see Chapter 6). We also had lived experience representation on our Oversight Committee from Paula Harriott, PPI lead for the Prison Reform Trust. We had intermittent representation at our bi-monthly research team meetings where an expert-by-experience participated in discussions about the quantitative analysis WP (see Chapter 5), the integration WP (see Chapter 6) and dissemination. We also invited comments, questions and suggestions from the prisoner policy network (PPN) led by Paula Harriott. The PPN brings together people with lived experience of prison who wish to get involved in policy work, from those who want to be kept informed to those who want to develop a more active role.

As anticipated, PPI activity evolved over the course of the project, not least in response to the pandemic and other challenges relating to the recruitment and retention of experts-by-experience. Prior to the commencement of the project, both experts-by-experience who contributed to the development of the project had to withdraw from their formal roles as co-applicant and nominated PPI representative, respectively. Despite trying different routes and methods, we found it difficult to engage individuals who were willing to perform an ongoing PPI role in the study. Some individuals that we approached told us that they would be prepared to make a one-off contribution as interview participants but were not willing to get involved in a medium- to long-term PPI capacity, such as attending research meetings. Although we engaged two individuals (MB, MC) to advise on the qualitative WP, they were only involved in discrete activities. A further expert-by-experience (PP) who had multiple roles in the study and contributed to several WPs was unable to continue his role in the project. These challenges had two main consequences: first, we completed the stakeholder consensus process with minimal input from people with lived experience and, second, we had intermittent input from people with lived experience of imprisonment at our research team meetings. Furthermore, despite the opportunities for individuals to provide feedback or to volunteer to contribute to the project as an expert-by-experience, we did not receive any comments via the website or PPN network. Our plans were also limited by the pandemic: we considered it would be inappropriate, unethical, and logistically difficult to approach new contacts during this time. We are cognisant of the fact that prison leavers may face multiple challenges upon release ranging from homelessness, health problems, unemployment, disrupted personal relationships and financial difficulties, and that these may have been barriers to their involvement in PPI activities, especially those requiring long-term or regular commitment. Other issues may have also deterred people from getting involved, such as wishing to move on after imprisonment. We found that the individuals who did get involved were those who were working in paid roles that drew on their experiential expertise.

In response to these challenges, we developed ways to maximise the PPI input we did have. To partly compensate for these gaps, we drew on the expertise of the head of a local charity (BG) with over 20 years’ experience of public involvement, who attended Project Team meetings and performed the role of ‘critical friend’. Although she did not purport to speak on behalf of people with lived experience, she brought a wealth of experience of working in the sector and put us in touch with an expert-by-experience (PP). This provided the continuity that was missing in the absence of a permanent expert-by-experience team member. Instead of convening a lay stakeholder panel during the pandemic, we sought feedback on the quality indicator selection process from Paula Harriott, who provided a non-research, lived-experience perspective.

Despite the challenges we faced, it is a strength of our approach that we responded flexibly to overcome these challenges by ensuring that the lived-experience voice was incorporated throughout the project and particularly at key stages, including the initial development of the study, in participant-facing materials and alongside other stakeholders in the final integration WP. It is also a strength of our approach that we involved people with lived experience of prison at all stages of the project, including at the crucial stage of project development. Experts-by-experience were also involved in various levels and roles, contributing to the governance (via the Oversight Committee and the research team meetings) and strategic discussions and decision-making. Several experts-by-experience were involved in practical ways by contributing to the development of accessible and appropriate participant-facing materials and assisting with recruitment. The contribution of one expert-by-experience (PP) was pivotal, as he liaised with services and individuals at a time when we were unable to physically visit potential recruitment sites due to pandemic-related restrictions. Using his existing networks, he brokered relationships between academia and some of the most vulnerable and marginalised groups in society, something that we could not have achieved in his absence. We also utilised a range of different approaches to engage with the community, including the use of Twitter and our website, and the PPN network. Although we did not receive comments on the study via the website or PPN network, we did receive some interest (including retweets and likes) on our Twitter account. It is important to provide opportunities for individuals to access information about the project without facilitation by a third party and also to create an open, safe environment where people can engage with and scrutinise research on their own terms. This involves ensuring they have access to research and opportunities to be aware of current debates and to contribute (or not) if they wish. We also developed the innovative ‘voice memo’ approach (see Chapter 6) in partnership with the expert-by-experience (FB), partly because he could not attend the workshops, but also as a ‘reasonable adjustment’ to accommodate his neurodiverse needs. This approach had strengths and limitations. It was a limitation that the lived-experience consultant could not attend the events and did not complete the survey. This meant that the contributions he made could not influence the discussion or inform other stakeholders’ thoughts and comments. This also meant that we were unable to respond to his questions. It is, however, a strength of the approach that the lived-experience consultant was able to contribute in a flexible manner and to comment freely and without interruption or contradiction. To reduce written communication and partially offset the absence of interaction between the lived-experience consultant and the other stakeholders, we held several meetings to discuss and reflect on both the process and the workshop content.

In conclusion, the impact of PPI in this project was substantial. The attendance of experts-by-experience at meetings and, by extension, as members of the research team enhanced the team’s self-awareness around use of language, patient-versus-clinician perspectives and the day-to-day reality of living in prison. The involvement of Paula Harriott from an early stage of the project (post-funding) instigated the emphasis on a two-way exchange of information with prison leavers and experts-by-experience. Accordingly, alongside quantifiable impact such as assistance with recruitment, all the experts-by-experience brought extensive knowledge and a wealth of insight to the project.

Equality and diversity

Participant representation in the quantitative work package (see Chapter 5)

Participant representation amongst stakeholders in the consensus and integration work packages (see Chapters 3 and 6)

This part of the study also relied heavily on the involvement of (professional) stakeholders.

Consensus process participants

We engaged stakeholders in the consensus process to prioritise quality indicators for data extraction in WP1 (see Chapter 3). We identified a selection of stakeholders via our networks who would be able to assess and rate the quality indicators for potential for patient benefit. Accordingly, we approached individuals with professional experience of the criminal justice system (CJS), prison health care or expertise in quality indicators or delivery of primary care to underserved groups. Our priority here was to identify individuals from a range of professional backgrounds with the knowledge and expertise required to engage with and undertake the rating process. It is possible that this resulted in limited diversity (other than gender) in this stakeholder group. We did, however, attempt to simplify the consensus process and to make it accessible for individuals without clinical backgrounds by only asking participants to rate the quality indicators according to one and not two criteria (potential for patient benefit) as originally planned and by providing a booklet containing plain-English descriptions of each of the quality indicators we were asking stakeholders to rate.

Integration process participants

We also involved stakeholders in a series of workshops to consider the findings from the various elements of Qual-P plus existing evidence about implementing quality-improvement strategies in WP4 (see Chapter 6). The strategy here was to promote the study and its findings to a much wider professional audience. This led to attendance and engagement of a much more diverse group (although limited to professionals working in health and justice).

Representation in the research team

The research comprises a range of experts who vary in professional background, experience and areas of expertise. The team includes prison GPs, an academic (community) GP, a statistician, commissioners, qualitative methodologists, junior researchers, charity management, and lived experience (described under Patient and Public Involvement and Engagement activities). Together, the team combined community and prison-specific healthcare expertise and clinical and academic experience, perspectives from the frontline, management and commissioning, and a range of healthcare providers and prisons.

Junior members received support and supervision from more senior members of the team via regular one-to-one meetings. Junior members attended conferences and other meetings to present findings, attended courses, were supported to produce peer-reviewed articles and other outputs and were involved in the development of new grants.

Representation in patient and public involvement and engagement activities

Individuals with lived experience of prison from across the country were involved in the study, aided by the use of telephone and video calls as opposed to the resource-heavy demands of face-to-face meetings.

Implications for practice

There is a loss of informational continuity between community and prison primary care, which undermines individual patient care as well as the ability to measure and improve whole-system care. Improved linkage of individual electronic health records at this interface may deliver benefits for patient care and system-level improvement.

Our work has demonstrated marked gaps and variations in achievement of quality indicators across 13 prisons served by one primary care provider which are incompletely explained by population characteristics. Such gaps and variations are likely to be a more widespread phenomenon affecting other prisons and warrant attention.

Our suite of indicators, based on routinely collected data, may serve as a foundation for an efficient and EB audit and feedback intervention, which could be scaled up and applied across the prison sector. As they are based on routinely collected data, it should be feasible for healthcare providers to adopt or adapt our data-collection templates. There is now a well-established and evolving evidence base to guide effective feedback methods, such as providing repeated rather than one-off feedback and incorporating action planning into feedback.

Suggestions for action from our briefing on opioid and gabapentinoid prescribing:

• Initiate multidisciplinary care plans for prisoner patients prescribed three or more psychotropic medicines, which include involvement from primary care, the drug and alcohol recovery team (DART), MH and the prison service.

• Adopt regular prescribing audits using routinely collected data and EB comparative feedback to prison healthcare teams that includes persuasive messaging and action plans directed at prescribers.

• Support clinicians to change prescribing practice through nationally recognised training courses, such as the RCGP courses in the management of substance misuse.

• Escalate details for the small number of prisoner patients who show intimidating behaviour towards clinicians in seeking prescribed drugs to the prison service through an agreed pathway so that ‘safe haven’ support can be provided in individual consultations.

• Potentially stigmatising attitudes and behaviours vary between individual staff members and so there is merit in tailoring current statutory and mandatory training in equality and diversity for prison staff to reduce the likelihood of such staff delivering (or withholding) treatment in a punitive fashion.

• There would be merit in providing confidentiality and wider information governance training to discipline staff so that a patient’s sensitive health information is not (either intentionally or inadvertently) made available to their peers.

• Prisons represent an ideal environment in which to encourage uptake of national screening and immunisation interventions yet uptake is variable, thus presenting an opportunity for awareness-raising amongst both staff and patients.

• Some prison-based clinical staff are deskilled in the area of long-term condition management; there is merit in reviving historical models of clinical quality whereby healthcare staff are encouraged to work part of the week in community primary care settings.

• Variation in prison healthcare performance could be addressed by providing anonymised feedback to healthcare teams for a range of indicators to enable an individual team’s performance to be gauged against their peers.

• Monitoring the reason why patients ‘did not attend’ healthcare appointments (individual choice or system constraint) should be undertaken in order to improve attendance rates and patient experience while making recommendations for resource allocation.

• Incentivising attainment of national agreed outcomes (i.e. the QOF) has enhanced the standard of community long-term condition monitoring, thus presenting an opportunity to review commissioning frameworks and key performance indicators in this regard for prison healthcare teams.

Recommendations for research

Quantitative research: We identified no consistent pattern by ethnicity in achievement of indicators. However, we noted that Asian and Asian British people were less likely to experience psychotropic polypharmacy and, along with black and Black British and Chinese people, less likely to be prescribed opioids. Does this occur because of discrimination at the point of assessing needs and prescribing or are there other factors that protect people from different ethnicities from potentially harmful prescribing?

We identified no rigorous evaluations of strategies to improve the quality of primary care in prisons. A range of single or combined improvement strategies, informed by a wider evidence base, are promising and amenable to evaluation through randomised trial or rigorous quasi-experimental evaluation designs.

We have demonstrated the feasibility of using routinely collected data to measure quality of care at scale in prison primary care. This would form an ideal platform for an audit and feedback programme to improve care. While we have specifically suggested audit and feedback as an improvement strategy for prisons, given its known effectiveness in improving the quality of health care across different settings it would be useful to establish its effectiveness in this setting.

Qualitative research: One of the main issues identified through our qualitative research findings which requires more in-depth and further understanding is that of healthcare access for people in prison. We came across the issue of DNAs for primary care appointments inside the prison. Further qualitative research, most likely ethnographic in nature, is needed to understand why DNA rates are so high and what solutions can be implemented to reduce DNAs in order to ensure people in prison have timely access to health care. Our research consciously focused on contributing aspects of health inequalities and we were mindful to examine indicators related to age and gender. However, there is a distinct lack of qualitative research about the racialised experience of receiving/accessing health care while in prison. While research exists about being an ethnic minority prisoner in general, there is virtually nothing about the healthcare needs and experiences of ethnic minority prisoners. Lastly, staffing levels in prison came out strongly through our qualitative interviews. While the acute and community sector has research evidence about safer staffing, there is scant evidence about its impacts on the delivery of health care in the prison setting.

Contributions of authors

Sue Bellass (https://orcid.org/0000-0001-9383-4116) (Research Fellow, qualitative researcher) undertook all fieldwork and analysis for the qualitative work package and was the lead for the scoping review. She also supported both stakeholder consensus processes. Sue wrote Chapters 1, 2, 4 and co-wrote Chapter 6.

Krysia Canvin (https://orcid.org/0000-0001-6571-6411) (Programme Manager, qualitative researcher) managed the programme of research throughout and worked in all work packages but most significantly the qualitative research. She conducted the secondary qualitative analysis focusing on mental health. Krysia co-wrote Chapters 3, 6 and 7.

Tracey Farragher (https://orcid.org/0000-0002-1968-6378) (Senior Lecturer, epidemiologist) led the routinely collected data work package and the quantitative part of the mental health analysis. She conducted all statistical analyses. Tracey co-wrote Chapters 5 and 7.

Kate McLintock (https://orcid.org/0000-0002-9479-263X) (Clinical Academic and Prison GP) provided clinical interpretation to all work packages and worked on the routinely collected data work package. Kate co-wrote Chapter 5.

Nat Wright (https://orcid.org/0000-0003-3547-3724) (Clinical Research Lead and Prison GP) provided clinical interpretation to all work packages and facilitated access to the routinely collected data.

Pip Hearty (https://orcid.org/0000-0002-0172-505X) (Research Fellow, mixed methods researcher) worked on data extraction in the routinely collected data work package and facilitated access to participants in the qualitative work package.

Nicola Seanor (https://orcid.org/0000-0001-5651-2177) (Joint Lead for Health and Justice Commissioning Support) provided a commissioner and policy interpretation to all work packages.

