Configuration of vascular services: a multiple methods research programme

Article history

The research reported in this issue of the journal was funded by PGfAR as project number RP-PG-1210-12009. The contractual start date was in June 2013. The final report began editorial review in June 2019 and was accepted for publication in July 2020. As the funder, the PGfAR programme agreed the research questions and study designs in advance with the investigators. The authors have been wholly responsible for all data collection, analysis and interpretation, and for writing up their work. The PGfAR editors and production house have tried to ensure the accuracy of the authors’ report and would like to thank the reviewers for their constructive comments on the final report document. However, they do not accept liability for damages or losses arising from material published in this report.

Copyright statement

Copyright © 2021 Michaels et al. This work was produced by Michaels 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 adaption 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.

2021 Michaels et al.

Background

In providing any clinical service, there is tension between maximising efficiency, cost-effectiveness and other desirable features of the service. Financial pressure on providers encourages efficiency, maximising activity for the minimum possible cost. Commissioners wishing to maximise cost-effective use of resources are interested in wider outcomes. However, they are limited in their ability to identify clinically meaningful outcome measures or validated proxy measures and process attributes that adequately reflect service quality and can be derived from currently available data sources. Other service attributes of importance to service users and wider society, such as equity, processes of care and dignity, are not routinely assessed but may be significantly affected by service reconfiguration. For example, when considering potential models for devolved or centralised services, the need for providers to maximise efficiency may produce adverse incentives that encourage smaller independent units to increase activity by treating cases where effective management could be better provided by a larger unit. However, the same drivers may cause centralised units to consolidate on a single site, reducing patient choice and accessibility and potentially reducing equity. It is thus vital that in planning services the key desirable attributes are identified, their relative importance is understood and there is a means available to monitor the effects of any changes.

There is currently enormous pressure for the reconfiguration of vascular services due to many conflicting requirements. Vascular surgery has separated from general surgery, progressing from a situation in the late 1990s with only a handful of centres with sufficient specialist clinicians to offer separate emergency vascular services1 to the situation when the programme was planned, when about half of vascular surgeons had no general surgical practice. 2 In July 2011 the four Departments of Health and Social Care in the UK agreed to the formation of a new specialty of vascular surgery, and a Specialist Advisory Committee was established and began specialty training year 3 in October 2013. Since then, most vascular and general services have separated completely, with < 10% of vascular services providing any general surgical cross-cover in 20153 and only 5% of vascular surgeons providing any general surgery in a 2018 vascular workforce survey. 4

These changes, and similar subspecialisation in vascular radiology, are driven partly by technological and clinical developments, such as new minimally invasive treatments for peripheral arterial disease (PAD), endovascular stent grafts for abdominal aortic aneurysms (AAAs), new treatments for varicose veins (VV) and new imaging methods, such as magnetic resonance angiography (MRA) and computerised tomography angiography (CTA).

Other drivers for service change have been the implementation of screening for AAAs (see www.gov.uk/topic/population-screening-programmes/abdominal-aortic-aneurysm; accessed 1 December 2020), scarcity of expertise in vascular interventional radiology,5 changes in training and working hours related to the European Working Time Directive and recognition of the need for sustainable out-of-hours specialist service provision. 3

Research carried out for the National Institute for Health Research (NIHR) Health Technology Assessment (HTA) programme 20 years ago in a single region highlighted conflicting pressures:6

• the need to optimise health gains by planning activity in centres with access to specialist expertise, the provision of emergency vascular and interventional radiology services and multidisciplinary working

• workforce planning, staffing and training needs

• improving equity of access and outcome between socioeconomic and geographic groups

• patient preferences for attributes, such as location, travelling times, waiting times and processes of care (including the availability of newer, minimally invasive techniques)

• links to other services, such as diabetes, general surgery, leg ulcer, cardiothoracic, stroke and renal services

• resource availability and the capital and recurrent costs associated with reconfiguration.

Overview of the programme

The overarching aim of the research programme is to identify and draw together existing evidence regarding vascular service configuration; to develop the tools necessary to plan and assess existing services; and to predict and evaluate the results of reconfiguration. In the original application, the programme was divided into four main workstreams that are closely inter-related and include a number of substudies. Figure 1 provides an overview of the workstreams, the links between them and the relevant outputs and appendices.

FIGURE 1.

Overview of the programme, workstreams, inter-relations and outputs. CAD, carotid artery disease; EVAR, endovascular aneurysm repair; HES, Hospital Episode Statistics.

The main outputs of the programme are a new electronic Personal Assessment Questionnaire – Vascular (ePAQ-VAS) to facilitate the collection of patient-reported outcome measure (PROM) data, and a series of economic and decision analytic models that incorporate all of the current evidence to allow the characterisation of current services and prediction of the effects of any reconfiguration at either a local or a national level.

An interactive demo version of the ePAQ-VAS, a copy of a sample report and a demonstration of the management’s site are available at www.epaq.co.uk/Demo/VascularDemo (accessed 1 December 2020). The web-based interface for the organisational model can be accessed at https://modellers.sheffield.ac.uk/vascularmodel/ (accessed 1 December 2020).

To develop these, separate strands of the research have involved a thorough evaluation of existing outcome measures used in vascular services, collection of published and primary qualitative data about vascular outcomes and developing and testing the ePAQ-VAS. This has been validated as a tool to monitor clinical outcomes and is intended to be used on an individual patient basis in clinical practice, and to provide aggregate data for assessing and monitoring the effectiveness of clinical services. Further work has developed algorithms to produce consistent analysis of practice and outcomes from routinely collected hospital data, which may be used in the future to evaluate the effects of reconfiguration.

Report outline

The following is a brief overview of each of the workstreams, as originally envisaged in the application, describing the component studies and how these are incorporated into the report. The appendices provide additional details of published papers and unpublished methods and results.

Summary of changes from the proposal

Patient and public involvement

The Sheffield Teaching Hospitals NHS Foundation Trust Online Public Advisory Panel provided feedback on the study materials throughout the development of the study. In the summer of 2016, the patient and public involvement (PPI) panel reviewed study documents, including the participant information sheet and invitation letter, and feedback was used to revise the wording of these documents. Moreover, members of the PPI panel participated in mock interviews using the AAA interview schedule. The overall aim was to test the language, structure and comprehension of the study materials to gather feedback and refine the survey. The feedback obtained included suggestions on the wording and design of study materials and the need to present risk (percentages) in an understandable way. All of the feedback was incorporated into the final version of the study materials. In particular, while presenting risk, a simple diagram was designed to explain what was meant by ‘chance of success’. This was included in the interview booklet and was used as a guide to decision-making during the telephone interview.

The effects of reconfiguration on practice and outcome

The relationship between the number of invasive procedures (volume) conducted by health-care institutions or individual clinicians and the outcomes, such as mortality, has been discussed and investigated in multiple conditions since the 1980s. 25,26

Although evidence of an inverse relationship between the volume of vascular procedures performed and the adverse outcomes is presented in previous systematic reviews and meta-analyses,27–37 the included data are dated. The evidence primarily represents populations in the USA38 and is, therefore, of questionable value in relation to contemporary UK practice. In the context of ongoing reconfiguration of vascular services in the UK and recent technological advances in the treatment of vascular conditions, a series of systematic reviews were conducted to evaluate the relationship between mortality and the volume of vascular procedures undertaken by individual clinicians and/or hospitals in European populations.

Methods

In general, the reviews were conducted in four stages:

1. A protocol was developed with input from clinicians, information specialists and academics and registered on PROSPERO (www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42014014850; accessed 1 December 2020) prior to the conduct of each review.

2. A single search strategy39 that combined search terms for all vascular conditions was developed and electronic searches were conducted in databases including MEDLINE, EMBASE™ (Elsevier, Amsterdam, the Netherlands), Cumulative Index to Nursing and Allied Health Literature (CINAHL) and PsycInfo^® (American Psychological Association, Washington, DC, USA). Additional hand-searches and citation searches were also conducted.

3. An overview of existing systematic reviews38 was undertaken. However, no relevant current systematic review of high quality was identified that answered the research question.

4. Three systematic reviews relating to three discrete conditions, PAD, AAA and CAD, were conducted. Systematic reviews were subsequently presented at international conferences and published in peer-reviewed journals (see Appendices 2–4). 13–15

Standard systematic review methods,40 in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) recommendations,40 were followed and are detailed in the published papers. 13–15 A decision to focus on European populations was made because the organisation and delivery of ‘socialised’ health care in these countries is similar, but not identical, to the UK NHS. This is in contrast to the USA, where a market-led model is the norm.

The ideal method of identifying a causal relationship between an exposure or intervention (in this case, volume) and an outcome is to conduct a randomised controlled trial; however, the studies included in these reviews were expected to be observational rather than experimental because of the practical and ethics difficulties of randomising participants to high- or low-volume clinicians or institutions. It was, therefore, judged to be important to evaluate studies on the effects of volume in accordance with principles that would avert any understimation of the risk of bias or attribution of an inflated level of certainty to any measure of effect size. A Cochrane Risk of Bias Assessment Tool for Non-Randomised Studies of Interventions was considered to be appropriate for this reason and, therefore, was used to assess the methodological quality of the included studies. Meta-analyses, although planned, were judged to be inappropriate because of clinical and methodological heterogeneity and the risk of selection, reporting and publication bias. Narrative syntheses were, therefore, conducted, with tabulation of results reflecting the different clinical and procedural groupings presented in individual studies.

Results

Discussion

The hypothesis that individual and institutional volumes are inversely related to adverse outcomes seems plausible, and these reviews, based on the largest and highest-quality studies included, found evidence that this is the case for CEA and AAA procedures. However, volume is a convenient but potentially imprecise proxy for quality. The mechanisms by which any benefits are produced were not investigated in this review. For this reason, subsequent benefits are potentially difficult to replicate. It is questionable whether or not simply centralising vascular procedures to be conducted by high-volume clinicians in high-volume institutions will replicate the outcomes associated with a high volume of procedures.

The list of potential confounders is extensive, but includes patient age and sex, surgeon caseload, hospital volume, comorbidities, surgical variables, American Society of Anesthesiologists grade, vascular risk factors, type of hospital, day of procedure, transfer between hospitals, social deprivation, staffing levels (medical and nursing), teaching hospital status, level of research activity and ratio of high-dependency/intensive therapy unit beds to hospital beds. Any of these could be responsible for some or all of the identified volume–outcome effect, either alone or in combination with other known or unknown variables, and it is possible that interventions aimed at manipulating these variables could be effective at improving outcomes for which a wholesale reconfiguration of vascular services might not.

Existing high-volume hospitals have infrastructure and human elements that differentiate them from low-volume hospitals, and potentially from any new institution that is developed to tap into or benefit from such an assumed relationship. It could be that increased volume may be necessary, but not sufficient, to replicate the outcomes already achieved at existing high-volume hospitals. New high-volume hospitals will need to recreate the conditions prevalent in existing high-quality, high-volume hospitals if they are to achieve results comparable to the highest achieving high-volume hospitals.

The authors intended to determine the minimum procedure thresholds that doctors and institutions should practise at to achieve acceptable outcomes; however, this was complicated by the range of clinical and procedural categories that were assessed by the individual studies and it was inappropriate to make definitive recommendations on the basis of the findings.

In addition, attempts to quantify the relationship between volume and outcome do not account for the role of preference. The provision of centres that provide high enough volumes to meet minimum volume criteria might be achievable and convenient in high-density populations, such as London and other major conurbations. However, in more sparsely populated regions the provision of high-volume centres would certainly mean an additional burden of travel to access health care, which could affect patients’ decisions to access treatment. Parallel research conducted as part of this Programme Grant does consider the role of preference.

Reviews of existing patient-reported outcome measures

Results

Details of the published systematic reviews of PROMs, with further details of the review results, are provided in Duncan et al. ,16 Poku et al. ,17 Essat et al. ,18 Aber et al. 19 and Poku et al. 20

Discussion

All of the systematic reviews contribute to the growing evidence of psychometric performance of PROMs in patients with vascular conditions, although a majority of the included studies (n = 41) did not report a complete psychometric evaluation of a single PROM. Widespread heterogeneity in the study methodology, patient population and treatment pathway could, in principle, limit the conclusions of the individual reviews. Therefore, these are important considerations in future research.

Reviews of qualitative evidence of vascular outcomes

Results

Five systematic reviews of qualitative evidence were completed to understand and summarise the impact that PAD, AAA, CAD, VV and VLU have on the daily living of patients. 16,21–24 The characteristics and main findings of the studies included in these five qualitative evidence syntheses systematic reviews are summarised in Table 2.