Marie Cunningham (https://orcid.org/0000-0002-1871-4728) (Joint Lead for Health and Justice Commissioning Support) provided a commissioner, policy and clinical interpretation to all work packages.

Robbie Foy (https://orcid.org/0000-0003-0605-7713) (Clinical Professor of Primary Care) was joint Principal Investigator programme of research and worked most significantly on both stakeholder consensus work packages and the routinely collected data work package. He co-wrote Chapters 3, 5 and 6.

Laura Sheard (https://orcid.org/0000-0002-9241-8361) (Associate Professor, qualitative methodologist) was joint Principal Investigator of the programme of research and worked most significantly on the qualitative work package. She wrote Chapter 8.

All authors reviewed the contents of this final report as a whole and provided revisions and comments.

Acknowledgements

We thank all of the people who participated in interviews for the qualitative work package and the many individuals and organisations who assisted with participant recruitment but cannot be named here to protect participants’ anonymity.

We are sincerely grateful to Stephen Roddis for his substantial efforts in ensuring a comprehensive data extract at Spectrum CIC and Stephen Graham for facilitating this process. Our thanks also to Bridget Gill from Spectrum People for attending research team meetings and acting as a ‘critical friend’. We are grateful to the members of the project Oversight Committee who provided invaluable guidance and support and facilitated the dissemination of emerging findings: James Woodall (chair), Paula Harriott, Eamonn O’Moore, Tim Doran, Richard Keers, Maria Panagioti, Tim Kirkpatrick, Sarah Bromley and Kathryn Waldegrave.

We also thank Wendy Hobson and Anna Halliday and other staff from the University of Leeds and Sharon Medley and George Charlesworth at Spectrum CIC for their administrative support, alongside Paul Eckhart for his proofreading and editorial work. Martin Simpson-Scott at NIHR made our lives easier with his swift and helpful responses to all our queries.

We especially wish to thank everyone with lived experience of prison who contributed their considerable expertise and undoubtedly improved the quality of the project: Fabien Decodts, Phil Pearce, Michaela Booth and Marc Conway, and the two individuals originally involved (not named to protect their identity).

Data-sharing statement

All data generated that can be shared are contained within the report. All data queries and requests should be submitted to the corresponding author for consideration.

Ethics statement

The whole programme of research was granted ethical approval by University of Leeds School of Medicine Research Ethics Committee on 17 July 2019 (Ref: 18-093).

Permission from the prison service was required to interview people in the community who were on probation at the time of the interview. This was granted by HMPPS National Research Committee on 24 December 2019 (Ref: 2019-383). The routinely collected data work package was exempted from requiring ethical review by HMPPS NRC and we were issued with a letter of exemption on 19 March 2019.

Information governance statement

University of Leeds is committed to handling all personal information in line with the UK Data Protection Act (2018) and the General Data Protection Regulation (EU GDPR) 2016/679. Under Data Protection legislation University of Leeds is the Data Processor and Data Controller, and we process personal data in accordance with their instructions. You can find out more about how we handle personal data, including how to exercise your individual rights and the contact details for DHSC’s Data Protection Officer: dpo@leeds.ac.uk.

Disclosure of interests

Full disclosure of interests: Completed ICMJE forms for all authors, including all related interests, are available in the toolkit on the NIHR Journals Library report publication page at https://doi.org/10.3310/GRFV4068.

Primary conflicts of interest: Sue Bellass: None declared.

Krysia Canvin reports that she has received funding from UKRI ESRC (2021–2) and is a member of an independent oversight committee: The Prevention Of Suicide Behaviour in Prison: Enhancing Access to Therapy (PROSPECT) Programme (NIHR Programme Grants for Applied Research -RP-PG-0218-20006, 2020–present).

Tracey Farragher reports that she is Chair of MBRC (NIHR Manchester Biomedical Research Centre) Health Inequalities Steering Group (HISG). She was also a board member for HS&DR commissioned calls panel.

Kate McLintock reports that she was in paid employment with Spectrum Community Health Community Interest Company (April 2019–October 2021).

Nat Wright reports that he is the NIHR Yorkshire and Humber primary care specialty lead and is a co-applicant on a recently successfully funded NIHR programme grant. He also sits on the Royal College of General Practitioners Secure Environments Group and also the NHSE England Secure Environments Clinical Reference Group. Previously, he was a panel member for two HTA committees. In the last year, he has received honoraria from Camurus and Indivior pharmaceutical companies for training and writing and activities.

Pip Hearty: None declared.

Nicola Seanor reports that she is Non-Executive Director at Calderdale and Huddersfield Foundation Trust and Lead for Health and Justice at NECS.

Marie Cunningham: None declared.

Robbie Foy reports that he is in receipt of several grants from National Institute for Health and Care Research and receives grant funding from Yorkshire Cancer Research (YCR). He is Chair of three independent oversight committees: Implementing improved asthma self-management as routine (IMP2ART, PGfAR, 2018–present); Acne Care Online (ACO; PGfAR, 2022–present); and Social Influence Interventions for Clinical Behaviour Change Among Health Professionals (SOCIAL, HS&DR 2018–20). He is also Chair of the Data Monitoring Committee At-Risk Registers Integrated into primary care to Stop Asthma crises (ARRISA-UK, HTA, 2015–present) and Co-chair of the Implementation Strategy Group, National Institute for Health and Care Excellence. Previously, he was a member of the Dissemination Centre Advisory Group. He also reports that he is a member of the primary care-led post diagnostic Dementia care (PriDem; Alzheimer’s Society; 2019–present).

Laura Sheard reports that she is in receipt of several grants from ESRC, UKPRP, NIHR (PGfAR, HS&DR, PHR, HTA) and has recently sat as a guest committee member on several funding boards (RfPB mental health, MRC Qualitative methods, SBRI Implementation). She is associate editor for Implementation Science.

Publications

Bellass S, Canvin K, McLintock K, Wright N. Integrating primary care across the prison and community interface. Br J Gen Pract 2021;71(703):56–7. https://doi.org/10.3399/bjgp21X714653

Bellass S, Canvin K, McLintock K, Wright N, Farragher T, Foy R, Sheard L. Quality indicators and performance measures for prison healthcare: a scoping review. Health Justice 2022;10(13). https://doi.org/10.1186/s40352-022-00175-9

https://doi.org/10.3399/bjgp21X714653

Bellass S, Canvin K, Sheard L. ‘Trying to battle a very slow version of the system that exists outside’: experiences of waiting for healthcare in English prisons (in review with Health).

Blackaby J, Byrne J, Bellass S, Canvin K, Foy R. Interventions to improve the implementation of evidence-based healthcare in prisons: a scoping review (in review with BMC Health and Justice).

Disclaimers

This article presents independent research funded by the National Institute for Health and Care Research (NIHR). The views and opinions expressed by authors in this publication are those of the authors and do not necessarily reflect those of the NHS, the NIHR, the HSDR programme or the Department of Health and Social Care. If there are verbatim quotations included in this publication the views and opinions expressed by the interviewees are those of the interviewees and do not necessarily reflect those of the authors, those of the NHS, the NIHR, the HSDR programme or the Department of Health and Social Care.

NICE quality and outcomes framework indicators47,51

1. The contractor establishes and maintains a register of patients with AF. AF001.

2. The contractor establishes and maintains a register of patients with asthma, excluding patients with asthma who have been prescribed no asthma-related drugs in the preceding 12 months. AST001.

3. The contractor establishes and maintains a register of all cancer patients defined as a ‘register of patients with a diagnosis of cancer excluding non-melanotic skin cancers diagnosed on or after 1 April 2003’. CAN001.

4. The percentage of patients aged 79 years or under, with CHD, in whom the last blood pressure reading (measured in the preceding 12 months) is 140/90 mmHg or less. CHD008.

5. The percentage of patients aged 80 years or over, with CHD, in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. CHD009.

6. The contractor establishes and maintains a register of patients with CHD. CHD01.

7. The contractor establishes and maintains a register of patients with COPD. COPD001.

8. The percentage of patients with COPD and Medical Research Council (MRC) dyspnoea scale ≥ 3 at any time in the preceding 12 months, with a subsequent record of an offer of referral to a pulmonary rehabilitation programme. COPD008.

9. The proportion of women eligible for screening and aged 25–49 years at the end of reporting period whose notes record than an adequate cervical screening test has been performed in the preceding 3 years and 6 months. CS005.

10. The proportion of women eligible for screening and aged 50–64 years and the end of reporting period whose notes record that an adequate cervical screening test has been performed in the previous 5 years and 6 months. CS006.

11. In those patients with a new diagnosis of hypertension aged 30 or over and who have not attained the age of 75, recorded between the preceding 1 April and 31 March (excluding those with pre-existing CHD, diabetes, stroke and/or TIA), who have a recorded CVD risk assessment score [using an assessment tool agreed with NHS Commissioning Board (CB)] of ≥ 20% in the preceding 12 months: the percentage who are currently treated with statins. CVD-PP001.

12. The contractor establishes and maintains a register of patients diagnosed with dementia. DEM001.

13. The percentage of patients with diabetes, on the register, without moderate or severe frailty, on the register, in whom the last blood pressure reading (measured in the preceding 12 months) is 140/80 mmHg or less. DM019.

14. The percentage of patients with diabetes, on the register, with moderate or severe frailty, on the register, in whom the last International Federation of Clinical Chemistry (IFCC)-HbA_1c is 75 mmol/mol or less in the preceding 12 months. DM021.

15. The percentage of patients with diabetes, on the register, aged 40 years and over, with no history of CVD and without moderate or severe frailty, who are currently treated with a statin (excluding patients with type 2 diabetes and a CVD risk score of < 10% recorded in the preceding 3 years). DM022.

16. The percentage of patients with diabetes, on the register, and a history of CVD (excluding haemorrhagic stroke) who are currently treated with a statin. DM023.

17. The percentage of patients with diabetes, on the register, without moderate or severe frailty, on the register, in whom the last IFCC-HbA_1c is 58 mmol/mol or less in the preceding 12 months. NM157.

18. The contractor establishes and maintains a register of patients aged 18 or over receiving drug treatment for epilepsy. EP001.

19. The contractor establishes and maintains a register of patients with heart failure. HF001.

20. The contractor establishes and maintains a register of patients with established hypertension. HYP001.

21. The percentage of patients aged 79 years or under, with hypertension, in whom the last blood pressure reading (measured in the preceding 12 months) is 140/90 mmHg or less. HYP003.

22. The percentage of patients aged 80 years and over, with hypertension, in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. HYP007.

23. The contactor establishes and maintains a register of patients with schizophrenia, bipolar affective disorder and other psychoses and other patients on lithium therapy. MH001.

24. The percentage of patients with schizophrenia, bipolar affective disorder and other psychoses who have a record of BMI in the preceding 12 months. MH006.

25. The contractor establishes and maintains a register of patients aged 18 years or over with a BMI ≥ 30 in the preceding 12 months. OB001.

26. The contractor establishes and maintains a register of all patients in need of palliative care/support irrespective of age. PC001.

27. The contractor can demonstrate continuous quality-improvement activity focused upon prescribing safety as specified in the QOF guidance. QI001.

28. The contractor has participated in network activity to regularly share and discuss learning from quality-improvement activity as specified in the QOF guidance. This would usually include participating in a minimum of two peer-review meetings. QI002.

29. The contractor can demonstrate continuous quality-improvement activity focused on end-of-life care as specified in the QOF guidance. QI003.

30. The contractor has participated in network activity to regularly share and discuss learning from quality-improvement activity as specified in the QOF guidance. This would usually include participating in a minimum of two network peer-review meetings. QI004.

31. The percentage of patients aged 80 years or over, with a history of stroke or TIA, in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. STAI011.

32. The contractor establishes and maintains a register of patients with stroke or TIA. STIA001.

33. The percentage of patients aged 79 years or under, with a history of stroke or TIA, in whom the last blood pressure reading (measured in the preceding 12 months) is 140/90 mmHg or less. STIA010.

34. The percentage of patients with CHD in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. CHD002.

35. The percentage of patients with CHD whose last measured cholesterol (measured in the preceding 12 months) is 5 mmol/l or less. CHD003.

36. The percentage of patients on the CKD register in whom the last blood pressure reading (measured in the preceding 12 months) is 140/85 mmHg or less. CKD002.

37. The percentage of patients on the CKD register whose notes have a record of a urine ACR [or protein : creatinine ratio (PCR)] test in the preceding 12 months. CKD004.

38. The contractor establishes and maintains a register of women aged 54 or under who have been prescribed any method of contraception at least once in the last year, or other clinically appropriate interval, for example last 5 years for an intrauterine system (IUS). CON001.

39. The percentage of women, on the register, prescribed emergency hormonal contraception one or more times in the preceding 12 months by the contractor who have received information from the contractor about long-acting reversible contraception at the time or within 1 month of the prescription. CON003.

40. The percentage of patients with COPD with a record of FEV1 in the preceding 12 months. COPD004.

41. The percentage of patients with COPD and MRC dyspnoea grade ≥ 3 at any time in the preceding 12 months, with a record of oxygen saturation value within the preceding 12 months. COPD005.

42. The contractor has a protocol that is in line with national guidance agreed with the NHS CB for the management of cervical screening, which includes staff training, management of patient call/recall, exception reporting and the regular monitoring of inadequate sample rates. CS001.

43. The percentage of women aged 25 or over and who have not attained the age of 65 whose notes record that a cervical screening test has been performed in the preceding 5 years. CS002.

44. The contractor has a policy for auditing its cervical screening service and performs an audit of inadequate cervical screening tests in relation to individual sample-takers at least every 2 years. CS004.

45. The percentage of patients diagnosed with hypertension (diagnosed after or on 1 April 2009) who are given lifestyle advice in the preceding 12 months for: smoking cessation, safe alcohol consumption and healthy diet. CVD-PP002.

46. The percentage of patients with a new diagnosis of dementia recorded in the preceding 1 April to 31 March with a record of FBC, calcium, glucose, renal and liver function, thyroid function tests, serum vitamin B₁₂ and folate levels recorded between 12 months before or 6 months after entering on to the register. DEM005.

47. The percentage of patients with diabetes, on the register, whose last measured total cholesterol (measured within the preceding 12 months) is 5 mmol/l or less. DM004.

48. The percentage of patients with diabetes, on the register, who have a record of an ACR test in the preceding 12 months. DM005

49. The percentage of patients with diabetes, on the register, in whom the last IFCC-HbA_1c is 59 mmol/mol or less in the preceding 12 months. DM007.

50. The percentage of patients with diabetes, on the register, in whom the last IFCC-HbA_1c is 64 mmol/mol or less in the preceding 12 months. DM008.

51. The percentage of patients with diabetes, on the register, in whom the last IFCC-HbA_1c is 75 mmol/mol or less in the preceding 12 months. DM009.

52. The percentage of patients with diabetes, on the register, who have a record of retinal screening in the preceding 12 months. DM011.

53. The percentage of patients 18 or over on drug treatment for epilepsy who have been seizure-free for the last 12 months recorded in the preceding 12 months. EP002.

54. The percentage of women aged 18 or over and who have not attained the age of 55 who are taking antiepileptic drugs who have a record of information and counselling about contraception, conception and pregnancy in the preceding 12 months. EP003.

55. The percentage of patients with hypertension in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. HYP006.

56. The percentage of patients on the learning disability register with Down syndrome aged 18 or over who have a record of blood thyroid-stimulating hormone (TSH) in the preceding 12 months. LD002.

57. The percentage of patients aged 40 or over with schizophrenia, bipolar affective disorder and other psychoses who have a record of total cholesterol–HDL ratio in the preceding 12 months. MH004.

58. The percentage of patients aged 40 or over with schizophrenia, bipolar affective disorder and other psychoses who have a record of blood glucose or HbA_1c in the preceding 12 months. MH005.

59. The percentage of patients with schizophrenia, bipolar affective disorder and other psychoses who have a record of alcohol consumption in the preceding 12 months. MH007.

60. The percentage of women aged 25 or over and who have not attained the age of 65 with schizophrenia, bipolar affective disorder and other psychoses whose notes record that a cervical screening test has been performed in the preceding 5 years. MH008.

61. The percentage of women aged 25 or over and who have not attained the age of 65 with schizophrenia, bipolar affective disorder and other psychoses whose notes record that a cervical screening test has been performed in the preceding 5 years. MH008.

62. The percentage of patients on lithium therapy with a record of serum creatinine and TSH in the preceding 9 months. MH009.

63. The percentage of patients on lithium therapy with lithium levels in the therapeutic range in the preceding 4 months. MH010.

64. The percentage of patients on the CKD register with hypertension and proteinuria who are currently treated with renin–angiotensin system antagonists. NM84.

65. The percentage of patients aged 50 or over, and who have not attained the age of 75, with a fragility fracture on or after 1 April 2012, in whom osteoporosis is confirmed on a dual-energy X-ray absorptiometry (DEXA) scan, who are currently treated with an appropriate bone-sparing agent. OST002.

66. The percentage of patients aged 75 or over with a record of a fragility fracture on or after 1 April 2014 and a diagnosis of osteoporosis, who are currently treated with a bone-sparing agent. OST005.

67. The percentage of patients with peripheral arterial disease (PAD) in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. PAD002.

68. The percentage of patients with peripheral arterial disease in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. PAD002.

69. The percentage of patients with peripheral arterial disease in whom the last measured total cholesterol (measured in the preceding 12 months) is 5 mmol/l or less. PAD003.

70. The percentage of patients with peripheral arterial disease with a record in the preceding 12 months that aspirin or an alternative antiplatelet is being taken. PAD004.

71. The contractor has regular (at least 3 monthly) multidisciplinary case-review meetings where all patients on the palliative care register are discussed. PC002.

72. The percentage of patients with rheumatoid arthritis aged 30 or over and who have not attained the age of 85 who have had a cardiovascular risk assessment using a CVD risk-assessment tool adjusted for RA in the preceding 12 months. RA003.

73. The percentage of patients aged 50 or over and who have not attained the age of 91 with rheumatoid arthritis who have had an assessment of fracture risk using a risk-assessment toll adjusted for RA in the preceding 24 months. RA004.

74. The percentage of patients aged 15 or over whose notes record smoking status in the preceding 24 months. SMOK001.

75. The contractor supports patients who smoke in stopping smoking by a strategy which includes providing literature and offering appropriate therapy. SMOK003.

76. The percentage of patients with a stroke shown to be non-haemorrhagic, or a history of TIA whose last measured total cholesterol (measured in the preceding 12 months) is 5 mmol/l or less. STAI005.

77. The percentage of patients with a history of a stroke or TIA in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. STIA003.

78. The percentage of patients with a stroke or TIA (diagnosed on or after 1 April 2014) who have a record of a referral for further investigation between 3 months before or 1 month after the date of the latest recorded or stroke or the first TIA. STIA008.

79. The contractor establishes and maintains a register of patients with hypothyroidism who are currently treated with levothyroxine. THY001.

80. The percentage of patients with hypothyroidism, on the register, with thyroid function tests recorded in the preceding 12 months. THY002.

81. In those patients with AF whose latest record of a CHADS2 score is > 1, the percentage of patients who are currently treated with anticoagulation therapy. AF004.

82. In those patients with AF in whom there is record of a CHADS2 score of 1 the percentage of patients who are currently treated with anticoagulation drug therapy or antiplatelet therapy. AF005.

83. The percentage of patients with a history of MI (on or after 1 April 2011) currently treated with an ACE-I (or ARB if ACE-I-intolerant), aspirin or an alternative antiplatelet therapy, beta-blocker and statin. CHD006.

84. The percentage of patients on the CKD register with hypertension and proteinuria who are currently treated with an ACE-I or ARB. CKD003.

85. The percentage of patients with diabetes, on the register, in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. NM01.

86. The percentage of patients with diabetes, on the register, in whom the last blood pressure reading (measured in the preceding 12 months) is 140/80 mmHg or less. NM02.

87. The percentage of women under the age of 55 years who are taking antiepileptic drugs who have a record of information and counselling about contraception, conception and pregnancy in the preceding 15 months. NM03.

88. Percentage of patients on the Learning Disability register with Down syndrome aged 18 and over who have a record of blood TSH in the previous 15 months (excluding those who are on the thyroid disease register). NM04.

89. The percentage of patients with a new diagnosis of dementia recorded in the preceding 1 April to 31 March with a record of FBC, calcium, glucose, renal and liver function, thyroid function tests, serum vitamin B₁₂ and folate levels recorded between 6 months before or after entering on to the register. NM09.

90. The percentage of patients with hypothyroidism, on the register, with thyroid function tests recorded in the preceding 12 months (Inherited). NM100.

91. The percentage of patients aged 8 or over with asthma (diagnosed on or after 1 April 2006), on the register, with measures of variability or reversibility recorded between 3 months before or any time after diagnosis (Inherited). NM101.

92. The percentage of patients with asthma aged 14 or over and who have not attained the age of 20, on the register, in whom there is a record of smoking status in the preceding 12 months (Inherited). NM102.

93. The percentage of patients with COPD (diagnosed on or after 1 April 2011) in whom the diagnosis has been confirmed by post-bronchodilator spirometry between 3 months before and 12 months after entering on to the register (Inherited). NM103.

94. The percentage of patients with COPD who have had a review, undertaken by a healthcare professional, including an assessment of breathlessness using the MRC dyspnoea scale in the preceding 12 months (Inherited). NM104.

95. The percentage of patients with COPD with a record of FEV1 in the preceding 12 months (Inherited). NM105.

96. The percentage of patients with COPD who have had influenza immunisation in the preceding 1 August to 31 March (Inherited). NM106.

97. The percentage of patients diagnosed with dementia whose care plan has been reviewed in a face-to-face review in the preceding 12 months (Inherited). NM107.

98. The percentage of patients with schizophrenia, bipolar affective disorder and other psychoses who have a comprehensive care plan documented in the record, in the preceding 12 months, agreed between individuals, their family and/or carers as appropriate (Inherited). NM108.

99. The percentage of patients on the CKD register whose notes have a record of a urine ACR (or PCR) test in the preceding 12 months (Inherited). NM109.

100. The percentage of patients aged 18 or over on drug treatment for epilepsy who have been seizure-free for the last 12 months recorded in the preceding 12 months (Inherited). NM110.

101. The contractor supports patients who smoke in stopping smoking by a strategy which includes providing literature and offering appropriate therapy (Inherited). NM113.

102. The percentage of women, on the register, prescribed an oral or patch contraceptive method in the preceding 12 months who have also received information from the contractor about long-acting reversible methods of contraception in the preceding 12 months (Inherited). NM114.

103. The percentage of patients on the CKD register in whom the last blood pressure reading (measured in the preceding 12 months) is 140/90 mmHg or less (Inherited). NM117.

104. The percentage of patients with CHD whose last measured total cholesterol (measured in the preceding 12 months) is 5 mmol/l or less (Inherited). NM118.

105. The percentage of patients with schizophrenia, bipolar affective disorder and other psychoses aged 25–84 (excluding those with pre-existing CHD, diabetes, stroke and/or TIA) who have had a CVD risk assessment performed in the preceding 12 months (using an assessment tool agreed with NHS England). NM120.

106. The percentage of patients with CHD, stroke or TIA, diabetes, hypertension, peripheral arterial disease, heart failure, COPD, asthma and/or rheumatoid arthritis who have had a BMI recorded in the preceding 12 months. NM121.

107. The percentage of patients with CHD, stroke or transient ischaemic attack, diabetes and/or COPD who have influenza immunisation in the preceding 1 August and 31 March. NM122.

108. The percentage of patients with a new diagnosis of depression and/or anxiety disorder in the preceding 1 April to 31 March, whose notes record an offer of referral for psychological treatment within 3 months of the date of diagnosis (Inherited). NM123.

109. The percentage of patients with schizophrenia, bipolar affective disorder or other psychoses whose notes record smoking status in the preceding 12 months. NM124.

110. The percentage of patients with schizophrenia, bipolar affective disorder or other psychoses who are recorded as current smokers who have a record of an offer of support and treatment within the preceding 12 months. NM125.

111. The percentage of patients with any or any combination of the following conditions: CHD, PAD, stroke or TIA, hypertension, diabetes, COPD, CKD or asthma, whose notes record smoking status in the preceding 12 months. NM126.

112. The percentage of patients with any or any combination of the following conditions: CHD, PAD, stroke or TIA, hypertension, diabetes, COPD, CKD, asthma, who are recorded as current smokers who have a record of an offer of support and treatment within the preceding 12 months. NM127.

113. The contractor establishes and maintains a register of patients aged 18 or over with a BMI ≥ 25 in the preceding 12 months. NM128.

114. The percentage of patients aged 18 and over with schizophrenia, bipolar affective disorder and other psychoses who have a record of total cholesterol:HDL ratio in the preceding 12 months. NM129.

115. The percentage of patients with diabetes with a record of a foot examination and risk classification: (1) low risk (normal sensation, palpable pulses), (2) increased risk (neuropathy or absent pulses), (3) high risk (neuropathy or absent pulses plus deformity or skin changes or previous ulcer) or (4) ulcerated foot within the preceding 15 months. NM13.

116. The percentage of patients aged 18 years and over with schizophrenia, bipolar affective disorder and other psychoses who have a record of blood glucose or HbA_1c in the preceding 12 months. NM130.

117. The percentage of patients with diabetes with a record of testing of foot sensation using a 10 g monofilament within the preceding 12 months. NM131.

118. The percentage of patients aged 25–84 years with a new diagnosis of hypertension or type 2 diabetes, recorded between the preceding 1 April and 31 March (excluding those with pre-existing CHD, stroke and/or TIA) who have had a consultation for cardiovascular risk assessment using the QRISK2 risk assessment tool between 3 months before and 3 months after date of diagnosis (Inherited). NM132.

119. In those patients with a new diagnosis of hypertension or type 2 diabetes aged 25–84 years, recorded between the preceding 1 April and 31 March (excluding those with pre-existing CHD, stroke and/or TIA), who have a recorded CVD risk-assessment score (using the QRISK2 assessment tool) of > 20% in the preceding 12 months: the percentage who are currently treated with statins (unless there is a contraindication). NM133.

120. The percentage of patients with diabetes, on the register, who have had influenza immunisation in the preceding 1 August to 31 March (Inherited). NM139.

121. The percentage of patients with stroke or TIA who have had influenza immunisation in the preceding 1 August to 31 March (Inherited). NM140.

122. The percentage of patients with schizophrenia, bipolar affective disorder and other psychoses who have a record of alcohol consumption in the preceding 15 months. NM15.

123. The percentage of patients with a diagnosis of heart failure (diagnosed on or after 1 April 2006) which has been confirmed by an echocardiogram or by specialist assessment 3 months before or 12 months after entering on to the register (Inherited). NM16.

124. The percentage of patients with schizophrenia, bipolar affective disorder and other psychoses who have a record of BMI in the preceding 15 months. NM16.

125. The percentage of patients with schizophrenia, bipolar affective disorder and other psychoses who have a record of blood pressure in the preceding 15 months. NM17.

126. The percentage of patients with asthma, on the register, who have had an asthma review in the preceding 12 months that includes an assessment of asthma control using the three RCP questions. NM23.

127. The percentage of patients newly diagnosed with diabetes, on the register, in the preceding 1 April to 31 March who have a record of being referred to a structured education programme within 9 months after entry on to the diabetes register. NM27.

128. The percentage of patients with diabetes who have a record of a dietary review by a suitably competent professional in the preceding 15 months. NM28.