Discussion

A total of 32 studies were included across the five reviews of existing qualitative research. The qualitative evidence from these reviews identified major themes and several subthemes within each disease area. There was some overlap between these themes. These qualitative data were used to develop the conceptual framework for the new electronic PROM developed as part of this NIHR programme grant. The evidence from the triangulation helped to identify where previous disease-specific PROMs fell short in covering issues that were deemed to be important to patients with vascular disease. Further detail about the use of these qualitative data in developing the new outcome measure is provided in Development of the electronic Personal Assessment Questionnaire – Vascular.

Analysis of Hospital Episode Statistics data: general methods

A major part of the first workstream of the programme was the analysis of HES data to characterise the workload of vascular services; identify trends in activity, working practices and outcomes; and relate these to service configuration. This section outlines the processes involved in this analysis, with further details given in the published papers and additional material provided in the appendices and supplementary material. The section starts with a brief description of the nature of HES and the process of obtaining the appropriate extract. Following this, there are sections relating to the process for establishing consistent and clinically relevant groupings of vascular activity, the identification of the sites at which the activity was carried out, methods for obtaining valid measures of outcome from the data, and distinguishing comorbidities and complications.

The subsequent section provides some descriptive material regarding the services that are provided, the trends in practice and configuration of services and outcomes. Further details of these analyses are provided in Appendix 1 and published papers. The detailed risk models that were derived from HES data to populate the economic models are described, along with other aspects of the modelling process, in Modelling the effects of service reconfiguration.

Data extract

The main analysis of hospital activity case-mix, resource use, working practices and outcomes was carried out based on an extract of HES data supplied by NHS Digital, and included all relevant fields in an extract of inpatient episodes covering all likely vascular procedural and diagnostic codes (see Report Supplementary Material 1). Further data extracts included linked records for all other inpatient episodes, critical care episodes and death certification records from the Office for National Statistics (ONS) for the cohort of episodes identified in the initial extract. The original data request was made in July 2013; however, because of considerable delays and changes in procedure at NHS Digital, the original data extract was not obtained until May 2015. When an extension request for the programme was made in the autumn of 2017, a further request was made for an updated HES extract to include the most recent years, but further delays resulted in the extract not being received until February 2019, leaving little time for further detailed analysis.

The initial categorisation of data, as described below, was based on the first data set and revised and updated following the receipt of additional data. However, because of the changes in coding and limited resources, a decision was made to limit the final analysis base to the 12-year period from April 2006 to March 2018, which was the most recent 12-year period that was available.

Hospital Episode Statistics data analysis

The process of analysing the HES data was largely carried out using custom-built programmes written in the R software package (The R Foundation for Statistical Computing, Vienna, Austria) (see Appendix 1). The following is a brief summary of the issues that were addressed for each of these stages of data analysis.

Trends in case-mix, practice and outcome

Abdominal aortic aneurysm

Over the past 12 years, there have been considerable changes in AAA management, with the introduction of a screening programme for men aged 65 years and the introduction of endovascular repair for elective and, increasingly, emergency aneurysm repair. The overall number of elective aneurysm repairs in England increased to a maximum of 4889 in 2011/12 and has been declining gradually since, although the proportion of endovascular repairs has risen to a steady level of approximately 70% for the most recent 3 years. Emergency procedures have declined steadily, from 3411 procedures in 2006/7 to 2302 in 2017/18, with the proportion of EVARs increasing steadily to 36.1% (Figure 2).

FIGURE 2.

Number of AAA admissions by year and category of admission.

There is considerable variation in practice with regard to the use of EVAR. The proportion of patients treated by EVAR varies between ≈ 30% and > 90% of elective cases, with similar variation for emergency admissions. Over 25% of centres do not appear to offer any emergency EVAR service (Figure 3).

FIGURE 3.

Proportion of elective AAA admissions treated by EVAR by year and volume of activity at treating centre (box plot showing median, interquartile range and 10th and 90th centiles).

An increasing proportion of aneurysms treated by EVAR are classified as complex, being coded as juxtarenal or suprarenal aneurysms, increasing from 8.1% in 2011/12 to 18.1% in 2017/18 (see Discussion for a comparison with the estimates in the NVR report).

Table 3 provides summary data regarding the number and demographics, length of stay, critical care usage, re-admission rates and mortality for each of the categories of aneurysm repair, averaged over the most recent 3 years, and Figure 4 provides further details of the critical care usage for those emergency and elective AAA admissions that necessitated a critical care stay.

TABLE 3 - Demographics, resources use and outcomes for AAA admissions in England in 2015–18

IQR, interquartile range; LOS, length of stay; SD, standard deviation.

Demographics	Elective EVAR	Elective open	Emergency EVAR	Emergency open	Unoperated
Number	10,670	4307	2811	2989	1763
Age (years), median (IQR)	76.0 (70.0–81.0)	70.0 (65.0–75.0)	76.0 (70.0–82.0)	75.0 (68.0–79.0)	85.0 (79.0–89.0)
Age (years), mean (SD)	75.1 (7.7)	69.4 (9.0)	74.0 (12.1)	73.0 (9.9)	83.6 (8.1)
Proportion male (%)	86.8	87.0	79.7	82.1	63.1
Proportion diabetic (%)	18.2	13.2	15.1	11.8	14.3
Proportion elective (%)	100.0	100.0	0.0	0.0	1.1
LOS (days), median (IQR)	3.0 (2.0–5.0)	8.0 (6.0–11.0)	10.0 (5.0–19.0)	12.0 (6.0–23.0)	1.0 (0.0–3.0)
LOS (days), mean (SD)	5.1 (10.9)	11.6 (17.3)	17.9 (24.9)	20.2 (27.7)	3.4 (8.1)
Wait (days), median (IQR)	34.0 (16.0–62.0)	29.0 (14.0–52.0)
Wait (days), mean (SD)	48.3 (55.5)	40.8 (41.3)
Number admitted to critical care, n (%)	4805 (45.0)	3828 (88.9)	1905 (67.8)	2563 (85.7)	93 (5.3)
Hours in critical care, median (IQR)	27.3 (22.0–52.3)	70.1 (42.8–118.3)	66.0 (27.8–145.0)	98.0 (48.0–216.0)	32.7 (11.4–88.9)
Hours in critical care, mean (SD)	57.8 (147.8)	115.8 (232.2)	140.0 (229.7)	195.3 (297.7)	134.9 (389.7)
In-hospital death rate (%)	1.4	5.1	13.2	31.9	100.0
30-day mortality (%)	1.4	4.5	12.2	29.8	98.5
Combined post-operative mortality (%)	1.7	5.2	14.1	32.2	100.0
Second procedure (%)	0.3	0.6	1.7	1.1	0.0
Re-admission rate of survivors within 30 days of discharge (%)	15.1	11.6	21.8	17.4

FIGURE 4.

Length of critical stay for those emergency and elective admissions for AAA repair who were admitted to critical care.

Overall, mortality from elective AAA treatment has declined steadily, from 5.6% in 2006/7 to 2.7% in 2017/18, while mortality from emergency treatment fell from 32.2% to 22.3% over the same period. This was partly because of an increase in endovascular treatment, although there has been a reduction in mortality in all treatment categories (Table 4). The interpretation of mortality for emergency repair is confounded by the difficulty in distinguishing between emergency and ruptured cases. In addtion, the number of patients who die after being admitted with a ruptured aneurysm, but before undergoing repair, may not be included in the figures. When considering these issues, both the mortality and the turn-down rate appear to be higher for women than for men. 11

TABLE 4 - Mortality for AAA admissions in England 2006–18 (death in hospital or within 30 days of procedure)

Year	Elective admissions (%)			Emergency admissions (%)
	EVAR	Open	Overall	Ruptured	Non-ruptured	All (including unoperated)
2006/7	2.4	6.0	5.6	41.9	8.6	54.0
2007/8	2.9	6.2	5.4	39.3	8.0	51.2
2008/9	2.1	6.8	5.1	39.4	9.0	49.9
2009/10	2.3	6.1	4.2	36.7	9.3	48.2
2010/11	1.5	5.7	3.5	36.4	8.7	47.0
2011/12	1.8	6.0	3.6	37.3	8.3	45.6
2012/13	1.4	5.3	3.1	35.4	8.5	42.8
2013/14	1.6	4.8	3.1	36.2	9.5	43.2
2014/15	1.6	4.6	2.9	38.4	10.9	42.5
2015/16	1.2	5.7	2.7	38.2	9.4	40.2
2016/17	1.3	4.3	2.5	37.4	13.1	40.9
2017/18	1.4	4.4	2.6	34.9	9.9	40.1

Based on linked data with repeat admission and ONS mortality data, Kaplan–Meier analysis of long-term survival was carried out for some of the key diagnostic groups. Kaplan–Meier plots for overall survival (OS) following AAA repair are provided in Figure 5, and show that OR is associated with higher initial mortality but better long-term survival. These differences persist after correction for case-mix differences (see Appendix 6 and Report Supplementary Material 6).

FIGURE 5.

Kaplan–Meier survival estimates for elective infrarenal EVAR and open AAA repair.

Peripheral arterial disease

The total number of vascular reconstructions (including all surgical and endovascular procedures) in England increased from about 25,000 in 2006/7 to a maximum of nearly 33,000 in 2013/14, decreasing to 29,000 in 2017/18. Over the same period, there was a gradual increase in the proportion that were emergency admissions, from 27.7% to 31.1%. For elective admissions, the proportion that underwent endovascular treatments remained constant at around 70%, whereas the proportion for emergency admissions increased from 41.6% to 51.7%.

The number of major amputations fell from a peak of 5851 in 2008/9 to 5522 in 2017/18, with approximately two-thirds being admitted as an emergency. Over the same period, the number of minor amputations increased from 5410 to 8280.

All procedures for PAD are more common in men but the proportion varies by category, being highest, at > 75%, for distal bypasses but just over 50% for elective minor amputations. Most patients with PAD are aged > 60 years, with those admitted as an emergency, women and those with more distal disease tending to be older.

Table 5 provides summary data regarding the demographics, length of stay, critical care usage and re-admission rates and mortality for each of the categories of PAD admission, averaged over the most recent 3 years (see Report Supplementary Material 7).

TABLE 5 - Demographics, resources use and outcomes for PAD admissions in England in 2015–18

IQR, interquartile range; LOS, length of stay; SD, standard deviation.

Demographics	Investigations only	Ulcer (no procedure)	Major amputation	Minor amputation	Angioplasty (mild/moderate)	Angioplasty (severe)	Reconstruction (mild/moderate)	Reconstruction (severe)
Number	78,976	29,211	16,461	24,035	37,552	20,217	10,482	20,202
Age (years), median (IQR)	67.0 (52.0–77.0)	71.0 (59.0–80.0)	66.0 (54.0–76.0)	67.0 (56.0–77.0)	69.0 (61.0–76.0)	74.0 (64.0–82.0)	69.0 (62.0–76.0)	69.0 (58.0–77.0)
Age (years), mean (SD)	63.6 (17.8)	68.6 (15.1)	63.8 (15.9)	66.1 (14.5)	67.9 (11.6)	71.7 (13.3)	68.4 (10.7)	66.6 (14.9)
Proportion male (%)	53.2	62.0	71.0	68.0	66.8	60.1	76.3	67.0
Proportion diabetic (%)	21.5	44.8	46.2	64.4	30.9	49.5	28.3	27.6
Proportion elective (%)	42.7	38.9	34.7	50.2	100.0	32.5	100.0	36.9
LOS (days), median (IQR)	0.0 (0.0–7.0)	3.0 (0.0–12.0)	23.0 (9.0–48.0)	5.0 (0.0–15.0)	0.0 (0.0–1.0)	7.0 (1.0–17.0)	4.0 (2.0–6.0)	10.0 (5.0–20.0)
LOS (days), mean (SD)	8.4 (27.9)	11.3 (22.8)	35.2 (50.7)	13.2 (38.9)	1.4 (26.4)	15.0 (26.5)	6.2 (9.7)	17.7 (24.3)
Wait (days), median (IQR)	29.0 (14.0–49.0)	41.0 (15.0–84.0)	23.0 (7.0–60.0)	22.5 (8.0–55.0)	30.0 (15.0–55.0)	22.0 (12.0–40.0)	34.0 (14.0–64.0)	26.0 (11.0–55.0)
Wait (days), mean (SD)	40.7 (74.3)	61.5 (90.5)	46.2 (66.2)	41.8 (56.3)	44.1 (73.7)	31.5 (38.9)	48.0 (52.9)	41.8 (47.5)
Number admitted to critical care, n (%)	12,077 (15.3)	1356 (4.6)	3177 (19.3)	623 (2.6)	548 (1.5)	1649 (8.2)	1772 (16.9)	7336 (36.3)
Hours in critical care, median (IQR)	74.0 (38.0–165.2)	74.5 (32.9–159.3)	69.9 (25.3–166.3)	87.8 (33.7–206.1)	38.8 (22.1–74.6)	71.6 (32.5–156.9)	29.3 (21.0–65.3)	52.4 (24.0–114.8)
Hours in critical care, mean (SD)	160.6 (314.3)	158.6 (378.4)	162.2 (311.2)	197.8 (394.3)	74.2 (133.2)	151.8 (251.6)	61.0 (127.3)	115.8 (232.8)
In-hospital death rate (%)	4.9	5.2	8.3	2.2	0.2	4.4	0.8	6.4

Mortality is high among patients with severe limb ischaemia (defined as emergency procedures, distal bypasses, those with a current or preceding minor or major amputation or with a diagnosis of ulcer). The median OS following angioplasty is just under 3 years and just over 6 years for open procedures, with similar differences for amputation-free survival (AFS) (Figure 6).