129. The contractor establishes and maintains a register of patients: (1) aged 50 or over and who have not attained the age of 75 with a record of a fragility fracture on or after 1 April 2012 and a diagnosis of osteoporosis confirmed on DEXA scan, and (2) aged 75 or over with a record of a fragility fracture on or after 1 April 2014 and a diagnosis of osteoporosis. NM29.

130. The contractor establishes and maintains a register of patients with peripheral arterial disease. NM32.

131. The percentage of patients with peripheral arterial disease with a record in the preceding 15 months that aspirin or an alternative antiplatelet is being taken. NM33.

132. The percentage of patients with peripheral arterial disease in whom the last measured total cholesterol (measured in preceding 15 months) is 5.0 mmol/l or less. NM35.

133. The percentage of patients with hypertension aged 16–74 years in whom there is an annual assessment of physical activity, using the General Practice Physical Activity Questionnaire (GPPAQ), in the preceding 15 months. NM36.

134. The percentage of patients with hypertension aged 16–74 years who score ‘less than active’ on the GPPAQ in the preceding 15 months, who also have a record of a brief intervention in the preceding 15 months. NM37.

135. The percentage of patients with any or any combination of the following conditions: CHD, PAD, stroke or TIA, hypertension, diabetes, COPD, CKD, asthma, schizophrenia, bipolar affective disorder or other psychoses who are recorded as current smokers who have a record of an offer of support and treatment within the preceding 12 months. NM38.

136. The percentage of patients with any or any combination of the following conditions: CHD, PAD, stroke or TIA, hypertension, diabetes, COPD, CKD, asthma, schizophrenia, bipolar affective disorder or other psychoses who smoke whose notes contain a record of an offer of support and treatment within the preceding 15 months. NM39.

137. The percentage of patients aged 15 years and over who are recorded as current smokers who have a record of an offer of support and treatment within the preceding 24 months. NM40.

138. The contractor establishes and maintains a register of all patients aged 17 or over with diabetes mellitus, which specifies the type of diabetes where a diagnosis has been confirmed. NM41.

139. The percentage of patients with COPD and MRC Dyspnoea Scale ≥ 3 at any time in the preceding 15 months, with a subsequent record of an offer of referral to a pulmonary rehabilitation programme. NM47.

140. The percentage of patients with heart failure diagnosed within the preceding 15 months with a subsequent record of an offer of referral for an exercise-based rehabilitation programme within the preceding 15 months. NM48.

141. The percentage of patients with a new diagnosis of depression in the preceding 1 April to 31 March who have had a bio-psychosocial assessment by the point of diagnosis. NM49.

142. The percentage of patients with a new diagnosis of depression in the preceding 1 April to 31 March who have been reviewed within 10–35 days of the date of diagnosis. NM50.

143. The percentage of male patients with diabetes with a record of being asked about erectile dysfunction in the preceding 15 months. NM51.

144. The percentage of male patients with diabetes who have a record of erectile dysfunction with a record of advice and assessment of contributory factors and treatment options in the preceding 15 months. NM52.

145. The percentage of patients under 80 years old with hypertension in whom the last recorded blood pressure (measured in the preceding 9 months) is 140/90 or less. NM53.

146. The percentage of patients aged 80 years and over with hypertension in whom the last recorded blood pressure (measured in the preceding 9 months) is 150/90 or less. NM54.

147. The practice can produce a register of all patients aged 16 years and over with rheumatoid arthritis. NM55.

148. The percentage of patients with rheumatoid arthritis aged 30–84 years who have had a cardiovascular risk assessment using a CVD risk assessment tool adjusted for RA in the preceding 15 months. NM56.

149. The percentage of patients aged 50–90 years with rheumatoid arthritis who have had an assessment of fracture risk using a risk-assessment tool adjusted for RA in the preceding 27 months. NM57.

150. The percentage of patients with rheumatoid arthritis, on the register, who have had a face-to-face review in the preceding 12 months. NM58.

151. The percentage of patients with diabetes who have a record of an ACR test in the preceding 15 months. NM59.

152. The percentage of patients with a stroke shown to be non-haemorrhagic or a history of TIA whose last measured total cholesterol (measured in the preceding 15 months) is 5 mmol/l or less. NM60.

153. The percentage of patients aged 40 years and over with a blood pressure measurement recorded in the preceding 5 years. NM61.

154. The percentage of patients with cancer diagnosed within the preceding 15 months who have a review recorded as occurring within 3 months of the practice receiving confirmation of the diagnosis. NM61.

155. The percentage of patients with dementia with the contact details of a named carer on their record. NM64.

156. The percentage of patients with dementia (diagnosed on or after 1 April 2014) who have a record of attendance at a memory-assessment service up to 12 months before entering on to the register. NM65.

157. The percentage of patients with a new diagnosis of hypertension (diagnosed on or after 1 April 2014) which has been confirmed by ambulatory blood pressure monitoring (ABPM) or home blood pressure monitoring (HBPM) in the 3 months before entering on to the register. NM66.

158. The percentage of patients aged 79 or under with peripheral arterial disease in whom the last blood pressure reading (measured in the preceding 12 months) is 140/90 mmHg or less. NM67.

159. The percentage of patients aged 79 or under with CHD in whom the last blood pressure reading (measured in the preceding 12 months) is 140/90 mmHg or less. NM68.

160. The percentage of patients aged 79 or under with stroke or TIA in whom the last blood pressure reading (measured in the preceding 12 months) is 140/90 mmHg or less. NM69.

161. The percentage of women with diabetes aged 17 or over and who have not attained the age of 45 who have a record of being given information and advice about pregnancy or conception or contraception tailored to their pregnancy and contraceptive intentions recorded in the preceding 12 months. NM70.

162. The percentage of women with epilepsy aged 18 or over and who have not attained the age of 45 who are taking antiepileptic drugs who have a record of being given information and advice about pregnancy or conception or contraception tailored to their pregnancy and contraceptive intentions recorded in the preceding 12 months. NM71.

163. The contractor establishes and maintains a register of patients with learning disabilities. NM73.

164. The percentage of patients with diabetes who have had the following care processes performed in the preceding 12 months: BMI measurement; BP measurement; HbA_1c measurement; cholesterol measurement; record of smoking status; foot examination; albumin–creatinine ratio; serum creatinine measurement. NM74.

165. The percentage of patients with a new diagnosis of hypertension in the preceding 1 April to 31 March who have a record of urinary albumin–creatinine ratio test in the 3 months before or after the date of entry to the hypertension register. NM75.

166. The percentage of patients with a new diagnosis of hypertension in the preceding 1 April to 31 March who have a record of a test for haematuria in the 3 months before or after the date of entry to the hypertension register. NM76.

167. The percentage of patients with a new diagnosis of hypertension in the preceding 1 April to 31 March who have a record of a 12-lead electrocardiogram (ECG) performed in the 3 months before or after the date of entry to the hypertension register. NM77.

168. The percentage of women with schizophrenia, bipolar affective disorder or other psychoses under the age of 45 years who have been given information and advice about pregnancy, conception or contraception tailored to their pregnancy and contraceptive intentions recorded in the preceding 12 months. NM78.

169. The percentage of patients who had a MI in the preceding 1 April to 31 March and who are currently being treated with ACE-I (or ARB if ACE-I-intolerant), dual antiplatelet therapy, beta-blocker and a statin. NM79.

170. The percentage of patients with a history of MI (more than 12 months ago) who are currently being treated with an ACE-I (or ARB if ACE-I intolerant), aspirin (or clopidogrel) (or anticoagulant drug therapy) and a statin and a beta-blocker for those patients with left ventricular systolic dysfunction. NM80.

171. The percentage of patients with AF in whom stroke risk has been assessed using the CHA2DS2-VASc score risk stratification scoring system in the preceding 12 months (excluding those patients with a previous CHADS2 or CHA2DS2-VASc score of 2 or more). NM81.

172. In those patients with AF with a record of a CHA2DS2-VASc score of 2 or more, the percentage of patients who are currently treated with anticoagulation drug therapy. [Patients with a previous score of 2 or above using CHADS2, recorded prior to (implementation date) should be included in the denominator.] NM82.

173. The contractor establishes and maintains a register of patients aged 18 years or over with CKD with classification of categories G3a to G5 (previously stage 3–5). NM83.

174. The percentage of patients on the CKD register who have hypertension and proteinuria and who are currently being treated with renin–angiotensin system antagonists. NM84.

175. The percentage of patients with CHD who have had influenza immunisation in the preceding 1 August to 31 March (Inherited). NM87.

176. The percentage of patients with CHD with a record in the preceding 12 months that aspirin, an alternative antiplatelet therapy, or an anticoagulant is being taken (Inherited). NM88.

177. In those patients with a current diagnosis of heart failure due to left ventricular systolic dysfunction, the percentage of patients who are currently treated with an ACE-I or ARB (Inherited). NM172.

178. In those patients with a current diagnosis of heart failure due to left ventricular systolic dysfunction who are currently treated with an ACE-I or ARB, the percentage of patients who are additionally currently treated with a beta-blocker licensed for heart failure (Inherited). NM173.

179. The percentage of patients with a stroke shown to be non-haemorrhagic, or a history of TIA, who have a record in the preceding 12 months that an antiplatelet agent or an anticoagulant is being taken (Inherited). NM94.

180. The percentage of patients with diabetes, on the register, with a diagnosis of nephropathy (clinical proteinuria) or micro-albuminuria who are currently treated with an ACE-I (or ARBs) (Inherited). NM95.

181. The percentage of patients with diabetes, on the register, in whom the last IFCC-HbA_1c is 64 mmol/mol or less in the preceding 12 months (Inherited). NM96.

182. The percentage of patients with diabetes, on the register, in whom the last IFCC-HbA_1c is 75 mmol/mol or less in the preceding 12 months (Inherited). NM97.

183. The percentage of patients with diabetes, on the register, who have a record of retinal screening in the preceding 12 months (Inherited). NM98.

184. The contractor establishes and maintains a register of patients with hypothyroidism who are currently treated with levothyroxine (Inherited). NM99.

185. The contractor establishes and maintains a register of patients with AF. AF001.

186. The contractor establishes and maintains a register of patients with asthma, excluding patients with asthma who have been prescribed no asthma-related drugs in the preceding 12 months. AST001.

187. The contractor establishes and maintains a register of all cancer patients defined as a ‘register of patients with a diagnosis of cancer excluding non-melanotic skin cancers diagnosed on or after 1 April 2003’. CAN001.

188. The percentage of patients aged 79 years or under, with CHD, in whom the last blood pressure reading (measured in the preceding 12 months) is 140/90 mmHg or less. CHD008.

189. The percentage of patients aged 80 years or over, with CHD, in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. CHD009.

190. The contractor establishes and maintains a register of patients with CHD. CHD01.

191. The contractor establishes and maintains a register of patients with COPD. COPD001.

192. The percentage of patients with COPD and MRC dyspnoea scale ≥ 3 at any time in the preceding 12 months, with a subsequent record of an offer of referral to a pulmonary rehabilitation programme. COPD008.

193. The proportion of women eligible for screening and aged 25–49 years at the end of reporting period whose notes record that an adequate cervical screening test has been performed in the preceding 3 years and 6 months. CS005.

194. The proportion of women eligible for screening and aged 50–64 years and the end of reporting period whose notes record that an adequate cervical screening test has been performed in the previous 5 years and 6 months. CS006.

195. In those patients with a new diagnosis of hypertension aged 30 or over and who have not attained the age of 75, recorded between the preceding 1 April to 31 March (excluding those with pre-existing CHD, diabetes, stroke and/or TIA), who have a recorded CVD risk assessment score (using an assessment tool agreed with NHS CB) of ≥ 20% in the preceding 12 months: the percentage who are currently treated with statins. CVD-PP001.

196. The contractor establishes and maintains a register of patients diagnosed with dementia. DEM001.

197. The percentage of patients with diabetes, on the register, without moderate or severe frailty, on the register, in whom the last blood pressure reading (measured in the preceding 12 months) is 140/80 mmHg or less. DM019.

198. The percentage of patients with diabetes, on the register, with moderate or severe frailty, on the register, in whom the last IFCC-HbA_1c is 75 mmol/mol or less in the preceding 12 months. DM021.

199. The percentage of patients with diabetes, on the register, aged 40 years and over, with no history of CVD and without moderate or severe frailty, who are currently treated with a statin. (excluding patients with type 2 diabetes and a CVD risk score of < 10% recorded in the preceding 3 years). DM022.

200. The percentage of patients with diabetes, on the register, and a history of CVD (excluding haemorrhagic stroke) who are currently treated with a statin. DM023.

201. The percentage of patients with diabetes, on the register, without moderate or severe frailty, on the register, in whom the last IFCC-HbA_1c is 58 mmol/mol or less in the preceding 12 months. NM157.

202. The contractor establishes and maintains a register of patients aged 18 or over receiving drug treatment for epilepsy. EP001.

203. The contractor establishes and maintains a register of patients with heart failure. HF001.

204. The contractor establishes and maintains a register of patients with established hypertension. HYP001.

205. The percentage of patients aged 79 years or under, with hypertension, in whom the last blood pressure reading (measured in the preceding 12 months) is 140/90 mmHg or less. HYP003.

206. The percentage of patients aged 80 years and over, with hypertension, in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. HYP007.

207. The contactor establishes and maintains a register of patients with schizophrenia, bipolar affective disorder and other psychoses and other patients on lithium therapy. MH001.

208. The percentage of patients with schizophrenia, bipolar affective disorder and other psychoses who have a record of BMI in the preceding 12 months. MH006

209. The contractor establishes and maintains a register of patients aged 18 years or over with a BMI ≥ 30 in the preceding 12 months. OB001.

210. The contractor establishes and maintains a register of all patients in need of palliative care/support irrespective of age. PC001.

211. The contractor can demonstrate continuous quality-improvement activity focused upon prescribing safety as specified in the QOF guidance. QI001.

212. The contractor has participated in network activity to regularly share and discuss learning from quality-improvement activity as specified in the QOF guidance. This would usually include participating in a minimum of two peer-review meetings. QI002.