FIGURE 6.

Kaplan–Meier estimates for OS and AFS following open surgery and angioplasty for severe limb ischaemia. OS, overall survival.

Carotid artery disease

The number of CAD procedures increased to a maximum of 6299 in 2011/12, decreasing to 4711 in 2017/18, with the proportion of endovascular procedures increasing gradually to 10.4% in 2017/18 and the proportion of patients who were emergency admissions increasing from 14% in 2006/7, to ≈ 35%, where it has remained over the past 5 years. Approximately 66% of those patients undergoing surgery are men with an average age of 71 years; those undergoing endovascular treatment were slightly younger and including a higher proportion of women (Table 6 and Report Supplementary Material 8).

TABLE 6 - Demographics, resources use and outcomes for CAD admissions in England in 2015–18

IQR, interquartile range; LOS, length of stay; SD, standard deviation.

Demographics	Endovascular	Endarterectomy
Number	880	12,819
Age (years), median (IQR)	66.0 (56.0–74.0)	72.0 (65.0–79.0)
Age (years), mean (SD)	63.9 (13.6)	70.9 (10.8)
Proportion male (%)	59.8	66.4
Proportion diabetic (%)	21.0	25.0
Proportion elective (%)	59.0	66.4
LOS (days), median (IQR)	3.0 (1.0–14.0)	3.0 (2.0–6.0)
LOS (days), mean (SD)	16.5 (39.6)	7.5 (17.6)
Wait (days), median (IQR)	13.0 (5.5–34.0)	7.0 (4.0–15.0)
Wait (days), mean (SD)	26.5 (37.0)	16.7 (41.9)
Number admitted to critical care, n (%)	286 (32.5)	5288 (41.3)
Hours in critical care, median (IQR)	47.7 (22.9–137.3)	24.0 (20.1–45.5)
Hours in critical care, mean (SD)	156.1 (257.6)	43.8 (86.4)
In-hospital death rate (%)	5.9	1.1
30-day mortality (%)	5.2	1.2
Combined post-operative mortality (%)	6.4	1.5
Second procedure (%)	1.5	0.2
Re-admission within 30 days (%)	12.5	10.9
Proportion with prior stroke (%)	9.2	17.0

The median survival, free of re-admission with stroke, following a CAD procedure is 8.1 years for those patients without a prior stroke and 6.2 years for those with a prior stroke (Figure 7).

FIGURE 7.

Kaplan–Meier survival estimates free of stroke re-admission following carotid treatment for those with and without a prior stroke diagnosis.

Varicose veins

The total number of admissions for treatment of VV fell substantially between 2009/10 and 2012/13, from nearly 40,000 to a low of just over 25,000 cases per year. The number of open procedures (high tie, stripping, etc.) has continued to fall and been largely replaced by the new modalities of endovenous laser treatment (EVLT) and radiofrequency ablation (RFA), with the total number of VV procedures rising again in recent years.

The demographics of the treated population has altered over the past 12 years, with an increasing proportion of men and an older population. Those treated by avulsions tend to be younger and include a higher proportion of women (Table 7).

TABLE 7 - Demographics, resources use and outcomes for VV admissions in England in 2015–18

Demographics	RFA	EVLT	High tie, etc.	Sclerotherapy	Avulsions
Number	35,495	16,831	16,495	16,947	5398
Age (years), median (IQR)	54.0 (42.0–67.0)	53.0 (42.0–66.0)	51.0 (40.0–63.0)	57.0 (45.0–69.0)	49.0 (39.0–60.0)
Age (years), mean (SD)	54.3 (15.5)	53.8 (15.7)	51.6 (14.7)	56.6 (15.5)	50.1 (14.3)
Proportion male (%)	44.4	43.6	46.0	37.6	29.3
LOS (days), median (IQR)	0.0 (0.0–0.0)	0.0 (0.0–0.0)	0.0 (0.0–0.0)	0.0 (0.0–0.0)	0.0 (0.0–0.0)
LOS (days), mean (SD)	0.1 (6.7)	0.081 (3.3)	0.79 (6.7)	0.15 (12.9)	0.078 (0.82)
Wait (days), median (IQR)	74.0 (42.0–121.0)	72.0 (42.0–112.0)	69.0 (37.0–116.0)	74.0 (41.0–120.0)	71.0 (38.0–116.0)
Wait (days), mean (SD)	90.2 (67.5)	87.1 (66.0)	86.9 (82.6)	96.6 (91.3)	88.8 (108.6)
Re-admission within 30 days (%)	4.4	4.0	5.7	4.9	3.8

The different treatment modalities resulted in differences in re-admission rates for further VV interventions. Within 5 years of the first recorded treatment, 40% of those treated by sclerotherapy had been re-admitted, compared with ≈ 15% of those treated by open surgery, 20% treated with RFA and 27% treated with EVLT (Figure 8 and see Report Supplementary Material 9).

FIGURE 8.

Re-admission rates for VV treatments by modality of original treatment.

Discussion

Hospital Episode Statistics provides a rich source of data regarding hospital activity but the data are complex and can be difficult to interpret. There are a number of limitations in the coding systems and other pitfalls in interpreting the data that are particularly relevant to understanding the nature of vascular services. Specific issues that are important are the lack of detailed diagnostic codes for distinguishing between important subgroups of vascular patients, such as those with critical ischaemia and intermittent claudication. There are also difficulties in distinguishing between procedures or diagnoses that may be either complications of treatment or comorbidities, for example stroke can be both a complication of and an indication for carotid surgery and amputation can be a primary event or the result of a complication of failed treatment. These problems are compounded by the lack of adequate coding for laterality, which makes it impossible to distinguish between two procedures on the same leg or separate procedures on both legs.

Another difficulty in interpretation arises from the nature of the data set, which is based on episodes of treatment rather than admissions or patients; therefore, complex procedures of data linkage and identification of overlapping and repeated episodes are necessary to understand pathways of care. Where differences are identified, these may relate to real variations in clinical treatment or inconsistencies in coding practice.

Although these limitations are recognised, HES provides a very rich source of data and is the only complete database that will allow linkage of episodes throughout a patient pathway, which can also be linked to data regarding mortality.

The detailed analysis of HES data that has been carried out for this programme of research has addressed a number of the potential issues within the data through the methods developed for cleaning and linking data and modifying algorithms for identifying case-mix, comorbidities and complications, which take into account previous diagnoses and re-admissions. Although it is not possible to address all the inconsistencies in coding, some attempt can be made to produce consistent figures by identifying clinical groupings from within the data that are a proxy for certain subgroups, such as those with severe or moderate limb ischaemia and those who are admitted with a ruptured aortic aneurysm and die without vascular intervention.

Taken as a whole, the analysis of HES data demonstrates a number of trends. Overall outcomes, particularly mortality related to AAA, appear to be improving over time. Although the reduction in mortality is partly because of the move towards EVAR, there has also been mortality improvement in each of the subgroups of treatment. Overall, there is a trend towards a reducing number of AAA repairs, whereas for other diagnostic groups the overall levels appear to be relatively constant, apart from a shift towards endovascular treatment, with an older population having greater comorbidity. However, it is difficult to know whether the trend towards higher comorbidity is real or the result of an increasing depth of coding in recent years, possibly related to the introduction of HRG groupings that provide higher tariff rates for patients with additional comorbidities.

In the treatment of VV, there was a considerable reduction in the number of procedures carried out around 2011/12, but this has now gradually returned to the original rate.

There is considerable variation in practice, which is particularly notable with the adoption of new technologies. In the case of aneurysm repair, the proportion of patients treated by EVAR varies between providers from 30% to > 90%. There is also considerable variation in the proportion of AAA cases classified as complex in the use of endovascular treatments for PAD and of endovenous treatments (EVLT and RFA) for VV.

There are also marked variations in practice with regard to the use of inpatient or outpatient investigations, with some providers appearing to carry out large numbers of investigations, including duplex ultrasound as day-case admissions, whereas others appear to carry out investigations as outpatient procedures. This has considerable implications for the difference in income that may be generated from treating similar conditions.

There are a number of potential areas for further research regarding HES data, which were not within the remit of this programme. Further work is needed to identify the extent to which differences in workload and cost represent differences in coding or reflect clinical practice. There may be a potential for better classification algorithms, possibly through the use of machine-learning techniques, and linkage of HES data to other sources with richer clinical information may allow better algorithms to be developed for classification of case-mix.

The methods of classification of HES data do, however, provide a useful basis for comparison between centres and over time. This is explored further in the modelling in Modelling the effects of service reconfiguration.

Changes in working arrangements

Results

Abdominal aortic aneurysm

The trend in the number of sites offering AAA surgery is shown in Figure 9. The overall number of sites offering aneurysm repair fell from 136 to 69 between 2006/7 and 2017/18. The majority of the reduction was due to the cessation of aortic aneurysm surgery at those sites carrying out < 40 cases per year.

FIGURE 9.

Number of sites undertaking aortic surgery by total number of AAA cases per year, based on HES data.

Considering the overall number of cases treated at sites with different volumes of activity, there was a reduction in the proportion of patients treated at sites with low volumes until approximately 2011. Since then, the figures have remained fairly stable, with approximately 20% of procedures carried out at sites that carry out < 60 cases per year (Figure 10).

FIGURE 10.

Proportion of AAA admissions by total number of AAA cases per year at treating site.

The NVR reported that the number of centres carrying out > 30 elective cases per year of infrarenal elective AAA repair had reduced to 11, compared with 58 centres carrying out more than this number. 3 For comparison, the HES data suggested that there were 12 centres in this category out of the same total of 69. This definition of activity category differs from that reported in the specification for the provision of vascular services,171 which suggests that the minimum number of cases for a designated aortic aneurysm centre should be 60 cases per year of all types of aneurysm repair, averaged over 3 years. By this criterion, the HES data suggest that 40 out of the 69 centres were compliant with current advice.

Peripheral arterial disease

Many admissions for PAD appear to have been centralised, along with the centralisation of aneurysm services, over the past 12 years (Figure 11). Those centres that have a sustained aneurysm practice undertook 96.9% of all surgical arterial reconstructions in 2017/18, compared with under 60% in 2006/7. Most other procedures have followed a similar trend, although about one-third of minor amputations are carried out at non-vascular centres.

FIGURE 11.

Trends in the proportion of categories of PAD admissions treated at sites with a current AAA practice.

Carotid artery disease

The most recent NVR data show that 65 English trusts carry out carotid surgery, of which 23 have activity levels below the recommendation of 40 per year. In comparison, HES data analysis for the most recent year shows 74 sites, of which 26 are below the threshold. As expected, the AAA volume correlates with CAD volume, but there are a small number of sites carrying out CAD but not AAA procedures or vice versa (Figure 12).

FIGURE 12.

Number of CAD and AAA procedures for sites undertaking vascular procedures in 2017/18, compared with VSGBI recommendations. 171

Approximately 16% of CAD procedures are carried out at sites with volumes below the recommended volume, and the postoperative mortality at these sites is significantly higher than at sites that reach the recommended volume (Table 8).

TABLE 8 - Number of CAD procedures and mortality by site: annual volume of procedures 2015/16 to 2017/18

CI, confidence interval.

CAD procedures	CAD annual volume
	Under 40	40 and over	Overall
Number of cases	2174	11,525	13,699
Mortality, % (95% CI)	2.9 (2.2 to 3.6)	1.6 (1.4 to 1.9)	1.8 (1.6 to 2.1)

Varicose veins

Although VV procedures are not included in the NVR reports, they constitute a significant workload for vascular clinicians and the reconfiguration of vascular services may affect the place or method of treatment. Between 2006/7 and 2012/13 there was a substantial reduction in the overall number of admissions related to VV procedures and an increase in the proportion treated by endovascular methods (EVLT and RFA) and at vascular centres (Figure 13). Table 9 provides details of the features of VV admissions based on the method of treatment and proportion treated at current vascular sites (those with a current AAA practice).

FIGURE 13.

Trends in the number of VV admissions treated by open and endovenous procedures at sites with and without a current AAA practice.

TABLE 9 - Trends in the site and mode of treatment of varicose veins

Year	Non-vascular sites			Vascular sites			Proportion at vascular site (%)
	Number	EVLT (%)	RFA (%)	Number	EVLT (%)	RFA (%)
2006/7	18,309	5.6	0.3	15,649	6.6	0.1	46.1
2007/8	16,670	11.7	1.2	17,048	12.1	1.6	50.6
2008/9	16,091	16.8	5.1	17,171	14.2	4.7	51.6
2009/10	15,390	18.2	14.2	17,146	18.3	10.7	52.7
2010/11	14,334	16.3	18.5	15,849	21.1	14.9	52.5
2011/12	11,586	15.8	20.8	13,126	20.9	20.2	53.1
2012/13	10,127	16.2	24.7	11,741	24.3	21.4	53.7
2013/14	10,731	16.0	31.6	12,614	25.5	25.1	54.0
2014/15	12,843	14.7	41.9	16,219	24.7	30.9	55.8
2015/16	12,047	15.7	47.0	17,481	23.7	33.2	59.2
2016/17	11,354	17.4	51.0	17,090	23.4	35.9	60.1
2017/18	10,341	14.5	55.9	15,578	21.3	40.6	60.1

Discussion

To understand the current arrangements for the provision of vascular services and the way that these may be affected by any future reconfiguration, a detailed analysis was carried out of the current sites at which vascular services are delivered. This was compared with data from an organisational audit carried out by VSGBI and the data on activity from the NVR. These sources of data provide rich information, but each has limitations and drawbacks. The organisational audit relies on voluntary submission of data. The NVR is a procedure-based registry that does not link to long-term re-admission and outcome data, whereas the HES data have the limitations described in the previous section relating to the coding systems and accuracy. There is, however, reasonable agreement between the sets of data in most respects.

The main findings with regard to the configuration of vascular services are that there has been a move towards centralisation of complex arterial cases, including AAA, CAD and major vascular reconstructions. As a result of the centralisation of AAA services, the number of sites at which aneurysm surgery is carried out has halved in the last 10 years. However, despite this, over the most recent 5-year period approximately 20% of aneurysm repairs are still carried out at centres with an annual volume below the 60 cases recommended in the provision of vascular services document. 171 Consideration of the distances between centres that have already amalgamated their aneurysm service and those that continue to carry out small numbers suggests that, with few exceptions, the geographical distances are not a major barrier to further centralisation.

There has been much discussion of hub-and-spoke arrangements, with various documents providing advice regarding such arrangements. 172 The organisational survey regarding such arrangements is limited in the detail that it provides. One issue in this respect is that the survey is carried out on the basis of providers, and a single provider may deliver vascular services at multiple sites. The HES data suggest that, where aneurysm services have been consolidated on a single site, many other aspects of the vascular service have followed suit, resulting in centralisation of many services rather than a hub-and-spoke arrangement. The HES data relate to inpatient activity only, so there may be hub-and-spoke arrangements with regard to outpatient clinics. However, the number of services that appear to offer day-case investigations, minor procedures or rehabilitation following amputation at satellite units appears to be limited.

Even in the case of VV surgery, which is largely carried out as a day-case procedure, there appears to be a significant degree of centralisation, with the VV activity following other major vascular services.

These results suggest that further research may be useful in identifying the drivers for and barriers to service reconfiguration and particularly to the provision of hub-and-spoke arrangements that may allow the local delivery of those aspects of patient care that can safely and appropriately be delivered at spoke sites.

Comparison between the activity and the outcomes reported from NVR and HES data suggest a number of issues that may be worthy of further investigation. The mortality estimates from NVR appear to be consistently lower than those obtained from the HES data, and there are a number of possible explanations for this. Although NVR would appear to have quite high acquisition rates, if the returns are selectively omitting cases in which there was mortality, this may result in underestimation of the mortality rate. This may occur because notes may be unavailable following deaths, so records remain incomplete, or because patients may be recorded as having survived a procedure when they have been transferred to another unit, even though they subsequently die without leaving hospital.

Another possible cause of distortion is that patients who are turned down for emergency surgery may not be recorded in the NVR. The patients identified in HES as having died with a primary diagnosis of aortic aneurysm include some such patients, although some of these underwent procedures, such as laparotomy, and, thus, should be included in the NVR data.

Another discrepancy between the HES data and the NVR relates to complex aortic aneurysm repair. Both NVR and HES suggest that there was a substantial increase in the number of EVAR procedures carried out for complex AAA, including branched and fenestrated endovascular grafts. However, the number identifiedas such in NVR is larger than the number with the relevant codes in HES data. It is not possible to distinguish between patients undergoing these complex procedures who would previously have undergone infrarenal open or endovascular procedures and patients who would not previously have been considered suitable for treatment. The distribution of such cases is uneven, with a small number of centres carrying out a higher proportion of these procedures. Considering the declining total number of AAA procedures and the absence of evidence of a large number of tertiary referrals, it seems more likely that this represents a different method of treatment of existing patients rather than a previously untreated population.

Further research may be justified to understand the appropriate place of such treatments, particularly in the light of the recent draft National Institute for Health and Care Excellence (NICE) guidance. 173

Conclusions

The detailed analysis of HES underpins the modelling that is described in Modelling the effects of service reconfiguration. The key findings in relation to service configuration are that, despite considerable centralisation of major procedures, there are still several centres that do not meet recommendations regarding activity levels and that, in most cases, this does not appear to relate to geographical limitations. Furthermore, the centralisation has been accompanied by significant changes in practice, particularly in relation to the implementation of less invasive treatments. Considerable variation in practice has been identified, some of which correlates with the degree of service centralisation. An additional finding has been the trend for centralisation of investigations and minor procedures, along with the emergency and major vascular workload.

Methods

Results

Substudy: EuroQol-5 Dimensions, five-level version, utility values

The average EQ-5D-5L derived utility values ranged from 0.396 for PAD patients with a major amputation to 0.886 for VV patients following treatment (Table 13).

Discussion

This section documents the steps undertaken to develop the ePAQ-VAS, a new tool to collect PROMs and other clinical information from users of vascular services. This can be used as a holistic clinical assessment tool to be completed by patients before seeing a clinician and during follow-up. The information generated can be used to help shared decision-making and to monitor the impact of intervention on the patients’ quality of life. As an electronic online measure it can potentially be completed remotely, which facilitates virtual clinics,192 and may contribute to electronic patient records or aggregated data for service evaluation. A demonstration version of the final version of the web-based form is available online at www.epaq.co.uk/Demo/VascularDemo (accessed 1 December 2020).

A major strength of the work is that the instrument has been developed through a rigorous process in line with FDA guidelines for developing PROMs. 176 Evidence from this study suggests that scales in the lower limb section of the ePAQ-VAS have good test–retest reliability, particularly the PAD and VLU scales. The results of the known group validity show that the AAA-related anxiety scale correlates with the size of AAA. Patients’ anxiety is increased and the impact that the disease has on patients’ daily living is greater for preoperative patients than for those under surveillance. The instrument shows good correlation between rest pain in PAD and increased PAD impact on ADL scores. The results of the survey also confirmed that the presence of an ulcer with PAD diagnosis increased PAD impact on ADL scores, and recurrent ulcer is associated with an increase in ulcer symptom scores. The results of the responsiveness analyses show that the following scales can detect changes following intervention: AAA-related anxiety, PAD symptoms, impact of PAD on ADL, VV symptoms scale and impact of VVs on ADL.

Another strength of the work is the inclusion of the EQ-5D-5L alongside disease-specific scales. This allows the generation of utility values for the different health states that can be used in cost-effectiveness modelling, in line with NICE’s methodology. 193 It may also facilitate further research to consider the relationship between such generic measures and the more detailed symptomatic and disease-specific description of vascular conditions provided by the new instrument.

These studies had a number of limitations. For pragmatic reasons, the development and validation were largely based on evaluation at a single site. Sample size was small for some groups of patients, because of resources and patient availability, particularly for patients with CAD and AAA. Access to some patient groups before and after treatment was difficult and the fact that some forms were completed online, some in outpatient clinics and some by telephone may have been a confounding factor. Furthermore, the sample size for responsiveness and test–retest was small for all groups, and future analysis with a larger sample size is desirable. The follow-up data for test–retest and responsiveness were collected by telephone, which may have introduced some bias. Further studies are also required to explore acceptability and completion rates, to consider the practicalities of wider implementation and to refine aspects of the process, such as reporting formats and the analysis of longitudinal and aggregate data.

Overall, the ePAQ-VAS provides a holistic data collection process that is relevant to most vascular service users and has the potential to contribute to patient-focused care and the collection of aggregate data for service evaluation.

Trade-off study

The reorganisation of vascular services will have an impact not only in terms of health outcomes, but also with respect to other aspects of service provision, such as travel distances and treatment processes. The aim of the proposed research was to elicit preferences from members of the public for the way in which vascular services could be organised in the NHS. Following qualitative work with vascular patients, travel distance to health facilities was identified as an extremely important factor in any reorganisation. Further work with vascular clinicians revealed a desire to elicit preferences for alternative treatment processes for AAA, as treatment of AAA is the principal driving force behind any potential reorganisation. The specific aims of the study, therefore, were to elicit preferences for (1) the treatment processes associated with EVAR and open surgical repair of AAA and (2) having to travel to specialist hospitals for treatment and follow-up for AAA, CAD and PAD. 194

Method

The method involved surveying members of the UK population, through individual telephone interviews, to elicit their preferences for treatment processes for AAA and travel distance to specialist hospitals. At the heart of the method is the notion of opportunity cost and how this relates to value. Fundamentally, something is of value to an individual only if they are willing to give up (or sacrifice) something to acquire what is being valued. Without sacrifice, there is no value. What respondents were asked to sacrifice to have their preferred treatment option or preferred hospital was small changes in the chance of treatment being successful. From their responses it was possible to quantify their strength of preference in terms of a QALY equivalent that allows those preferences to be incorporated into the cost-effectiveness models. Interview booklets for the three groups are provided in Appendices 3–5.

Results

Discussion

Our results comparing EVAR with open surgery for AAA repair suggest a clear preference for EVAR in the sample. This suggests that patient preferences may be in conflict with the recent recommendation by NICE195 that EVAR should not be recommended as the first-line treatment option for most people with this condition. These findings suggest that greater consideration should be given to the value that is placed on the treatment processes of EVAR and OR. If NICE were to find a mechanism to explicitly incorporate such preferences in the decision-making process, it may increase the likelihood that recommended treatment pathways align with the preferences of the UK population. 173

Our results valuing the burden of travelling for treatment and follow-up clearly indicate that it is a potentially important component of disutility in the sample for each of the three clinical areas considered. As such, it is suggested that there is a need take this disutility into account when considering the implications of any decision to reorganise vascular services to a more centralised provision. To that end, the impact on cost-effectiveness of including the values placed on the disutility of travelling has been investigated in Modelling the effects of service reconfiguration.

Summary

This section reports the evaluation of the cost and quality implications of different possible service configurations for subspecialist vascular services. A number of techniques were used, including HES data analysis, regression modelling, systematic literature review, preference elicitation, decision analysis and modelling. Costs are reported in Great British pounds at year 2017/18 prices. The NHS and Personal Social Services (PSS) perspective was adopted for the economic evaluation. Costs and outcomes are discounted at 3.5% per year. Statistical analyses and simulation were performed in R version 3.4.3.

The modelling was carried out in two parts. First, three separate models covering the clinical areas of AAA, PAD and CAD were developed. These models of individual disease areas were then brought together in an interactive web-based model that enables users to identify potential reconfiguration of services in particular geographical areas and to predict the overall effects of potential service reconfiguration in terms of workload, resource use, outcomes and cost-effectiveness.

Results at the cohort level are reported for each vascular group (AAA, CAD and PAD) separately and for the cohort as a whole. The incremental cost per QALY is reported for the combined cohort as a whole to indicate how cost-effective the new configuration is compared with the baseline configuration. The model estimates the specific results for each vascular site, before and after the reconfiguration. Scenario analysis and one-way sensitivity analysis were conducted to see how the results were affected by the model’s structure and key parameters. To assess the impact of parameter uncertainty on the model’s results, 2000 Monte Carlo simulations of the model were run in a probabilistic sensitivity analysis (PSA). Each PSA simulation ran the model with a sample of inputs for stochastic parameters.