213. The contractor can demonstrate continuous quality-improvement activity focused on end-of-life care as specified in the QOF guidance. QI003.

214. The contractor has participated in network activity to regularly share and discuss learning from quality-improvement activity as specified in the QOF guidance. This would usually include participating in a minimum of two network peer-review meetings. QI004.

215. The percentage of patients aged 80 years or over, with a history of stroke or TIA, in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. STAI011.

216. The contractor establishes and maintains a register of patients with stroke or TIA. STIA001.

217. The percentage of patients aged 79 years or under, with a history of stroke or TIA, in whom the last blood pressure reading (measured in the preceding 12 months) is 140/90 mmHg or less. STIA010.

218. The percentage of patients with CHD in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. CHD002.

219. The percentage of patients with CHD whose last measured cholesterol (measured in the preceding 12 months) is 5 mmol/l or less. CHD003.

220. The percentage of patients on the CKD register in whom the last blood pressure reading (measured in the preceding 12 months) is 140/85 mmHg or less. CKD002.

221. The percentage of patients on the CKD register whose notes have a record of a urine ACR (or PCR) test in the preceding 12 months. CKD004.

222. The contractor establishes and maintains a register of women aged 54 or under who have been prescribed any method of contraception at least once in the last year, or other clinically appropriate interval, for example last 5 years for an IUS. CON001.

223. The percentage of women, on the register, prescribed emergency hormonal contraception one or more times in the preceding 12 months by the contractor who have received information from the contractor about long-acting reversible contraception at the time or within 1 month of the prescription. CON003.

224. The percentage of patients with COPD with a record of FEV1 in the preceding 12 months. COPD004.

225. The percentage of patients with COPD and MRC dyspnoea grade ≥ 3 at any time in the preceding 12 months, with a record of oxygen saturation value within the preceding 12 months. COPD005.

226. The contractor has a protocol that is in line with national guidance agreed with the NHS CB for the management of cervical screening, which includes staff training, management of patient call/recall, exception reporting and the regular monitoring of inadequate sample rates. CS001.

227. The percentage of women aged 25 or over and who have not attained the age of 65 whose notes record that a cervical screening test has been performed in the preceding 5 years. CS002.

228. The contractor has a policy for auditing its cervical screening service and performs an audit of inadequate cervical screening tests in relation to individual sample-takers at least every 2 years. CS004.

229. The percentage of patients diagnosed with hypertension (diagnosed after or on 1 April 2009) who are given lifestyle advice in the preceding 12 months for: smoking cessation, safe alcohol consumption and healthy diet. CVD-PP002.

230. The percentage of patients with a new diagnosis of dementia recorded in the preceding 1 April to 31 March with a record of FBC, calcium, glucose, renal and liver function, thyroid function tests, serum vitamin B₁₂ and folate levels recorded between 12 months before or 6 months after entering on to the register. DEM005.

231. The percentage of patients with diabetes, on the register, whose last measured total cholesterol (measured within the preceding 12 months) is 5 mmol/l or less. DM004.

232. The percentage of patients with diabetes, on the register, who have a record of an ACR test in the preceding 12 months. DM005.

233. The percentage of patients with diabetes, on the register, in whom the last IFCC-HbA_1c is 59 mmol/mol or less in the preceding 12 months. DM007.

234. The percentage of patients with diabetes, on the register, in whom the last IFCC-HbA_1c is 64 mmol/mol or less in the preceding 12 months. DM008.

235. The percentage of patients with diabetes, on the register, in whom the last IFCC-HbA_1c is 75 mmol/mol or less in the preceding 12 months. DM009.

236. The percentage of patients with diabetes, on the register, who have a record of retinal screening in the preceding 12 months. DM011.

237. The percentage of patients 18 or over on drug treatment for epilepsy who have been seizure-free for the last 12 months recorded in the preceding 12 months. EP002.

238. The percentage of women aged 18 or over and who have not attained the age of 55 who are taking antiepileptic drugs who have a record of information and counselling about contraception, conception and pregnancy in the preceding 12 months. EP003.

239. The percentage of patients with hypertension in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. HYP006.

240. The percentage of patients on the learning disability register with Down syndrome aged 18 or over who have a record of blood TSH in the preceding 12 months. LD002.

241. The percentage of patients aged 40 or over with schizophrenia, bipolar affective disorder and other psychoses who have a record of total cholesterol-HDL ratio in the preceding 12 months. MH004.

242. The percentage of patients aged 40 or over with schizophrenia, bipolar affective disorder and other psychoses who have a record of blood glucose or HbA_1c in the preceding 12 months MH005.

243. The percentage of patients with schizophrenia, bipolar affective disorder and other psychoses who have a record of alcohol consumption in the preceding 12 months. MH007.

244. The percentage of women aged 25 or over and who have not attained the age of 65 with schizophrenia, bipolar affective disorder and other psychoses whose notes record that a cervical screening test has been performed in the preceding 5 years. MH008.

245. The percentage of women aged 25 or over and who have not attained the age of 65 with schizophrenia, bipolar affective disorder and other psychoses whose notes record that a cervical screening test has been performed in the preceding 5 years. MH008.

246. The percentage of patients on lithium therapy with a record of serum creatinine and TSH in the preceding 9 months. MH009.

247. The percentage of patients on lithium therapy with lithium levels in the therapeutic range in the preceding 4 months. MH010.

248. The percentage of patients on the CKD register with hypertension and proteinuria who are currently treated with renin–angiotensin system antagonists. NM84.

249. The percentage of patients aged 50 or over, and who have not attained the age of 75, with a fragility fracture on or after 1 April 2012, in whom osteoporosis is confirmed on DEXA scan, who are currently treated with an appropriate bone-sparing agent. OST002.

250. The percentage of patients aged 75 or over with a record of a fragility fracture on or after 1 April 2014 and a diagnosis of osteoporosis, who are currently treated with a bone-sparing agent. OST005.

251. The percentage of patients with peripheral arterial disease in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. PAD002.

252. The percentage of patients with peripheral arterial disease in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. PAD002.

253. The percentage of patients with peripheral arterial disease in whom the last measured total cholesterol (measured in the preceding 12 months) is 5 mmol/l or less. PAD003.

254. The percentage of patients with peripheral arterial disease with a record in the preceding 12 months that aspirin or an alternative antiplatelet is being taken. PAD004.

255. The contractor has regular (at least 3 monthly) multidisciplinary case-review meetings where all patients on the palliative care register are discussed. PC002.

256. The percentage of patients with rheumatoid arthritis aged 30 or over and who have not attained the age of 85 who have had a cardiovascular risk assessment using a CVD risk-assessment tool adjusted for RA in the preceding 12 months. RA003.

257. The percentage of patients aged 50 or over and who have not attained the age of 91 with rheumatoid arthritis who have had an assessment of fracture risk using a risk-assessment tool adjusted for RA in the preceding 24 months. RA004.

258. The percentage of patients aged 15 or over whose notes record smoking status in the preceding 24 months. SMOK001.

259. The contractor supports patients who smoke in stopping smoking by a strategy which includes providing literature and offering appropriate therapy. SMOK003.

260. The percentage of patients with a stroke shown to be non-haemorrhagic or a history of TIA whose last measured total cholesterol (measured in the preceding 12 months) is 5 mmol/l or less. STAI005.

261. The percentage of patients with a history of a stroke or TIA in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. STIA003.

262. The percentage of patients with a stroke or TIA (diagnosed on or after 1 April 2014) who have a record of a referral for further investigation between 3 months before and 1 month after the date of the latest recorded or stroke or the first TIA. STIA008.

263. The contractor establishes and maintains a register of patients with hypothyroidism who are currently treated with levothyroxine. THY001.

264. The percentage of patients with hypothyroidism, on the register, with thyroid function tests recorded in the preceding 12 months. THY002.

265. In those patients with AF whose latest record of a CHADS2 score is >1, the percentage of patients who are currently treated with anticoagulation therapy. AF004.

266. In those patients with AF in whom there is record of a CHADS2 score of 1 the percentage of patients who are currently treated with anticoagulation drug therapy or antiplatelet therapy. AF005.

267. The percentage of patients with a history of MI (on or after 1 April 2011) currently treated with an ACE-I (or ARB if ACE-I-intolerant), aspirin or an alternative antiplatelet therapy, beta-blocker and statin. CHD006.

268. The percentage of patients on the CKD register with hypertension and proteinuria who are currently treated with an ACE-I or ARB. CKD003.

269. The percentage of patients with diabetes, on the register, in whom the last blood pressure reading (measured in the preceding 12 months) is 150/90 mmHg or less. NM01.

270. The percentage of patients with diabetes, on the register, in whom the last blood pressure reading (measured in the preceding 12 months) is 140/80 mmHg or less. NM02.

271. The percentage of women under the age of 55 years who are taking antiepileptic drugs who have a record of information and counselling about contraception, conception and pregnancy in the preceding 15 months. NM03.

272. Percentage of patients on the Learning Disability register with Down syndrome aged 18 and over who have a record of blood TSH in the previous 15 months (excluding those who are on the thyroid disease register). NM04.

273. The percentage of patients with a new diagnosis of dementia recorded in the preceding 1 April to 31 March with a record of FBC, calcium, glucose, renal and liver function, thyroid function tests, serum vitamin B₁₂ and folate levels recorded between 6 months before and after entering on to the register NM09.

274. The percentage of patients with hypothyroidism, on the register, with thyroid function tests recorded in the preceding 12 months (Inherited). NM100.

275. The percentage of patients aged 8 or over with asthma (diagnosed on or after 1 April 2006), on the register, with measures of variability or reversibility recorded between 3 months before and any time after diagnosis (Inherited). NM101.

276. The percentage of patients with asthma aged 14 or over and who have not attained the age of 20, on the register, in whom there is a record of smoking status in the preceding 12 months (Inherited). NM102.

277. The percentage of patients with COPD (diagnosed on or after 1 April 2011) in whom the diagnosis has been confirmed by post bronchodilator spirometry between 3 months before and 12 months after entering on to the register (Inherited). NM103.

278. The percentage of patients with COPD who have had a review, undertaken by a healthcare professional, including an assessment of breathlessness using the MRC dyspnoea scale in the preceding 12 months (Inherited). NM104.

279. The percentage of patients with COPD with a record of FEV1 in the preceding 12 months (Inherited). NM105.

280. The percentage of patients with COPD who have had influenza immunisation in the preceding 1 August to 31 March (Inherited). NM106.

281. The percentage of patients diagnosed with dementia whose care plan has been reviewed in a face-to-face review in the preceding 12 months (Inherited). NM107.

282. The percentage of patients with schizophrenia, bipolar affective disorder and other psychoses who have a comprehensive care plan documented in the record, in the preceding 12 months, agreed between individuals, their family and/or carers as appropriate (Inherited). NM108.

283. The percentage of patients on the CKD register whose notes have a record of a urine ACR (or protein–creatinine ratio) test in the preceding 12 months (Inherited). NM109.

284. The percentage of patients aged 18 or over on drug treatment for epilepsy who have been seizure-free for the last 12 months recorded in the preceding 12 months (Inherited). NM110.

285. The contractor supports patients who smoke in stopping smoking by a strategy which includes providing literature and offering appropriate therapy (Inherited). NM113.

286. The percentage of women, on the register, prescribed an oral or patch contraceptive method in the preceding 12 months who have also received information from the contractor about long-acting reversible methods of contraception in the preceding 12 months (Inherited). NM114.

287. The percentage of patients on the CKD register in whom the last blood pressure reading (measured in the preceding 12 months) is 140/90 mmHg or less (Inherited). NM117.

288. The percentage of patients with CHD whose last measured total cholesterol (measured in the preceding 12 months) is 5 mmol/l or less. (Inherited). NM118.

289. The percentage of patients with schizophrenia, bipolar affective disorder and other psychoses aged 25–84 (excluding those with pre-existing CHD, diabetes, stroke and/or TIA) who have had a CVD risk assessment performed in the preceding 12 months (using an assessment tool agreed with NHS England). NM120.

290. The percentage of patients with CHD, stroke or TIA, diabetes, hypertension, peripheral arterial disease, heart failure, COPD, asthma and/or rheumatoid arthritis who have had a BMI recorded in the preceding 12 months. NM121.

291. The percentage of patients with CHD, stroke or transient ischaemic attack, diabetes and/or COPD who have influenza immunisation in the preceding 1 August and 31 March. NM122.

292. The percentage of patients with a new diagnosis of depression and/or anxiety disorder in the preceding 1 April to 31 March, whose notes record an offer of referral for psychological treatment within 3 months of the date of diagnosis (Inherited). NM123.

293. The percentage of patients with schizophrenia, bipolar affective disorder or other psychoses whose notes record smoking status in the preceding 12 months. NM124.

294. The percentage of patients with schizophrenia, bipolar affective disorder or other psychoses who are recorded as current smokers who have a record of an offer of support and treatment within the preceding 12 months. NM125.

295. The percentage of patients with any or any combination of the following conditions: CHD, PAD, stroke or TIA, hypertension, diabetes, COPD, CKD or asthma, whose notes record smoking status in the preceding 12 months. NM126.

296. The percentage of patients with any or any combination of the following conditions: CHD, PAD, stroke or TIA, hypertension, diabetes, COPD, CKD, asthma who are recorded as current smokers who have a record of an offer of support and treatment within the preceding 12 months. NM127.

297. The contractor establishes and maintains a register of patients aged 18 or over with a BMI ≥ 25 in the preceding 12 months. NM128.

298. The percentage of patients aged 18 and over with schizophrenia, bipolar affective disorder and other psychoses who have a record of total cholesterol–HDL ratio in the preceding 12 months. NM129.

299. The percentage of patients with diabetes with a record of a foot examination and risk classification: (1) low risk (normal sensation, palpable pulses), (2) increased risk (neuropathy or absent pulses), (3) high risk (neuropathy or absent pulses plus deformity or skin changes or previous ulcer) or (4) ulcerated foot within the preceding 15 months. NM13.