General overview

The conceptual modelling framework was based on clinical consensus representing the pathways of care, characterised through the analysis of HES. The aim of the model is to predict the changes in workloads, distance from patients’ homes to hospitals, hospital costs and outcomes when vascular services are reconfigured (i.e. merging small centres into larger centres). Our model was a patient-level simulation. We chose a patient-level modelling approach to better utilise patient-level data from HES and to accommodate the complexity of the decision problem, capturing both patient-level information and hospital-level information. Our simulation used discrete time-to-event rather than time cycles in modelling. This reduced unnecessary computer time in running the model. System dynamics was not suitable for our modelling problem. The microsimulation models were populated with data from regression analysis of HES records, systematic literature reviews and preference information.

Service reconfiguration

Conceptual model

The model aims to predict the changes in workloads, distance from patients’ homes to hospitals, hospital costs and outcomes when vascular services are reconfigured (i.e. merging small centres into larger centres). The model structure is similar across the three main vascular groups: AAA, CAD and PAD (Figure 14).

FIGURE 14.

The model structure. TIA, transient ischaemic attack.

Modelling

Abdominal aortic aneurysm model

Peripheral arterial disease model

Carotid artery disease model

Combined model of service configuration

The three patient-level simulation models for the vascular groups AAA, CAD and PAD were combined to develop an overall model. This model predicts the changes in workloads, distance from patients’ homes to hospitals, hospital costs and outcomes when vascular services are reconfigured (i.e. merging small centres to form larger centres) taking the three main vascular groups into account. The simulation has an interactive user interface (UI) and is deployed as a web-based application that can be accessed online at https://modellers.sheffield.ac.uk/vascularmodel/ (accessed 1 December 2020).

The user interface (UI) allows the users to specify a particular service configuration (a list of available vascular centres) that they want to be modelled and evaluated. It also allows the users to specify the type of analysis (deterministic or probabilistic sensitivity analysis), number of sample iterations and changes in inputs, such as one-off cost of the reconfiguration, probability of switching from OR to EVAR and per cent increase (or decrease) in no-operation deaths owing to the reconfiguration. Figure 15 illustrates these features of the UI.

FIGURE 15.

Example of the specification component of the UI.

The decision problem

The NHS England service specification for vascular services170 and the VSGBI171 currently recommend an AAA volume threshold of 60 cases per year. 171 This was used to define the decision problem at the national level for service configuration: is it cost-effective to reconfigure the current landscape of vascular services in England to achieve this threshold? The baseline option is then the current configuration of services in 2017/18 (the latest year of the data) and the intervention option is a new configuration of services, so that the minimum AAA volume of each vascular centre is 60.

To identify the current configuration of services in 2017/18, the total number of AAA repairs was summarised for each vascular site in the data. Sites carrying out fewer than five AA repairs per annum were considered non-vascular and were excluded. To identify the new configuration of services that satisfies the AAA volume threshold of 60 cases per year for all vascular sites, an iterative process is adopted. First, the vascular site with the minimum volume from the current configuration was identified. Second, this site was excluded from the current configuration and its patients re-allocated to their nearest available sites. Third, the AAA volume for each site was recalculated and the revised values became the current configuration (i.e. excluding the site with minimum volume). Step 1 was repeated until a configuration with no site having a volume fewer than 60 cases per year was identified.

This method identified a baseline configuration of services that included 72 active vascular sites in England in 2017/18 and a new configuration that met a minimum volume threshold of 60 AAA cases per year at all sites. In this new configuration major vascular surgery was transferred from 23 vascular centres with low volume to those with higher volumes; the final arrangement included only 49 active centres. Figure 16 illustrates the AAA volume distribution in the baseline configuration and in the new configuration and Table 17 describes the changes in each region.

FIGURE 16.

Abdominal aortic aneurysm volume distribution at baseline and the new configuration.

Base-case deterministic results

Table 18 shows the results of the deterministic model for AAA patients. The reconfiguration reduced in-hospital death (–0.75%), but it had a negative impact on the long-term survival of those who survived the index repairs, which lead to a decrease in the total number of QALYs (–0.056 reduction in discounted QALYs gained per patient). This is consistent with what was observed in the HES data. The reconfiguration increased the costs of index admission (£706 per patient) and the total lifetime costs (including other costs) (£728 per patient).

TABLE 18 - Deterministic base-case results for AAA

Results	Baseline	New configuration	Incremental
Number of patients	7393	7393	0
AAA volume per site	92	135	43
Mean age (years)	74.4	74.4	0.0
Male (%)	82	82	0
Length of stay (days)	10.33	10.35	0.02
Hospital death (%)	20.49	19.74	–0.75
Life-years (undiscounted)	12.524	12.330	–0.194
QALYs (undiscounted)	9.770	9.621	–0.149
Life-years (discounted)	9.095	9.020	–0.075
QALYs (discounted)	7.068	7.011	–0.056
Costs of index admission (£)	17,021	17,727	706
Total costs (undiscounted) (£)	19,069	19,787	718
Total costs (discounted) (£)	18,614	19,343	728

Table 19 shows the results of the deterministic model for CAD patients. The reconfiguration reduced in-hospital death (–0.1%) and had a positive impact on long-term survival and stroke-related re-admission-free survival of those who survived the index repairs, leading to an increase in the total number of QALYs (0.078 additional discounted QALYs gained per patient) and an increase in the number of stroke-free days (98 days per patient). The reconfiguration increased the costs of index admission (£103 per patient) but saved resources on other longer-term costs (because there were fewer stroke-related re-admissions). Overall, this led to an increase in the total costs (£79 undiscounted and £101 discounted per patient).

TABLE 19 - Deterministic base-case results for CAD

Results	Baseline	New configuration	Incremental
Number of patients	5024	5024	0
Mean age (years)	70.5	70.5	0.0
Male (%)	66	66	0
Length of stay (days)	5.1	5.0	–0.1
Hospital death (%)	1.04	0.94	–0.11
Stroke-free days	7274	7372	98
Life-years (undiscounted)	20.480	20.696	0.216
QALYs (undiscounted)	15.585	15.760	0.175
Life-years (discounted)	13.299	13.395	0.096
QALYs (discounted)	10.139	10.217	0.078
Costs of index admission (£)	8991	9094	103
Total costs (undiscounted) (£)	19,448	19,527	79
Total costs (discounted) (£)	15,507	15,607	101

Table 20 shows the results of the deterministic model for PAD patients. The reconfiguration reduced in-hospital death (–0.12%) and had a positive impact on long-term survival and AFS of those who survived the index repair, leading to an increase in the total number of QALYs (0.035 additional discounted QALYs gained per patient) and an increase in the number of amputation-free days (60 days). The reconfiguration increased the costs of the index admission (£832 per patient) but saved resources on other longer-term costs (because there were fewer amputation-related re-admissions). This led to a reduction in the total costs (–£916 undiscounted and –£15 discounted per patient).

TABLE 20 - Deterministic base-case results for PAD

Results	Baseline	New configuration	Incremental
Number of patients	22,295	22,295	0
Mean age (years)	69	69	0
Male (%)	64	64	0
Length of stay (days)	8.7	9.1	0.4
Hospital death (%)	3.64	3.52	–0.12
Major amputation in index (%)	2.53	2.48	–0.04
Amputation-free days	5854.4	5914.8	60.4
Life-years (undiscounted)	17.277	17.380	0.103
QALYs (undiscounted)	9.861	9.939	0.078
Life-years (discounted)	11.256	11.306	0.050
QALYs (discounted)	6.369	6.404	0.035
Costs of index admission (£)	9436	10,268	832
Total costs (undiscounted) (£)	93,398	92,482	–916
Total costs (discounted) (£)	58,782	58,767	–15

Table 21 shows the results of the deterministic model when the whole combined cohort of AAA, PAD and CAD patients was considered. The reconfiguration reduced in-hospital death (–0.25%) and had a positive impact on long-term survival of those who survived the index admission, leading to an increase in the total number of QALYs (0.022 additional discounted QALYs gained per patient). The reconfiguration increased the costs of index admission (£700 per patient) but saved resources on other longer-term costs. This led to a reduction in the total costs when discounting was not included (–£424 per patient) but an increase in the total costs when discounting was included (£160 per patient).

TABLE 21 - Deterministic base case results for combined cohort (60 threshold reconfiguration vs. baseline)

Results	Baseline	New configuration	Incremental
Number of patients	34,712	34,712	0
Mean age (years)	70	70	0
Male (%)	68	68	0
Length of stay (days)	8.5	8.8	0.3
Hospital death (%)	6.85	6.60	–0.25
Travel distance (miles)	8.5	10.3	1.8
Life-years (undiscounted)	16.728	16.784	0.056
QALYs (undiscounted)	10.670	10.714	0.044
Life-years (discounted)	11.092	11.122	0.030
QALYs (discounted)	7.0631	7.0851	0.0219
Costs of index admission (£)	10,987	11,687	700
Total costs (undiscounted) (£)	66,864	66,440	–424
Total costs (discounted) (£)	43,964	44,124	160
Incremental costs per QALYs (£)			7312.90

The new configuration was associated with an incremental cost per QALY of £7313. This is well below the NICE cost-effectiveness threshold of £20,000 per QALY (λ). The net monetary benefit (NMB) of the reconfiguration of vascular services was £278 per patient at the £20,000 per QALY threshold (NMB = λ × incremental QALYs – incremental costs). Given the population size (34,712 patients), the population NMB was £9,644,639.

Deterministic sensitivity analysis results

Table 22 shows the results from the scenario analysis (see Methods).

TABLE 22 - Scenario analysis results

ICER, incremental cost-effectiveness ratio.

Scenario:

0, base case; 1, 50% of AAA OR would be switched to EVAR after reconfiguration; 2, 1% of AAA repair cases would be switched to no-operation deaths after reconfiguration; 3, 1% of AAA no-operation deaths would be switched to repair cases after reconfiguration; 4, using 6% discounting rate instead of 3.5% in the base case; 5, setting all stochastic parameters (from literature review) at their lower CI values; 6, setting all stochastic parameters (from literature review) at their higher CI values; and 7, removing volume effect from all long-term outcomes of survivors of index admissions.

Scenario	AAA		CAD		PAD		All		ICER
	Incremental cost (£)	Incremental QALYs	Incremental cost (£)	Incremental QALYs	Incremental cost (£)	Incremental QALYs	Incremental cost (£)	Incremental QALYs
0	728	–0.056	101	0.078	–15	0.035	160	0.022	7313
1	722	–0.071	101	0.078	–15	0.035	159	0.019	8448
2	625	–0.120	96	0.075	–14	0.034	138	0.007	19,161
3	2125	0.685	147	0.110	13	0.050	482	0.194	2488
4	731	–0.027	106	0.050	248	0.023	330	0.017	19,891
5	724	–0.053	101	0.075	95	0.034	230	0.021	10,779
6	733	–0.060	100	0.081	–124	0.037	91	0.023	4014
7	721	0.059	111	0.011	875	0.003	732	0.016	45,177

Figure 17 shows the results from the one-way sensitivity analysis (see Methods).

FIGURE 17.

Results from the one-way sensitivity analysis. LCI, lower 95% CI; OWSA, one-way sensitivity analysis; UCI, upper 95% CI.

The parameters with the utilities and monthly long-term costs of PAD cases were the most influential on the results, although none of them was sufficient to increase the incremental cost-effectiveness ratio (ICER) to above £20,000 per QALY.

Probabilistic sensitivity analysis results

Figure 18 shows the PSA results for incremental QALYs and incremental cost of the vascular service reconfiguration on a cost-effectiveness plane.

FIGURE 18.

The PSA results on a cost-effectiveness plane.

The values of the ICER of the service reconfiguration in PSA crossed into two different quadrants on the cost-effectiveness plane: 0.25% on the south-east (SE) quadrant (dominant – less expensive and more effective) and 0.25% on the north-west (NW) quadrant (dominated – more expensive and less effective). The probabilistic mean ICER was £7169 per QALY (compared with £7313 per QALY in the deterministic results).

Figure 19 shows the cost-effectiveness acceptability curve together with the cost-effectiveness acceptability frontier. At the threshold of £20,000 per QALY, the probability of the service reconfiguration being cost-effective was 96%.

FIGURE 19.

Cost-effectiveness acceptability curve and frontier.

Figure 20 presents the change in individual expected value of perfect information across different values of the cost-effectiveness threshold.

FIGURE 20.

Individual patient-expected value of perfect information.

The data analysed in Vascular activity and outcomes from routine data suggests that further improvements in outcome may be achieved by increasing the threshold of activity for AAA to 100 cases per year, rather than the 60 cases considered in this analysis. A further exploratory analysis was, therefore, carried out to consider the implications of a higher threshold (see Report Supplementary Material 16).