300. The percentage of patients aged 18 years and over with schizophrenia, bipolar affective disorder and other psychoses who have a record of blood glucose or HbA_1c in the preceding 12 months. NM130.

301. The percentage of patients with diabetes with a record of testing of foot sensation using a 10-g monofilament within the preceding 12 months. NM131.

302. The percentage of patients aged 25–84, years with a new diagnosis of hypertension or type 2 diabetes, recorded between the preceding 1 April and 31 March (excluding those with pre-existing CHD, stroke and/or TIA) who have had a consultation for cardiovascular risk assessment using the QRISK2 risk-assessment tool between 3 months before and 3 months after date of diagnosis (Inherited). NM132.

303. In those patients with a new diagnosis of hypertension or type 2 diabetes aged 25–84 years, recorded between the preceding 1 April and 31 March (excluding those with pre-existing CHD, stroke and/or TIA), who have a recorded CVD risk-assessment score (using the QRISK2 assessment tool) of > 20% in the preceding 12 months: the percentage who are currently treated with statins (unless there is a contraindication). NM133.

304. The percentage of patients with diabetes, on the register, who have had influenza immunisation in the preceding 1 August to 31 March (Inherited). NM139.

305. The percentage of patients with stroke or TIA who have had influenza immunisation in the preceding 1 August to 31 March (Inherited). NM140.

306. The percentage of patients with schizophrenia, bipolar affective disorder and other psychoses who have a record of alcohol consumption in the preceding 15 months. NM15.

307. The percentage of patients with a diagnosis of heart failure (diagnosed on or after 1 April 2006) which has been confirmed by an echocardiogram or by specialist assessment 3 months before or 12 months after entering on to the register (Inherited). NM16.

308. The percentage of patients with schizophrenia, bipolar affective disorder and other psychoses who have a record of BMI in the preceding 15 months. NM16.

309. The percentage of patients with schizophrenia, bipolar affective disorder and other psychoses who have a record of blood pressure in the preceding 15 months. NM17.

310. The percentage of patients with asthma, on the register, who have had an asthma review in the preceding 12 months that includes an assessment of asthma control using the three RCP questions. NM23.

311. The percentage of patients newly diagnosed with diabetes, on the register, in the preceding 1 April to 31 March who have a record of being referred to a structured education programme within 9 months after entry on to the diabetes register. NM27.

312. The percentage of patients with diabetes who have a record of a dietary review by a suitably competent professional in the preceding 15 months. NM28.

313. The contractor establishes and maintains a register of patients: (1) aged 50 or over and who have not attained the age of 75 with a record of a fragility fracture on or after 1 April 2012 and a diagnosis of osteoporosis confirmed on DEXA scan, and (2) aged 75 or over with a record of a fragility fracture on or after 1 April 2014 and a diagnosis of osteoporosis. NM29.

314. The contractor establishes and maintains a register of patients with peripheral arterial disease. NM32.

315. The percentage of patients with peripheral arterial disease with a record in the preceding 15 months that aspirin or an alternative antiplatelet is being taken. NM33.

316. The percentage of patients with peripheral arterial disease in whom the last measured total cholesterol (measured in preceding 15 months) is 5.0 mmol/l or less. NM35.

317. The percentage of patients with hypertension aged 16 to 74 years in whom there is an annual assessment of physical activity, using GPPAQ, in the preceding 15 months. NM36.

318. The percentage of patients with hypertension aged 16–74 years who score ‘less than active’ on GPPAQ in the preceding 15 months, who also have a record of a brief intervention in the preceding 15 months. NM37.

319. The percentage of patients with any or any combination of the following conditions: CHD, PAD, stroke or TIA, hypertension, diabetes, COPD, CKD, asthma, schizophrenia, bipolar affective disorder or other psychoses who are recorded as current smokers who have a record of an offer of support and treatment within the preceding 12 months. NM38.

320. The percentage of patients with any or any combination of the following conditions: CHD, PAD, stroke or TIA, hypertension, diabetes, COPD, CKD, asthma, schizophrenia, bipolar affective disorder or other psychoses who smoke whose notes contain a record of an offer of support and treatment within the preceding 15 months. NM39.

321. The percentage of patients aged 15 years and over who are recorded as current smokers who have a record of an offer of support and treatment within the preceding 24 months. NM40.

322. The contractor establishes and maintains a register of all patients aged 17 or over with diabetes mellitus which specifies the type of diabetes where a diagnosis has been confirmed. NM41.

323. The percentage of patients with COPD and MRC Dyspnoea Scale ≥ 3 at any time in the preceding 15 months, with a subsequent record of an offer of referral to a pulmonary rehabilitation programme. NM47.

324. The percentage of patients with heart failure diagnosed within the preceding 15 months with a subsequent record of an offer of referral for an exercise-based rehabilitation programme within the preceding 15 months. NM48.

325. The percentage of patients with a new diagnosis of depression in the preceding 1 April to 31 March who have had a bio-psychosocial assessment by the point of diagnosis. NM49.

326. The percentage of patients with a new diagnosis of depression in the preceding 1 April to 31 March who have been reviewed within 10–35 days of the date of diagnosis. NM50.

327. The percentage of male patients with diabetes with a record of being asked about erectile dysfunction in the preceding 15 months. NM51.

328. The percentage of male patients with diabetes who have a record of erectile dysfunction with a record of advice and assessment of contributory factors and treatment options in the preceding 15 months. NM52.

329. The percentage of patients under 80 years old with hypertension in whom the last recorded blood pressure (measured in the preceding 9 months) is 140/90 or less. NM53.

330. The percentage of patients aged 80 years and over with hypertension in whom the last recorded blood pressure (measured in the preceding 9 months) is 150/90 or less. NM54.

331. The practice can produce a register of all patients aged 16 years and over with rheumatoid arthritis. NM55.

332. The percentage of patients with rheumatoid arthritis aged 30–84 years who have had a cardiovascular risk assessment using a CVD risk-assessment tool adjusted for RA in the preceding 15 months. NM56.

333. The percentage of patients aged 50–90 years with rheumatoid arthritis who have had an assessment of fracture risk using a risk-assessment tool adjusted for RA in the preceding 27 months. NM57.

334. The percentage of patients with rheumatoid arthritis, on the register, who have had a face-to-face review in the preceding 12 months. NM58.

335. The percentage of patients with diabetes who have a record of an ACR test in the preceding 15 months. NM59.

336. The percentage of patients with a stroke shown to be non-haemorrhagic or a history of TIA whose last measured total cholesterol (measured in the preceding 15 months) is 5 mmol/l or less. NM60.

337. The percentage of patients aged 40 years and over with a blood pressure measurement recorded in the preceding 5 years. NM61.

338. The percentage of patients with cancer diagnosed within the preceding 15 months who have a review recorded as occurring within 3 months of the practice receiving confirmation of the diagnosis. NM61.

339. The percentage of patients with dementia with the contact details of a named carer on their record. NM64.

340. The percentage of patients with dementia (diagnosed on or after 1 April 2014) who have a record of attendance at a memory-assessment service up to 12 months before entering on to the register. NM65.

341. The percentage of patients with a new diagnosis of hypertension (diagnosed on or after 1 April 2014) which has been confirmed by ABPM or HBPM in the 3 months before entering on to the register. NM66.

342. The percentage of patients aged 79 or under with peripheral arterial disease in whom the last blood pressure reading (measured in the preceding 12 months) is 140/90 mmHg or less. NM67.

343. The percentage of patients aged 79 or under with CHD in whom the last blood pressure reading (measured in the preceding 12 months) is 140/90 mmHg or less. NM68.

344. The percentage of patients aged 79 or under with stroke or TIA in whom the last blood pressure reading (measured in the preceding 12 months) is 140/90 mmHg or less. NM69.

345. The percentage of women with diabetes aged 17 or over and who have not attained the age of 45 who have a record of being given information and advice about pregnancy or conception or contraception tailored to their pregnancy and contraceptive intentions recorded in the preceding 12 months. NM70.

346. The percentage of women with epilepsy aged 18 or over and who have not attained the age of 45 who are taking antiepileptic drugs who have a record of being given information and advice about pregnancy or conception or contraception tailored to their pregnancy and contraceptive intentions recorded in the preceding 12 months. NM71.

347. The contractor establishes and maintains a register of patients with learning disabilities. NM73.

348. The percentage of patients with diabetes who have had the following care processes performed in the preceding 12 months: BMI measurement; BP measurement; HbA_1c measurement; cholesterol measurement; record of smoking status; foot examination; albumin–creatinine ratio; serum creatinine measurement. NM74.

349. The percentage of patients with a new diagnosis of hypertension in the preceding 1 April to 31 March who have a record of urinary albumin–creatinine ratio test in the 3 months before or after the date of entry to the hypertension register. NM75.

350. The percentage of patients with a new diagnosis of hypertension in the preceding 1 April to 31 March who have a record of a test for haematuria in the 3 months before or after the date of entry to the hypertension register. NM76.

351. The percentage of patients with a new diagnosis of hypertension in the preceding 1 April to 31 March who have a record of a 12-lead ECG performed in the 3 months before or after the date of entry to the hypertension register. NM77.

352. The percentage of women with schizophrenia, bipolar affective disorder or other psychoses under the age of 45 years who have been given information and advice about pregnancy, conception or contraception tailored to their pregnancy and contraceptive intentions recorded in the preceding 12 months. NM78.

353. The percentage of patients who had a MI in the preceding 1 April to 31 March and who are currently being treated with ACE-I (or ARB if ACE-I-intolerant), dual antiplatelet therapy, beta-blocker and a statin. NM79.

354. The percentage of patients with a history of MI (more than 12 months ago) who are currently being treated with an ACE-I (or ARB if ACE-I-intolerant), aspirin (or clopidogrel) (or anticoagulant drug therapy) and a statin and a beta-blocker for those patients with left ventricular systolic dysfunction. NM80.

355. The percentage of patients with AF in whom stroke risk has been assessed using the CHA2DS2-VASc score risk stratification scoring system in the preceding 12 months (excluding those patients with a previous CHADS2 or CHA2DS2-VASc score of 2 or more). NM81.

356. In those patients with AF with a record of a CHA2DS2-VASc score of 2 or more, the percentage of patients who are currently treated with anticoagulation drug therapy. [Patients with a previous score of 2 or above using CHADS2 recorded prior to (implementation date) should be included in the denominator.] NM82.

357. The contractor establishes and maintains a register of patients aged 18 years or over with CKD with classification of categories G3a to G5 (previously stage 3–5). NM83.

358. The percentage of patients on the CKD register who have hypertension and proteinuria and who are currently being treated with renin–angiotensin system antagonists. NM84.

359. The percentage of patients with CHD who have had influenza immunisation in the preceding 1 August to 31 March (Inherited). NM87.

360. The percentage of patients with CHD with a record in the preceding 12 months that aspirin, an alternative antiplatelet therapy, or an anticoagulant is being taken (Inherited). NM88.

361. In those patients with a current diagnosis of heart failure due to left ventricular systolic dysfunction, the percentage of patients who are currently treated with an ACE-I or ARB (Inherited). NM172.

362. In those patients with a current diagnosis of heart failure due to left ventricular systolic dysfunction who are currently treated with an ACE-I or ARB, the percentage of patients who are additionally currently treated with a beta-blocker licensed for heart failure (Inherited). NM173.

363. The percentage of patients with a stroke shown to be non-haemorrhagic or a history of TIA who have a record in the preceding 12 months that an antiplatelet agent or an anticoagulant is being taken (Inherited). NM94.

364. The percentage of patients with diabetes, on the register, with a diagnosis of nephropathy (clinical proteinuria) or micro-albuminuria who are currently treated with an ACE-I (or ARBs) (Inherited). NM95.

365. The percentage of patients with diabetes, on the register, in whom the last IFCC-HbA_1c is 64 mmol/mol or less in the preceding 12 months (Inherited). NM96.

366. The percentage of patients with diabetes, on the register, in whom the last IFCC-HbA_1c is 75 mmol/mol or less in the preceding 12 months (Inherited). NM97.

367. The percentage of patients with diabetes, on the register, who have a record of retinal screening in the preceding 12 months (Inherited). NM98.

368. The contractor establishes and maintains a register of patients with hypothyroidism who are currently treated with levothyroxine (Inherited). NM99.

Primary care quality indicators for people with serious mental illness29

1. Co-ordinated care – identify key worker (social worker or community psychiatric nurse) – Routine data.

2. Staff continuity – good communication between staff and infrequent staff changes – Routine data.

3. Continuity: CONNECT is a patient questionnaire with 72 items, each rated on a five-point scale, with 13 scales and one single-item indicator: General co-ordination – ‘Overall, is your MH treatment well co-ordinated?’ Primary care scales – ‘How often is psychiatrist in contact with your primary care doctor?’ (Never, Rarely, Sometimes, Often, Always) – Primary data.

4. Total number of follow-up contacts during treatment episode after initial evaluation – Routine data.

5. Patients with SMI who smoke who are offered tobacco counselling/help to stop smoking – Routine data.

6. Alcohol-misuse screening – Routine data.

7. Screening for illicit drug use, type, quantity and frequency – Routine data.

8. Referral to substance-misuse disorder specialty care, if appropriate – Routine data.

9. HIV screening with co-occurring substance misuse for SMI service users – Routine data.

10. Practice can produce register of all SMI patients – Routine data.

11. Service user registration with a primary health organisation – Routine data.

12. Service user registration with markers of care recorded: contact with secondary health services, written care plans, 6-month MH review, identified care co-ordinator, evidence of physical examination – Routine data.

13. Patients who do not attend the practice for their annual review who are identified and followed up by the practice team – Routine data.