Discussion and conclusion

This study is the first model-based economic evaluation study evaluating the cost-effectiveness of a national strategy to reconfigure the vascular services in England. The decision problem concerns the merging of vascular centres with a low annual AAA repair volume and centres with higher volume so that all active vascular centres would have an annual AAA repair volume of at least 60 cases, as recommended by NHS England170 and VSGBI. 171 Using HES data between 2008/9 and 2017/18, the current baseline configuration of services in 2017/18 (72 active vascular centres) was identified. A re-allocation algorithm identified the new service configuration that satisfied the volume threshold; this reconfiguration required transfer of major vascular surgery from 23 vascular centres with low volume to the remaining 49 active centres in the new configuration. The two configurations (baseline and new) were assessed by a patient-level cost-effectiveness simulation that simulated the pathways, costs and outcomes of three patient groups: patients with AAA, CAD and PAD.

The deterministic results suggest that this reconfiguration of vascular services is cost-effective based on the NICE cost-effectiveness threshold of £20,000 per QALY. The incremental cost per QALY (ICER) for the reconfiguration was £7313. This was translated to a NMB of the reconfiguration of vascular services of £278 per patient and £9,644,639 for the whole population at the £20,000 per QALY threshold.

However, the cost-effectiveness results were sensitive to the following assumptions in the model: (1) the assumption about the impact that reconfiguration would have on the proportion of AAA no-operation deaths; (2) the discount rate used in the model; and (3) the assumption about the volume effect on long-term outcomes (i.e. survival) of survivors of the index admissions (see Deterministic sensitivity analysis results). One-way sensitivity analysis on the model parameters on utilities and other costs informed by the literature shows that, varying these parameters, one at a time between their lower confidence interval (CI) value and upper CI value did not cause the cost-effectiveness to exceed £20,000 per QALY. The PSA estimated the mean ICER at £7169 per QALY.

The main strength of the study is that it was based on a patient-level cost-effectiveness simulation that utilised 12 years of HES data between 2006/7 and 2017/18. The richness of information from HES data enabled us to develop a simulation describing all main vascular activities (AAA, PAD and CAD) at three levels: (1) the individual patient level; (2) the hospital level, at which patients are treated; and (3) the regional level, at which patients live. The model was verified and validated with the actual observations in HES data and expert opinions from vascular clinicians. The model’s results were tested extensively in scenario analyses and one-way sensitivity analysis, and the uncertainty with the model’s parameters was quantified in a PSA.

However, there are limitations with the study. First, there are challenges with processing and analysing HES data that include defining the outcome measures and predictors; identifying comorbidities; and various aspects concerning the statistical methods for model development (modelling framework, model fitting, assessment of model performance, recalibration, handling competing risks in survival models, estimating hospital resources used, etc.). 204

Facing the challenges raised by data quality, changes in coding across the years and past service reconfigurations required subjective choice and judgement in the analytical decisions. Such challenges were addressed throughout the modelling process in group discussions combining the clinical and clinical coding, statistical and modelling expertise of the group.

The results of the analyses on the relationship between volume and in-hospital outcomes for AAA patients generally agreed with previous volume–outcome studies;52 however, the results on the relationship between volume and long-term outcomes for those AAA patients who survived and were discharged from the index admissions did not agree with a previous study. 52 Patients discharged from centres with higher AAA volumes had worse long-term survival (even after case-mix adjustment), whereas Holt et al. 54 found the reverse relationship. It should be noted that Holt et al. 54 used HES data between 1 April 2000 and 31 March 2005 (before the specific procedure codes for EVAR were introduced in HES), whereas this analysis used HES data between 1 April 2006 and 31 March 2018 and several aspects of the methods attempted to address the limitations of the methods of Holt et al. 54 In this respect, it is of note that the HES data showed an association between higher volume and higher rates of EVAR, and the recent modelling for the NICE guideline196 on AAA suggested that EVAR is dominated by OR, being both more costly and less effective in the long term. This could potentially explain the apparently poorer long-term outcomes associated with higher-volume sites.

Second, our approach in HES data analysis was relatively simplistic and pragmatic owing to time and resource constraints. Not all possible alternative approaches were tested in developing the risk predictive models, such as machine-learning methods or more advanced multistate survival analysis.

The outpatient data set and the accident and emergency data set in the HES analyses were not used, owing to time and resource constraints. These data sets could improve our estimates of resources used and costs of vascular repairs and, thus, would improve our predictive models in the cost-effectiveness simulation.

Third, data for utilities and other long-term costs used in the model were sought from a rapid systematic review of the literature. Values for these parameters came mainly from three UK HTA reports for AAA, PAD and CAD. It could be argued that a more comprehensive review and data extraction could have been carried out to improve the estimates for these parameters. Nevertheless, the impact of changing these values between their lower and upper CI levels was tested in a one-way sensitivity analysis and it was found that doing so did not significantly change the cost-effectiveness results. Furthermore, the uncertainty with the model’s parameters was assessed in our PSA.

Fourth, our model is based on a fundamental assumption that the associations identified in the regression models reflect direct or indirect causal relationships. The model does not account for many complex influential factors, such as capacity constraints, linked hospital services, the experience of individual vascular surgeons and local factors (e.g. transport links) that may influence real-world choice and the undoubted complex disruptions associated with organisational change. Furthermore, the method of sequentially redistributing workload from the lowest-volume site may not achieve an ideal or optimal configuration, as there may be advantages in transferring services from several sites to one central location. Another issue is the overall selection of procedures carried out at different sites. For example, with appropriate collaboration many minor procedures, investigations and rehabilitation services may be provided at sites different from those carrying out major vascular procedures.

This point may be particularly relevant in the light of the findings of the preference work described in Evaluation of non-health outcomes, which suggests that the strength of preference for local services, when considered in terms of the QALYs that would be traded is high when compared with the average per-patient benefit of the effects of reconfiguration.

The overall economic benefit of reconfiguration is small and uncertain and, furthermore, is not consistent across the three vascular conditions considered: AAA, CAD and PAD. The primary economic benefit from reconfiguration arises from improved CAD outcomes and improved costs and outcomes associated with amputations in PAD. There appears to be a complex trade-off between short- and long-term outcomes in EVAR and OR in AAA that may indicate a potential for further economic gains from reconfiguration that is worthy of further research.

Another limitation of the study is that the modelling was confined to an analysis of the effects on the inpatient aspects of the three main diagnostic areas of AAA, CAD and PAD. Although these represent the majority of workload that may be expected to transfer with the reconfiguration of vascular services, vascular specialists provide services, such as VV surgery, outpatient clinics, joint diabetic foot services and, in some areas, vascular access. It is not necessary that such services are co-located with major vascular inpatient services, and there exist various arrangements through which some of these may be provided in ‘non-vascular’ centres or community settings. However, the evidence in Vascular activity and outcomes from routine data suggests that centralisation of vascular services may be accompanied by changes in practice and relocation of some services. As the arrangements for such services may vary depending on geography and local facilities, application of the model to a specific local reconfiguration would require separate consideration of the intended working arrangements in these respects.

The model provides estimates of the emergency and elective workload, bed requirements and resource use that will support the planning of reconfiguration. However, specific recommendations regarding workforce, bed numbers and facilities in any planned reconfiguration would also require additional local adaptation to account for intended arrangements regarding any ‘non-mandatory’ changes in configuration, such as the location of investigative, minor procedure, rehabilitation and outpatient provision.

Overview of programme outcomes

The vascular research programme has resulted in the development of two major products: an electronic web-based tool for the collection of PROMs and other clinical data (the ePAQ-VAS), and a tool for the computer simulation of potential service reconfiguration, which can be used to estimate the effects on workload, resource use, outcomes and cost-effectiveness of potential service reconfiguration. In the process of developing these, there have been a number of other outputs from the programme, including publications and analyses. These provided evidence regarding a variety of outcome measures of relevance to vascular services, estimates of utility associated with vascular-related health states, the details of patient preferences for aspects of service provision and the development of methods for the analysis of workload and outcome from routine data.

The electronic Personal Assessment Questionnaire – Vascular

The ePAQ-VAS is a web-based tool for the collection of PROMs and clinical information of relevance to patients using vascular services. It can be completed by patients from home using a web interface, with secure access being provided through a personalised voucher code that can be distributed with an appointment letter or by other means. It may also be completed by patients at the time of outpatient appointments using a tablet or computer workstation. The form is divided into a number of sections relating to generic information and specific sections relating to aneurysm, leg symptoms or CAD. Relevant sections may be completed or skipped depending on the nature of the condition that is being addressed. The form is designed to collect data of clinical relevance but also to produce outcome estimates including the generic EQ-5D and specific domains related to clinical conditions. These can be used to monitor individual patient progress or for overall service evaluation. The reliability and validity of the tool have been established through extensive psychometric evaluation. A demonstration version of the final version of the form is available online at www.epaq.co.uk/Demo/VascularDemo (accessed 1 December 2020).

The vascular services simulation model

A computerised simulation model has been developed with a web-based interface that allows the modelling of potential reconfiguration of the sites providing vascular services in England. The web-based interface allows users to select specific regions and combinations of hospital sites and allows the selection of various parameters for sensitivity analysis. By selecting different sites for a comparison, the effects of reconfiguration of services can be modelled, providing estimates of the overall cost-effectiveness of a reconfiguration along with calculated estimates of the workload in the different categories and resource use required.

Other outcomes

In addition to these two main products, the programme has generated evidence and research outputs from a number of other aspects of the studies. Several papers describe extensive reviews of the evidence relating to outcome measures for different aspects of vascular disease,17–24 the available evidence relating to patient preferences,194 and to the relationship between service configuration and outcomes. 11,13–15

The societal preference studies provide estimates of the strength of preference for EVAR compared with OR and for the strength of preference relating to travelling distance for access to vascular services.

The algorithms developed for the analysis of HES data provide a basis for consistent evaluation of case-mix and outcomes from this complex routine data set.

In addition to the main web-based model, the modelling has provided a detailed analysis of the relationship between activity outcomes and resource use.

Utility values for health states related to conditions dealt with by vascular services have been obtained from two sources: a detailed literature review to support the modelling and direct measurement in a patient sample based on EQ-5D-5L values measured by the ePAQ-VAS. The details of these have been added to the School of Health and Related Research Health Utilities Database (ScHARRHUD) (see www.scharrhud.org/; accessed 1 December 2020), where they are publicly available.

Patient and public involvement

A non-disease-specific PPI group was engaged for the relevant work on the NIHR Vascular Programme Grant.

The PPI group, recruited through the Sheffield Clinical Research Group was used on a number of occasions, for example to review documentation that was required for ethics approval [e.g. participant information sheets and invitation letters (see Appendix 10)].

There were two main periods of interaction with the PPI group, as detailed below:

1. In summer 2016 when the group reviewed study documents [participant information sheet and invitation letter (see Appendix 10)] and participated in mock interviews using the AAA interview schedule (this was relevant to workstream 3).

2. In spring 2017 when the group again participated in mock interviews (this was relevant to workstream 3).

The feedback from the mock interviews was used to revise the interview schedule and interview booklets to ensure that they were designed and delivered in line with the PPI panel recommendations regarding accessibility for all readers and participants.

Appendix 9 outlines a record of the changes that were recommended by the PPI panel to ensure maximum efficacy of the documentation shown in Appendix 10.

Details of the patient and public involvement panel

The PPI panel is a lay advisory panel that is not focused on a specific disease. Further information about the PPI panel is available at www.sheffieldclinicalresearch.org/for-patients-public/how-to-get-involved/ (accessed 1 December 2020).

Publications

The PPI group has been acknowledged in the publications resulting from this aspect of the programme of work. The PPI group lead was made aware of any decisions to include the PPI group in publication acknowledgements to ensure correct reference.

Successes and limitations

Implications for research

The programme has resulted in the development of two main tools that should be beneficial in the planning and evaluation of vascular services; however, there is considerable potential for further work to be carried out on these. The ePAQ-VAS has been developed to a stage at which it is in a useable format and has undergone extensive psychometric evaluation, showing good validity and reliability. The next stage in its development is the wider application in clinical practice with its evaluation both as a clinical tool for monitoring outcomes and as a potential method for collection of data for the evaluation of services. For this purpose, the usability and nature of report formats requires some further development and the tool requires evaluation in different clinical settings and geographical regions.

The web-based model of service provision has considerable potential for further development both in evaluating its usefulness in the real-world situation of regions undergoing a reorganisation of vascular services and in considering its potential applicability to other and more widespread clinical services.

In addition to further work on the tools that have been established by the programme, there are a number of areas that have been highlighted as worthy of further studies:

1. Studies of the drivers of and barriers to organisational change within vascular services.

   It is clear from the data that have been analysed that many centres have managed to amalgamate services for major vascular surgery and radiology on a single site. However, there are a number of other areas in which the geographical distribution of population and services would appear to differ little from those where there has been successful reorganisation and yet there remain services that fail to meet the published recommendations for service configuration. It is suggested that detailed qualitative studies with the various stakeholders in such areas may aid an understanding of the barriers to such reconfiguration.

2. Further development of vascular registries and data linkage.

   The current procedure-based NVR is an invaluable source of information regarding practice and outcome. However, it is limited by being a procedure-based registry that does not track subsequent procedures and outcomes, collect data relating to selection processes or collect data regarding patients who are turned down for elective or emergency surgery. There is potential for linkage between data sources including HES, ONS statistics and data from the NAASP. This has the potential to provide a more complete picture of practice and outcomes in vascular services.

3. The measurement and application of process utilities.

   The studies carried out in this programme suggest that society places a significant value on aspects of the service other than HRQoL outcomes. This includes aspects of the process of care, such as the invasive nature of an intervention and the location of services. This is a new area of research and further investigation is warranted to further develop methods of measurement of process utilities and to investigate the ways in which these may be incorporated into cost-effectiveness analyses.

4. Exploration of variations in practice and coding.

   The data analysed for this programme demonstrate considerable variation in practice, resource use and cost between different units. It is unclear from the data the extent to which these represent local variations in the way that patients are managed, geographical differences in case-mix or differences in coding practice. All of these may have significant implications for the cost-effectiveness of the service provided.

Implications for practice and policy

This programme of research has confirmed the potential clinical effectiveness and cost-effectiveness of consolidating services for major vascular surgery on single sites with a higher volume of activity. Considering the existing recommendation for a minimum of 60 aortic aneurysm repairs per year, averaged over a 3-year period,3,171,172 approximately 20% of aneurysm repairs in England continue to be carried out in centres that do not meet this criterion. Data analysis suggests that extending this to a higher threshold of approximately 100 cases per year may have further advantages with regard to clinical outcomes.

Examination of the geographical arrangements suggests that the distances involved, with a few exceptions, are unlikely to be a barrier to such reconfiguration and consideration could be given to how such changes may be achieved.

In considering service reconfiguration, there are a number of other issues that need to be taken into consideration. Patient preferences for local services and the need to maintain links to other specialties would suggest that some form of hub-and-spoke arrangement may allow some services to be provided more locally, where it is safe to do so. Providing services, such as investigations, minor procedures, day-case surgery and amputation rehabilitation, at a spoke site through an integrated hub-and-spoke service would maintain a regular presence of vascular clinicians and health-care professionals and promote linkages with other services. The evidence from the data analysed suggest that there is a trend towards moving such procedures into the central site, rather than maintaining hub-and-spoke arrangements. However, there would appear to be a potential for greater integration of services with outreach or in-reach arrangements that could minimise the movement of resources, pressure on facilities and workforce implications associated with centralisation of major operating. The potential for such distributed services would depend on existing local staffing and facilities, and could be usefully explored through further modelling in any further planned reorganisation of services.

In this respect, there is also a case for considering how preferences for aspects of the service that are not included in current cost-effectiveness calculations may be more formally incorporated in policy-making processes.

The evaluation of PROMs suggests that most of the existing measures that apply to vascular services are poorly validated and not widely implemented, hence the development of the new ePAQ-VAS instrument. There is a need for more widely applicable tools for the collection of such data in vascular patients both for clinical management and for the evaluation of services. It is suggested that the implementation of an appropriate outcome measure, such as the ePAQ-VAS, would be a potentially beneficial development.

There is considerable variation in practice with regard to the introduction of new technology and in coding practices. It is suggested that there is a need for standardisation of procedures for the introduction of new technology, better monitoring of compliance with guidelines and audit of sites that appear to be outliers, with regard to practice or coding, to address such variability.

Contributions of authors

Jonathan Michaels (https://orcid.org/0000-0002-3422-7102) is the principal investigator and made a substantial contribution to the conception, design, analysis, interpretation and writing up of all aspects of the study.

Emma Wilson (https://orcid.org/0000-0002-4695-2184) was the programme manager throughout the full 6 years of the programme. She was involved with and had oversight of the design, development and implementation of all of the workstreams in the programme. She was involved in the day-to-day research (governance approvals, data collection and data analysis) for workstreams 2 and 3.

Ravi Maheswaran (https://orcid.org/0000-0002-3899-4421) was co-lead for the workstream relating to analysis of HES to identify trends and variation in activity and aspects of case-mix and outcome that can be established from routinely collected data sources. He made a substantial contribution to the conception, design, data acquisition, analysis, interpretation and writing up of the study, particularly in relation to epidemiological aspects.

Stephen Radley (https://orcid.org/0000-0002-3980-7712) reviewed the manuscript, including the electronic web-based questionnaire (ePAQ-VAS) materials and updating the website and associated links. He was responsible for the design and support of web-based questionnaire and associated platform technology.

Georgina Jones (https://orcid.org/0000-0002-5267-1776) was lead for workstream 2. She made a substantial contribution to the conception, design, data acquisition, analysis, interpretation and writing up of the study, particularly in relation to the stages of work that underpinned the development and psychometric testing of the ePAQ-VAS.

Thai-Son Tong (https://orcid.org/0000-0002-9307-6850) was the lead for the workstream relating to the development of the cost-effectiveness model and the analysis of HES data supporting the model development. He was also the main data analyst to manage and process HES data to support other workstreams. He made a substantial contribution to the conception, design, data acquisition, analysis, interpretation and writing up of the study, particularly in relation to HES analysis and modelling studies.

Eva Kaltenthaler (https://orcid.org/0000-0002-6185-8321) contributed to the conception, design, analysis and interpretation of the study, particularly in relation to the systematic reviews of PROMs and volume–outcome relationships.

Ahmed Aber (https://orcid.org/0000-0002-5707-2430) made a significant contribution to the conception, design, data acquisition, analysis, interpretation and writing up of the study, particularly in relation to the systematic reviews of valid PROMs, qualitative systematic reviews, development of the ePAQ-VAS and psychometric analysis of the ePAQ-VAS. He made substantial contribution to HES data analysis and the design of health states to measure the process utilities associated with vascular services reconfiguration.

Andrew Booth (https://orcid.org/0000-0003-4808-3880) made a significant contribution to the conception, design and write up of the qualitative evidence synthesis, providing methodological advice on the use of framework synthesis and advising on the triangulation of concepts from the literature with those from the PROMs.

Helen Buckley Woods (https://orcid.org/0000-0002-0653-9803) made a significant contribution to the project as information specialist, particularly in the systematic reviews of PROMs and volume–outcome relationships, and the qualitative literature review of patients’ perspectives.

James Chilcott (https://orcid.org/0000-0003-1231-7817) contributed to the conception, design, data acquisition, analysis, interpretation and writing up of the study, particularly in relation to the health economic modelling workstream.

Rosie Duncan (https://orcid.org/0000-0003-2712-4743) made a significant contribution to the methods of the qualitative reviews, the data extraction from the systematic reviews and the design and collection of the qualitative interviews that informed the development of the PROMs.

Munira Essat (https://orcid.org/0000-0003-2397-402X) made a significant contribution to the conception, design, data acquisition, analysis, interpretation and writing up of the study, particularly in relation to the systematic reviews of PROMs and volume–outcome relationships and in the identification of economic model parameters.

Edward Goka (https://orcid.org/0000-0002-6754-3312) contributed to the conception, design and writing up (data collection, analysis and interpretation of findings) of the manuscript on relationship between volume and outcomes in lower limb. He also contributed to data extraction, and critically reviewing and revising intellectual content of the manuscripts for the systematic reviews on abdominal aneurysm and carotid artery, and approved the final versions of all the three reviews and the final report.

Aoife Howard (https://orcid.org/0000-0002-1589-5586) made a significant contribution to the conception, design, data collection, analysis, interpretation and writing up of the study, particularly in relation to the large-scale national telephone survey of public preferences for non-health outcomes related to vascular services. Aoife also contributed to systematic reviews of valid PROMs and the impact of vascular conditions on quality of life.

Anju Keetharuth (https://orcid.org/0000-0001-8889-6806) contributed to data collection and analysis of and interpretation of psychometric properties of PROMs in patients with AAA and PAD.

Elizabeth Lumley (https://orcid.org/0000-0002-8962-7568) made a significant contribution to the conception, design, data acquisition, analysis, interpretation and writing up of the study, particularly in relation to the qualitative quality of life study, qualitative systematic reviews and development of the ePAQ-VAS.

Shah Nawaz (https://orcid.org/0000-0002-7282-5816) made a significant contribution to the conception, design, data acquisition, analysis, interpretation and writing up of the study. He was also significantly involved across the workstreams in relation to the ePAQ-VAS, HES and PPI.

Suzy Paisley (https://orcid.org/0000-0002-1739-6852) contributed to the design of systematic reviews including scope definition, literature search design and study selection processes.

Simon Palfreyman (https://orcid.org/0000-0002-5927-1951) contributed to the conception, design, data acquisition and analysis of the study, particularly in relation to PROMs. He was also significantly involved across the workstreams in relation to the ePAQ-VAS, systematic reviews, HES and PPI.

Edith Poku (https://orcid.org/0000-0001-6549-5081) made a substantial contribution to the conception, design, data acquisition, analysis, interpretation and writing up of the study, particularly in relation to the systematic reviews of PROMs and volume–outcome relationships and in the identification of economic model parameters.

Patrick Phillips (https://orcid.org/0000-0003-0241-1527) made a significant contribution to the conception, design, data acquisition, analysis, interpretation and writing up of the study, particularly in relation to the systematic reviews of volume–outcome relationships and PROMs, the development of the ePAQ-VAS and in the evaluation of non-health outcomes.

Gill Rooney (https://orcid.org/0000-0002-8388-9444) made a significant contribution to data collection, analysis and writing up of the final report, in particular with relation to the evaluation of public preferences for non-health outcomes related to vascular services. She also assisted in preparing and co-ordinating the final report for submission.

Praveen Thokala (https://orcid.org/0000-0003-4122-2366) contributed to the conception, design, analysis, interpretation and writing up of the HES analysis and modelling studies.

Steven Thomas (https://orcid.org/0000-0001-5855-2842) made a significant contribution to the conception, design, data acquisition, analysis, interpretation and writing up of the study. He was also significantly involved across the workstreams in relation to the ePAQ-VAS, HES and economic model parameters.

Angela Tod (https://orcid.org/0000-0001-6336-3747) contributed to the conception, design, data acquisition, analysis, interpretation and writing up of the qualitative components of the research programme, especially in the initial 3 years.

Nyantara Wickramasekera (https://orcid.org/0000-0002-6552-5153) made a significant contribution to the conception, design, data collection, analysis, interpretation and writing up of the study, particularly in relation to the large-scale national telephone survey of public preferences for non-health outcomes related to vascular services.

Phil Shackley (https://orcid.org/0000-0002-1862-0596) made a substantial contribution to the conception, design, data acquisition, analysis, interpretation and writing up of the study. He led the workstream relating to the elicitation of public preferences for treatments for abdominal aortic aneurysms and the disutility of having to travel for treatment, and conceived the methodology and study design used in the workstream.

Data-sharing statement

All data requests should be submitted to the corresponding author for consideration. Access to anonymised data may be granted following review. Data from Hospital Episode Statistics can be requested through NHS Digital (https://digital.nhs.uk/data-and-information).

Patient data

This work uses data provided by patients and collected by the NHS as part of their care and support. Using patient data are vital to improve health and care for everyone. There is huge potential to make better use of information from people’s patient records, to understand more about disease, develop new treatments, monitor safety, and plan NHS services. Patient data should be kept safe and secure, to protect everyone’s privacy, and it is important that there are safeguards to make sure that it is stored and used responsibly. Everyone should be able to find out about how patient data are used. #datasaveslives You can find out more about the background to this citation here: https://understandingpatientdata.org.uk/data-citation

Disclaimers

This report presents independent research funded by the National Institute for Health 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, CCF, NETSCC, PGfAR 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, NETSCC, the PGfAR programme or the Department of Health and Social Care.

Analysis of Hospital Episode Statistics data: general methods

A major part of the first workstream of the programme was the analysis of HES data, as described in summary in Vascular activity and outcomes from routine data, and in more detail in Report Supplementary Materials 1–11, to characterise the workload of vascular services, to identify trends in activity, working practices and outcomes and to relate these to service configuration. This appendix describes the processes involved in this analysis.