14. System contact: number of patients in contact with the treatment system – Routine data.

15. Surveillance to prevent relapse – Routine data.

16. Crisis management and out-of-hours services – Routine data.

17. Access to services and range of services – Routine data.

18. Family care – record of families living with person with schizophrenia – Primary data.

19. Duration of untreated psychosis: number of recently diagnosed patients – Routine data.

20. Waiting time between registration and start of treatment – Routine data.

21. All current medication clearly available at all consultations – known drug dosages, frequencies, history of side effects, review date – Primary data.

22. Monitor patients suffering extrapyramidal effects, check compliance – Routine data.

23. Assess weight gain, use of concomitant medication – Routine data.

24. Use of lithium: plasma lithium levels monitored regularly – Routine data.

25. Percentages of bipolar service users prescribed antidepressants and anxiolytics – Routine data.

26. Proportion of patients who are receiving depot antipsychotics who have appropriate laboratory screening tests – Routine data.

27. Patients have their antipsychotic medication reviewed regularly, considering symptoms and side effects: appropriate referral to specialist – Routine data.

28. Polypharmacy: reduce number of patients using more than four psychotropic drugs at the same time – Routine data.

29. Monitoring patients with neurological, sexual, sleeping and sedation side effects – Routine data.

30. Percentage of patients given annual MH review by GP – Routine data.

31. Comprehensive mental status examination and history conducted in patients with a new treatment episode – Routine data.

32. Referral for specialist MH assessment – Routine data.

33. Comprehensive assessment of comorbid psychiatric conditions and response to treatment – Routine data.

34. Reassess severity of symptoms – Routine data.

35. Examined for duration of untreated psychosis – Primary data.

36. Delayed diagnosis – Primary data.

37. Informal carer contacts – Primary data.

38. Information on employment status – Primary data.

39. Diabetes monitoring for people with diabetes and schizophrenia – Routine data.

40. Diabetes and cholesterol monitoring for people with schizophrenia and diabetes – Routine data.

41. Diabetes screening for people who are using antipsychotic medications – Routine data.

42. Blood pressure screening for patients with diabetes – Routine data.

43. Weight management/BMI monitoring – Routine data.

44. Proportion with increased BMI/abdominal waistline – Routine data.

45. Patients with diabetes who received education about diabetes, nutrition, cooking, physical activity, or exercise – Routine data.

46. Counselling on physical activity and/or nutrition for those with documented elevated BMI – Routine data.

47. Retinal exam for patients with SMI who have diabetes – Routine data.

48. Foot exam for patients with SMI who have diabetes – Routine data.

49. Hypertension counselling: patients with hypertension who received education services related to hypertension, nutrition, cooking, physical activity or exercise – Routine data.

50. Hypertension: recording and monitoring patients with hypertension and high blood cholesterol [low-density lipoprotein (LDL)] – Routine data.

51. Breast cancer screening for women – Routine data.

52. Colorectal cancer screening – Routine data.

53. Proportion of patients who have an increased blood pressure – Routine data.

54. Proportion of patients who have an increased blood glucose level – Routine data.

55. Proportion of patients who have low levels of glycosylated haemoglobin – Routine data.

56. Proportion of patients who have increased level of blood lipids – Routine data.

57. Comprehensive physical health assessment with appropriate advice – Routine data.

58. Patients with diabetes who received psychoeducation related to weight (BMI), diabetes (blood glucose levels) – Routine data.

59. Medical attention for nephropathy – Routine data.

High-impact quality indicators in general practice53

1. Diabetes: composite indicator recording the proportion of eligible patients receiving all nine recommended processes of care:

   • blood pressure measurement;

   • HbA_1c measurement;

   • cholesterol measurement;

   • urine ACR/PCR testing or proteinuria code;

   • estimated glomerular filtration rate (eGFR) or serum creatinine testing;

   • foot review;

   • retinal screening;

   • BMI recording;

   • smoking status.

2. Set of 9 indicators focusing on avoiding adverse effects of non-steroidal antiinflammatory drugs (NSAIDs) and antiplatelet drugs:

   • Prescribing a traditional oral NSAID or low-dose aspirin in patients with a history of peptic ulceration without co-prescription of gastroprotection.

   • Prescribing a traditional oral NSAID in patients aged 75 years or over without co-prescription of gastroprotection.

   • Prescribing of a traditional oral NSAID and aspirin in patients aged 65 years or over without co-prescription of gastroprotection.

   • Prescribing of aspirin and clopidogrel in patients aged 65 years or over without co-prescription of gastroprotection.

   • Prescribing of warfarin and a traditional oral NSAID without co-prescription of gastroprotection.

   • Prescribing of warfarin and low dose aspirin or clopidogrel without co-prescription of gastroprotection.

   • Prescribing an oral NSAID in patients with heart failure.

   • Prescribing an oral NSAID in patients prescribed both a diuretic and an angiotensin-converting-enzyme inhibitor (ACE inhibitor) or ARB.

   • Prescribing an oral NSAID in patients with CKD.

3. The proportion of patients with a record of AF and a score of two or higher on the CHADS2 risk tool who have a current prescription for anticoagulation therapy.

4. The proportion of patients with a lifetime record of MI who are receiving the recommended four drugs: ACE inhibitor or ARB, aspirin or antiplatelet, beta-blocker and statin.

5. The proportion of patients with type 2 diabetes that achieve each of the three recommended target levels: BP < 140/80 mmHg (or < 130/80 mmHg if kidney, eye or cerebrovascular damage), HbA_1c ≤ 59 mmol/mol, and cholesterol ≤ 5 mmol/l.

6. Blood pressure control in hypertension: the proportion of patients achieving individual, age-dependent targets in the previous 9 month: BP < 140/90 mmHg if aged under 80 years, or < 150/90 mmHg if aged 80 years or more.

7. Blood pressure control in CKD: a combination of two indicators assessing the achievement of recommended BP targets in specific patient groups: < 140/85 mmHg, or < 130/80 mmHg if record of diabetes or proteinuria.

High-impact guideline-based quality indicators for United Kingdom primary care52

1. Smoking: the percentage of patients in high-risk groups whose notes record smoking status and the offer of support and treatment within preceding 15 months (composite).

2. COPD: diagnosis of COPD, through use of spirometry and chest radiograph (composite).

3. CKD: the percentage of patients on the CKD register with hypertension and proteinuria who are treated with an ACE-I or ARB.

4. CKD: measurement of blood pressure, urinary protein excretion and lifestyle advice (composite).

5. CKD: blood pressure and urinary protein excretion targets, and appropriate drug therapy (composite).

6. MI: all patients who have had an acute MI should be offered specific combination drug treatment.

7. Chronic heart failure: measurement of serum natriuretic peptides and referral where appropriate (composite).

8. AF: recommendations concerning use of anticoagulants in AF (composite).

9. Hypertension: blood pressure targets in those under/over 80 years of age (composite).

10. Hypertension: lifestyle advice and monitoring of cholesterol and urinary protein excretion (composite).

11. Type 2 diabetes: nine annual processes of care: that is, measurement of blood pressure, lipids, renal function, urine ACR, glycaemic control, BMI, smoking status, plus foot and eye checks (composite).

12. Type 2 diabetes: integrate dietary advice with a personalised diabetes management plan.

13. Type 2 diabetes: cardiovascular risk assessment and subsequent statin therapy where indicated.

14. Type 2 diabetes: achievement of target levels for blood pressure, cholesterol and glycaemic control (composite).

15. Type 2 diabetes: for a person on dual therapy who is markedly hyperglycaemic, consider starting insulin therapy in preference to adding other drugs to control blood glucose.

16. Diabetes mellitus: the percentage of patients with diabetes in whom the last blood pressure is ≤140/80 mmHg.

17. NSAIDs: use of NSAIDs and monitoring of potential side effects (composite).

18. Depression in adults: recommendations concerning severity-appropriate treatment of depression (composite).

Guidelines for the physical health of people in prison48

1. At first reception into prison, a healthcare professional (or trained healthcare assistant under the supervision of a registered nurse) should carry out a health assessment for every person. Do this before the person is allocated to their cell. As part of the assessment, identify any issues that may affect the person’s immediate health and safety before the second-stage health assessment priority health needs to be addressed at the next clinical opportunity.

2. Ensure continuity of care for people transferring from one custodial setting to another (including court, the receiving prison or during escort periods) by, for example: accessing relevant information from the patient clinical record, prisoner escort record and cell-sharing risk assessment, checking medicines and any outstanding medical appointments.

3. Take into account any communication needs or difficulties the person has (including reading and writing ability), and follow the principles in NICE’s guideline on patient experience in adult NHS services.

4. The first-stage health assessment should include the questions and actions in table 1. It should cover: physical health, alcohol use, substance misuse, MH, self-harm and suicide risk.

5. Give the person advice about how to contact prison health services and book GP appointments in the future.

6. Ask the person for consent to transfer their medical records from their GP to the prison healthcare service (see recommendations 1.7.1 and 1.7.2 for more information about transfer of medical records).

7. Enter in the person’s medical record: all answers to the reception health assessment questions; health-related observations, including those about behaviour and mental state (including eye contact, body language, rapid, slow or strange speech, poor hygiene, strange thoughts); details of any action taken.

8. Carry out a MR (in line with NICE’s guideline on medicines optimisation) before the second-stage health assessment. See also recommendations 1.4.1 and 1.7.10 for recommendations on risk assessments for IP medicines and ensuring continuity of medicine.

9. Healthcare professionals in prisons should ensure people coming into prison are screened for TB within 48 hours of arrival.

10. Report all suspected and confirmed TB cases to the local multidisciplinary TB team within 1 working day.

11. If a case of TB is confirmed: arrange for the local multidisciplinary TB team to visit within 5 working days. Contact the local PHE unit and multidisciplinary TB team to arrange a contact investigations exercise. They should also consider using mobile X-ray to check for further cases.

12. Put contingency, liaison and handover plans in place to ensure continuity of care before a person being treated for TB is transferred between prisons or released. Any other agencies working with the person should also be involved in this planning.

13. A healthcare professional (e.g. a registered general nurse) should carry out a second-stage health assessment for every person in prison. Do this within 7 days of the first-stage health assessment, and include as a minimum:

    • reviewing the actions and outcomes from the first-stage health assessment;

    • asking the person about any previous misuse of alcohol, use of drugs or improper use of prescription medicine; if they have ever suffered a head injury or lost consciousness, and, if so: how many times this has happened, whether they have ever been unconscious for more than 20 minutes, whether they have any problems with their memory or concentration; smoking history; the date of their last sexual health screen; any history of serious illness in their family (e.g. heart disease, diabetes, epilepsy, cancer or CCs); their expected release date, and if < 1 month plan a pre-release health assessment: see recommendation 1.7.5; whether they have ever had a screening test (e.g. a cervical screening test or mammogram); whether they have, or have had, any gynaecological problems;

    • measuring and recording the person’s height, weight, pulse, blood pressure and temperature, and carrying out a urinalysis.

14. Review the person’s first- and second-stage health-assessment records, medical history, GP and vaccination records and refer the person to the GP or a relevant clinic if further assessment is needed. See, for example, NICE’s guidelines on CVD (recommendations on identifying people for full formal risk assessment) or type 2 diabetes (the recommendation on risk assessment). Arrange a follow-up appointment if needed.

15. Consider using the Correctional Mental Health Screen for Men (CMHS-M) or Women (CMHS-W) to identify possible MH problems if: the person’s history, presentation or behaviour suggests they may have a MH problem; the person’s responses to the first-stage health assessment suggest they may have a MH problem; the person has a chronic physical health problem with associated functional impairment; concerns have been raised by other agencies about the person’s abilities to participate in the criminal justice process.

16. When using the CMHS-M or CMHS-W with a transgender person, use the measure that is in line with their preferred gender identity.

17. If there is other evidence supporting the likelihood of MH problems, or a man scores 6 or more on the CMHS-M, or a woman scores 4 or more on the CMHS-W: a practitioner who is trained to perform an assessment of MH problems should conduct further assessment or a practitioner who is not trained to perform an assessment of MH problems should refer the person to an appropriately trained professional for further assessment.

18. Offer people tailored health advice based on their responses to the assessment questions. This should be in a variety of formats (including face-to-face). It should include advice on: alcohol (see NICE’s guideline on alcohol-use disorders), substance misuse (see NICE’s guideline on drug misuse in over 16s), exercise (see recommendations 1.3.3 and 1.3.4), diet (see recommendation 1.3.5), stopping smoking (see recommendation 1.3.6), sexual health (see recommendations 1.3.7 and 1.3.8).

19. Offer the person advice, with supporting literature if appropriate, on: how to contact prison health services and book GP appointments or other clinics, for example, dental, optician, chiropodist, substance-misuse and recovery services; where to find health information that is accessible and understandable; how to attend or get a referral to attend any health-promoting activities in the future (see recommendations 1.3.1–1.3.8); medicines adherence (see recommendation 1.4.7).

20. Enter in the person’s medical record: all answers to the second-stage health assessment questions; health-related observations; details of any action taken.

21. Plan a follow-up healthcare review at a suitable time based on clinical judgement, taking into account the age of the person and length of their sentence. For people who may be in prison for < 1 month, see recommendation 1.7.5.

22. Hepatitis B and C – the recommendations in this section have been adapted from the NICE guideline on hepatitis B. Prison healthcare services (working with the NHS lead for hepatitis) should ensure that: all people are offered a hepatitis B vaccination when entering prison (for the vaccination schedule, refer to the Green Book); all people are offered access to confidential testing for hepatitis B and C when entering prison and during their detention; people who test for hepatitis B or C receive the results of the test, regardless of their location, when they become available; results from hepatitis B and C testing are provided to the person’s community-based GP, if consent is given.

23. HIV – the recommendations in this section have been adapted from the NICE guideline on HIV testing.

    1. - Offer all people HIV testing when entering prison.

    2. - Primary care providers should ensure annual HIV testing is part of the integrated health care offered to men who are known to have sex with men.

    3. - Provide information on HIV testing and discuss why it is recommended (including to those who indicate that they may wish to decline the test).

    4. - Conduct post-test discussions, including giving positive test results and delivering post-test and general health-promotion interventions.

    5. - Recognise illnesses that may signify primary HIV infection and clinical indicator diseases that often coexist with HIV.

24. STIs – identify people at high risk of STIs using their sexual history. Opportunities for risk assessment may arise during consultations on contraception, pregnancy or abortion, and when carrying out a cervical smear test or offering an STI test. Risk assessment could also be carried out during routine care or when a new patient registers; have structured, one-to-one discussions with people at high risk of STIs (if trained in sexual health), or arrange for these discussions to take place with a trained practitioner.

25. Other health checks and screening – offer people equivalent health checks to those offered in the community, for example: the NHS health check programme; learning disabilities; annual health check; relevant NHS screening programmes, such as those for AAA and bowel, breast and cervical cancer.

26. Ensure that the different teams (including prison staff) that manage a person’s care in prison communicate with one another to co-ordinate care.

27. Share information with other health and social care staff, offender supervisors and probation providers who are involved in the person’s care in prison if necessary for the person’s care.

28. Ensure that people with complex health and social care needs have a lead care co-ordinator responsible for managing their care. Ensure that the person and all healthcare and prison staff know who this is.

29. Share relevant information about people with complex needs with prison staff using prison record systems in line with legislation and national guidance. This should include information about any high-level risks, such as: risk of self-harm, risk to others, communicable diseases, epilepsy, diabetes, allergies, deteriorating health conditions, learning disabilities.

30. Review people in prison with complex health and social care needs. Ensure that if a person is supported by a multidisciplinary team, the teams meet regularly to plan and co-ordinate ongoing management. These should be facilitated by primary care.

31. Document all health and social care patient interactions and any information related to health and social care in the person’s primary care patient record.

32. Consider using peer support and mentoring to help promote a healthy lifestyle while in prison.

33. Offer people in prison tailored health information in a variety of formats, including face-to-face. Include advice about: exercise, diet, stopping smoking, sexual health, personal hygiene, including oral hygiene.

34. Encourage people to be physically active. Offer them information about: the benefits of exercise, what exercise facilities are provided, where they are and how they can use them; for example: going to the gym, using the exercise yard, exercises that can be done in the cell.

35. Offer people information and advice in line with recommendations in the NICE guidelines on: physical activity: brief advice for adults in primary care, physical activity: exercise referral schemes, preventing excess weight gain, obesity: identification, assessment and management (section 1.6 on physical activity).

36. Offer people information about: the benefits of a healthy diet and healthier food options available in the prison. See section 1.7 on dietary advice in NICE’s guideline on obesity: identification, assessment and management.

37. Offer people in prison information about the risks of smoking and support available to stop as part of smoking-cessation services (e.g. nicotine patches and motivational support). See the NICE pathway on smoking.

38. Offer people in prison information about STIs and available sexual health services.

39. Ensure that people in prison have discreet access to condoms, dental dams and water-based lubricants without the need to ask for them.

40. Carry out an individual risk assessment to determine if the person can hold their medicines IP. Allow people in prison to hold all medicine IP unless the person does not pass the risk assessment.

41. Directly observe the administration of all schedule 2 and 3 medicines (also see NICE’s guideline on controlled drugs) and medicines for tuberculosis (see NICE’s guideline on tuberculosis).

42. Directly observe the administration of any medicine that is not IP.

43. Work with prison staff to ensure a system is in place to supervise the administering of medicines not held IP to maximise adherence allow timings of medicines doses to align with the prescribed dose regime, reduce diversion (passing medicines on to other people) and protect confidentiality; see the section on supporting adherence in NICE’s guideline on medicines adherence.

44. Review and (if necessary) repeat a person’s risk assessment for IP medicine if the person’s circumstances change. Involve a multidisciplinary team if needed, including prison staff and the person. Examples of when the risk assessment should be repeated include: if carrying out a medicines review if a person is considered able to manage their own medicines after a period of having medicines not IP; if there is a medicine safety incident, including evidence of self-harm if someone has raised security concerns (e.g. about bullying, diversion or hoarding); if the person has not been taking their prescribed medicines; if there is concern about the person’s ability to self-medicate when following the ACCT care planning approach; if the person is transferred to or from a segregation unit.

45. Consider providing storage for IP medicine in prison cells, for example, a lockable cupboard.

46. Give people in prison information and education about medicine adherence (see the section on patient involvement in decisions about medicines in NICE’s guideline on medicine adherence).

    Monitor people with CCs in accordance with the following NICE guidelines:

47. Chronic heart failure www.nice.org.uk/guidance/ng106.

48. CKD www.nice.org.uk/guidance/cg182.

49. COPD www.nice.org.uk/guidance/NG115.

50. Epilepsy www.nice.org.uk/guidance/cg137.

51. Hypertension www.nice.org.uk/guidance/ng136.

52. Secondary prevention of MI www.nice.org.uk/guidance/cg172.

53. Diabetes (Type 1) www.nice.org.uk/guidance/ng17.

54. Diabetes (Type 2) www.nice.org.uk/guidance/ng28.

55. Asthma www.nice.org.uk/guidance/qs25.

Local quality indicators

Selected from local quality requirements from the NHS Standard Contract for prison healthcare 2019/2020 for the North East, North West, and Yorkshire and Humber (set by the Commissioning Team under schedule 4) www.england.nhs.uk/nhs-standard-contract/previous-nhs-standard-contracts/19-20/.

1. Number and percentage of patients over the age of 55 who have received an examination/assessment of their attention and concentration, orientation, short- and long-term memory, praxis, language and executive function using a validated tool such as MMSE, six-item Cognitive Impairment Test (6–CIT), or the GPCOG, in accordance with NICE CG42.

2. Number of patients who have been appropriately referred to Memory Assessment Services.

3. Number of patients who have been diagnosed with dementia and what type of dementia: that is vascular, Lewy body etc.

4. Number of patients who are taking acetylcholinesterase inhibitors (donepezil, galantamine, rivastigmine) for mild to moderate disease, or memantine for moderate disease.

5. Detailed ‘How am I Driving Report’ from SystmOne to be submitted with improvement plan for areas that are recording a red indicator.

6. Transfers should be in accordance with NICE NG57, NG66 and Substance Misuse clinical guidance (Orange book). Transfers between Prisons and Courts:

   1. Number and percentage of patients with ongoing health needs and/or on prescribed medication seen by a nurse prior to transfer to another establishment.

   2. Number and percentage of patients on prescribed medication who are transferred with 7 days' worth of medication.

   3. Number and percentage of patients seen by a nurse and declared unfit for transfer.

7. The provider to provide a narrative report detailing the total numbers of transfers arriving in the prison, broken down to each month in the time period with the following fields:

   1. Arriving without medication – sending prison to be identified.

   2. Individuals on clinical substance-misuse pathways arriving without communication with Substance-Misuse Team – sending prison to be identified.

   3. Complex MH patients arriving without communication with MH team – sending prison to be identified.

   4. Individuals with complex physical health problems arriving without communication with physical health team.

   5. Details of reports/concerns received from prisons where it has been highlighted that a patient has been transferred unsafely – containing remedial actions to prevent reoccurrence.

8. Released from prison:

   1. Number and percentage of patients seen by a nurse prior to release from custody.

   2. Number and percentage of patients released from custody with 7 days' worth of medication.

9. A pathway is in place with secondary care specialist services and clearly details:

   1. The process for blood-borne virus (BBV) screening within the healthcare service in the prison, including screening at reception/second reception and opportunistic screening.

   2. How DBSTs are ordered.

   3. Where the tests are sent for testing.

   4. How results are received back in health care.

   5. How patients are informed of the results.

   6. The process for referrals to specialist services for those patients with positive results.

10. Data to be provided per prison via opt-out method to include amount of DBST, aiming for a target uptake rate of 70%:

    1. Number of new receptions per month.

    2. Number and percentage of new receptions offered DBST.

    3. Number and percentage of new receptions accepting the opt-out DBST.

11. Tetanus, diphtheria and inactivated polio vaccine (Td/IPV) – numbers eligible as per National Immunisation Schedule and number received as per National Immunisation Schedule and % who have received.

12. Hep A – numbers eligible as per National Immunisation Schedule and number received as per National Immunisation Schedule – and % received.

13. Pneumococcal (PPV) – numbers eligible as per National Immunisation Schedule and number received as per National Immunisation Schedule, then they can provide % received.

14. The providers have developed a detailed multiagency seasonal flu plan for the implementation and delivery of a vaccination programme for patients, and demonstrate the preparation required for an anticipated outbreak of seasonal flu. The plan must be agreed with PHE.

15. The providers have developed a detailed multiagency Outbreak Plan per prison which has been submitted and agreed with PHE.

16. The provider has in place Patient Group Directions to support both flu vaccination and antiviral medication – there should be no gap in compliance with the antiviral medication, and the flu vaccine patient group direction should be fully authorised before 1 September 2019.

17. The provider to provide a standard operating procedure (SOP) for the management of people with end-of-life care needs within the establishment. SOP to include, but not limited to, access to specialist palliative care advice and support, and suitably trained personnel for administration of syringe driver.

18. Re-audit of Dying Well In Custody against the Ambitions Standards.

19. Submission of Dying Well In Custody audit indicating full compliance against the Dying Well In Custody Ambition standards.

20. Quarterly analysis of numbers of the following medication supported by logs and graphs indicating reduction and improvement plan for reduction: tramadol; pregabalin; gabapentin; benzodiazepines; codeine; zopiclone.

21. An up-to-date Medicines Management Strategy, which includes the reduction of tradeable medication.

Opioid, gabapentin and benzodiazepine prescribing55,56

1. Prescribed pregabalin/gabapentin but no diagnosis of neuropathic pain in clinical record. Current evidence suggests that the risk of misuse may be greater with pregabalin than gabapentin. Consider changing patients to gabapentin who have never previously tried gabapentin for neuropathic pain rather than continuing with pregabalin. It is important for prescribers to have a complete list of medications (including any over-the-counter products or illicit drugs) that patients are taking so that hazardous drug interactions can be minimised or avoided. If dependence on pregabalin or gabapentin, or other misuse or diversion, is suspected or identified the patient should be reviewed and the concerns of the prescriber should be discussed sensitively and documented clearly.

2. Pregabalin/gabapentin prescription and at CKD stage 3–5. Currently, pregabalin appears to be more sought-after for misuse than gabapentin. There is a growing illegal market, and these drugs are also being bought through online pharmacies. Prescribers should evaluate the risks of continued prescribing and make appropriate decisions regarding quantity of drugs prescribed and the intervals at which the patient should be reviewed. If dependence on prescribed medication is suspected or confirmed, the problem may require specialist advice on managing the dependence. It may simply require agreement on suitable controls on access to, and maximum daily use, of the drugs being misused (when it is felt the medication is still needed for the management of the original indication). Careful reassessment of the patient may lead to an appropriate decision to offer a planned withdrawal of the medication, particularly if the medication does not appear any longer to be required for the main clinical indication.

3. Over 65 years and prescribed pregabalin/gabapentin in last 8 weeks. In 2013, the total use in England of both these medicines was 8.2 million prescriptions. This represents a 46% rise in prescribing of gabapentin and 53% rise in pregabalin prescribing since 2011. Prescribers should set realistic expectations and treatment goals. Achieving pain-free status is not always achievable. Reduction in pain by 50% is a commonly used end point in clinical trials. If completely inappropriate use is confirmed (e.g. if there is unequivocal objective evidence that the drugs are simply being diverted), the drugs should be stopped. However, in some cases, patients may have diverted a portion of their treatment, such as to a family member, and so adequate assessment is needed to try and determine the most suitable approach in each case and context.

4. Diagnosis of depression and MH and prescribed pregabalin/gabapentin in last 8 weeks. Gabapentin and pregabalin have been mentioned on death certificates as adjunctive substances in patients dying of drug poisoning.

5. Patient issued at least two of gabapentin/pregabalin/duloxetine/amitriptyline in last 8 weeks. Between 2013 and 2015 in the UK, deaths reported to involve gabapentinoids increased by almost 400%.

6. Pregabalin/gabapentin and an opioid in last 8 weeks.

7. Any issue of lidocaine patch in last 8 weeks.

8. Lidocaine patch and no diagnosis of post-herpetic neuralgia.

9. Lidocaine patch on repeat for last 6 months.

10. Prescribed strong opioids.

Overcoming barriers to self-management of chronic pain in primary care.

Self-management is a recommended intervention for chronic pain and can improve patients’ quality of life and reduce impact on NHS services. This study found a number of barriers to self-management. Many patients felt the initial discussion about self-management came too late or not at all. Consider discussing self-management of pain much earlier in the patient pathway for those at risk of developing chronic non-cancer pain.

1. Men aged under 50 years and prescribed strong opioids.

Initial starting dose and the first refill of an opioid prescription increase risk of chronic use.

This retrospective cohort study followed opioid-naïve patients after their first prescription. Those who received more than one prescription within the first month of taking opioids and those given a higher morphine equivalent dose of opioid were more likely to become long-term users of opioids. Could we reduce the number of people becoming long-term users by thinking twice about that first repeat prescription?

1. Patients aged over 75 and prescribed strong or weak opioids.

Tramadol kills more people than heroin and cocaine.

Professor Jack Crane, State Pathologist of Northern Ireland, says tramadol is now claiming more lives than any other drug. Reclassification to a class C drug last year has made it illegal to use without a prescription, but many are obtaining it via the black market. He is campaigning for it to be reclassified to a Class A drug. In 2014, 240 deaths in Britain were linked to tramadol. Perhaps we need to think carefully before prescribing?

1. Women aged over 65 years and prescribed strong or weak opioids.

2. Polypharmacy (on 10 or more repeat prescriptions) and prescribed strong or weak opioids.

3. Any MH diagnoses and prescribed strong or weak opioids.

4. Taking antidepressant and a strong or weak opioid.

5. Taking benzodiazepines and a strong or weak opioid.