Data extract

Hospital Episode Statistics comprises several databases containing the details of all admissions, accident and emergency attendances and outpatient appointments at NHS hospitals in England. It is now managed by NHS Digital and contains extensive information, as described in the HES data dictionary. 206 Data from HES are available through a data access request service that enables bespoke extracts to be obtained from NHS Digital. For the purpose of this programme, a data extract that included all of the major vascular procedures and diagnostic areas was requested in July 2013. The basic structure of the requested information included the available data regarding patient characteristics, geographical information regarding place of residence and treatment, diagnostic and procedural information, and details of the dates and destination for admission and discharge for each episode fitting a set of criteria that were likely to pick up the majority of vascular-related conditions and procedures. Having identified all potentially relevant episodes, data linkage using a pseudo-anonymised identifier was used to obtain all further episodes for the same cohort of patients, details of critical care episodes for those patients and linked data from the ONS obtained from death certification that provided the date and cause of death (see Report Supplementary Material 1).

Owing to numerous iterations and changes in procedure at NHS Digital, there were considerable delays in obtaining the data, which were eventually provided in May 2015. When a request for an extension to the programme was made in the autumn of 2017, a further request was made to update the HES extract; however, because of further delays in changes in procedure, the final extract was not received until February 2019, which left little time for further analysis.

Although the original data extract contained information from 1999 and the updated data extend to March 2018, a decision was made to limit the final analysis to the 12-year period from 2006 to 2018: the most recent 12-year period that was available. This decision was made because, owing to changes in coding, geographical data and provider arrangements, it was felt that it would be difficult to draw clear comparisons with data prior to 2006.

Overview of process

The analysis of HES data was an extensive and time-consuming process because of the very large data sets and complexity of the information. The majority of analyses were carried out through custom programmes written in the R software environment for statistical computing. The processing consisted of a number of stages. Initially, the data were ‘cleaned’ to remove records missing critical information or containing inconsistent data and to identify and remove duplicate records.

The second stage was to identify and characterise individual hospital admissions. The structure of the inpatient records is based on episodes of treatment [finished consultant episodes (FCEs)] that differ from definitions of ‘spells’ or ‘admission’, in that multiple episodes may occur within the same period of admission to hospital for treatment. To produce consistent data, the decision was made to consider admissions in terms of CISs that include the full duration of a patient’s hospital journey from the date of first admission to hospital to the last discharge, in which episodes were overlapping or sequential without a break even if there was a transfer between specialties or hospitals during that period.

To categorise the admission, a series of case-mix categories were defined with the help of a clinical consensus group to classify admissions into clinically meaningful groups. The case-mix groups were ordered in a hierarchy to determine the category of those cases for which there were multiple procedural or diagnostic codes that may assign the case to different clinical groupings. Assignment rules were also developed to identify an index admission to categorise patients with multiple admissions and characterise pathways of care, and to prevent double-counting of patients who may fall into several categories at different times.

Having merged episodes into single records for admissions relating to the specific case-mix groups, further work was carried out to identify the site of treatment to link data with critical care and ONS mortality data. These were used to develop measures of outcome to classify those comorbidities and complications that were identifiable from the data and to carry out an analysis of costs for specific procedures and pathways of care.

Further details of the various process involved are provided in the following sections.

Clinical consensus group

A group of clinicians involved with the management of vascular disease assisted in the classification of HES data. The exact composition of the group varied over the duration of the programme, but included vascular surgeons, physicians, vascular interventional radiologists and clinical nurse specialists. Their input was an essential part of the process in identifying the appropriate categorisation of clinical activity. As can be seen from the detailed descriptions, there are a number of issues where ambiguities or inconsistencies in the coding led to uncertainties in the categorisation of patient groups. Where such difficulties arose, the clinical group considered the various options for categorisation and determined additional information that may be of assistance in determining the optimum categorisation. For example, where there was doubt about whether or not certain procedures were related to vascular disease, the consensus group suggested potential tabulations of data, based on other fields in the data set (e.g. specialty, diagnostic codes or data in linked admissions), that may help to clarify the most appropriate categorisation. This was an iterative process in which further analyses were suggested and data tabulated for further discussion by the clinical consensus group.

Examples of areas for which clinical input was essential in determining appropriate categorisation are the various methods for categorising the treatment of emergency or ruptured AAAs and for distinguishing between amputations for vascular and amputations for other conditions. These specific issues in these cases are discussed in more detail below and in Report Supplementary Materials 2 and 4.

Definition of case-mix groups

To facilitate the analysis, and in keeping with the proposed modelling, the analysis plan involved the development of specific categories of vascular activity for which pathways could be described. In each of these categories, activity was divided into clinically meaningful case-mix groups. This was carried out through an iterative process in which a group of clinicians and expert advisers provided some textual description of appropriate groups and categories. These were then translated into algorithms for identification based on the Office of Population Censuses and Surveys (OPCS)’s and diagnostic codes. Some initial identification using the categorisation was carried out, and there were several iterations where records were sampled both from those included in the various groupings and from those that would be excluded. These were reviewed and, where it became apparent that the categorisation was ambiguous or unsatisfactory, further attempts were made to refine the categorisation by including decision rules based on combinations of diagnostic and procedural codes or other fields that are available from the HES records.

The initial decision was to divide the workload into five case-mix categories:

1. AAA

2. PAD

3. CAD

4. VV

5. venous ulceration.

During the subsequent work, it became evident that the diagnostic codes for venous ulceration were not sufficiently sensitive to differentiate between chronic venous disease and leg or foot ulceration related to PAD. As a result, the PAD and venous ulcer categories were combined to make a single category of peripheral arterial and complex venous disease.

In addition to this, there was found to be a significant vascular workload that was not directly related to these categories, which included conditions for which there were differences in practice between centres and some more specialist procedures. These were treated as an additional category of ‘other vascular procedures’. This category included procedures on the visceral vessels, vascular access procedures, upper limb vascular procedures and arteriovenous malformations.

Initially, consideration was given to using existing coding systems for categorisation; the various versions of the HRG classification were considered but suffered from a number of drawbacks. There have been several iterations of these, with a changing categorisation over the years, and, although it was possible to allocate using the most recent grouper, when this was attempted the expert advisory group felt that the categorisation was not ideal for the purpose of identifying differences in practice that may be significantly related to the service configuration. The main rationale for this was that certain areas lacked the granularity to distinguish what were felt to be important clinical distinctions. Therefore, it was agreed that the categorisation procedure would be undertaken from scratch based on the OPCS and International Classification of Diseases (ICD) codes. 207

As a first step, all OPCS codes relating to vascular surgical procedures (largely L codes) and those relating to amputations (X codes) were considered individually and classified according to whether or not they were likely to be within the remit of vascular services. Those codes that were felt to be non-specific and may or may not relate to vascular services were identified separately. The OPCS codes were assigned to the vascular groups as detailed in the tables in Report Supplementary Material 2. (This gives the final categorisation following the iterative process described below.)

For each of the assigned groups, records were then sampled in two ways. Initially, random cases were drawn from the categories and a clinician reviewed all of the HES fields including age, sex, specialty and the text relating to OPCS, HRG and ICD coding, to establish whether or not they felt that the cases were being correctly categorised.

The second set of checks were carried out by cross-tabulating various aspects of the identified groups, looking at them by the most common primary diagnoses, the main specialty and treatment specialty and any other fields that were felt to be relevant in specific cases.

This process resulted in refinement of a number of the categories and groupings. The following sections describe the specific issues that were encountered and the decisions that were made regarding categorisation for each of the case-mix categories.

Abdominal aortic aneurysm

There were several issues encountered in identifying AAA surgery.

Emergency versus elective admission or procedure

In the HES data record, the OPCS data include separate codes for emergency and elective aortic aneurysm repair (e.g. L18X vs. L19X). There are also different codes for ruptured and non-ruptured aneurysm (e.g. I713 vs. I714) and the codes regarding the admission method distinguished between elective and emergency admission to hospital.

Cross-tabulating the method of admission against either the diagnostic or the OPCS codes suggested that there was considerable inconsistency in the way that the coding was carried out. Following discussions with clinical advisors, it was decided that the best way to handle this was to divide admissions into elective and emergency admissions, irrespective of the categorisation of the procedure or diagnosis. Among the emergency admissions, two categories were separately identified that would be a proxy for ruptured and non-ruptured urgent cases based on a combination of the ICD codes and the delay between admission and first operation.

On inspecting cross-tabulation of these data, it became evident that the combination of using the code for ruptured aneurysm with a delay between admission and surgery of < 3 days, and a code for a non-ruptured aneurysm with surgery on the day of admission resulted in discrimination between two groups of emergency aortic aneurysm, with a considerable difference in mortality. This was felt to reflect a best attempt at a meaningful separation between the clinically distinct categories of ruptured and non-ruptured urgent aneurysm repair.

Aortoiliac and aortobifemoral bypass

The OPCS procedure codes have separate codes for aneurysm repair and aortic bypass (e.g. L19X vs. L21X). The procedure carried out for an aortic aneurysm may sometimes be described as an aortic bypass, and examination of HES records showed that the codes often coexisted. Even where there was no code in the OPCS fields for an aortic aneurysm procedure, a significant number of cases in which there were aortic bypasses included a diagnostic code representing AAA. The aortic bypass procedures were, therefore, amalgamated and, where the ICD codes included a field containing a code for AAA, the procedures were categorised as infrarenal aneurysm repair, whereas those without such an ICD code were categorised as aortic bypass for PAD.

Endovascular aneurysm repair

New OPCS codes for EVAR (stent graft) were introduced in 2005. Prior to this, it is not possible to reliably separate EVAR from open surgical repair. After the introduction of separate codes for endovascular repair, it was found that many cases had records including OPCS codes for both non-specific aneurysm repair and endovascular repair. In some cases, this may be a reflection of multiple procedures within the same admission; however, this is quite an unusual event and is considered separately in relation to identifying cases with multiple operations in the same admission. In cases where the coding represents multiple codes being used for the same procedure the clinical advice, supported by considering differences in mortality rates and hospital stay, suggested that the majority of these were instances of a single endovascular procedure with multiple procedural codes. For this reason, those cases where there were both codes in the record were classified as endovascular repairs.

Juxtarenal and suprarenal aneurysms

Historically, aneurysms above the renal artery were dealt with in cardiothoracic units or a few specialist vascular units; however, with the increasing use of fenestrated and branched endovascular stent grafts, several vascular units are now undertaking significant numbers of these procedures. Examination of the records suggested that the majority of cases classified with codes representing these procedures continue to be carried out at specialist cardiothoracic units. However, a proportion represent juxtarenal aneurysms that fall into the workload of vascular services. In the absence of any better way to categorise these, they were classified on the basis of treatment specialty or, where this was not available, on main specialty, including vascular and general surgery and interventional radiology within the vascular workload. All other cases (most of which were cardiothoracic or cardiology specialties) were excluded.

Aneurysm-related deaths

A proportion of patients admitted as an emergency with a ruptured AAA die either before or during surgery. It felt important to try and capture these, as the selection of patients for intervention may potentially represent a difference owing to different organisational arrangements. We examined the records of a sample of patients who died in hospital and whose diagnostic codes included AAAs. This revealed that there were a significant number of cases in which a procedure, such as laparotomy, a diagnostic procedure or insertion of a venous line, was recorded in the procedure codes or in which there was a death on the day of admission without a procedure. However, there were also other cases for which aneurysm was included as a secondary diagnosis and the main reason for admission appeared to be other than the aneurysm, particularly cardiac or respiratory diagnoses. A vascular group was, therefore, defined in which the treatment and/or main specialty was vascular or general surgery, the primary diagnosis field included the code for AAA and the discharge method identified a death in hospital.

Summary

The considerations above gave rise to a final category of AAA-related admissions with the procedures being grouped as suprarenal and juxtarenal endovascular repair (complex endovascular); suprarenal and juxtarenal OR (complex open); infrarenal endovascular repair; infrarenal OR (to include aortic bypasses with a diagnosis of aneurysm); and patients with a diagnosis of an aneurysm who died without an aortic procedure being recorded.

Peripheral arterial disease

Procedures that were included in the peripheral arterial category covered a wide range of endovascular and open procedures and amputations carried out for lower limb vascular disease. The procedures were divided into 12 categories: aortoiliac bypass, extra-anatomical bypass, femoroproximal and femorodistal bypass, femoral endarterectomy, major and minor amputation, iliac, femoral and unspecified angioplasty, embolectomy, and investigations. Some of these categories required some further refinement, particularly where codes were non-specific.

Aortoiliac bypass

As referred to above, some aortoiliac bypasses were carried out in patients with diagnostic codes for aneurysm, and these were, therefore, classified above with the infrarenal aneurysm repairs. The remainder were categorised as PAD procedures; however, there was an additional group that included non-specific codes for operations on the aorta, such as unspecified bypasses of a segment of aorta (L219) and endarterectomy of aorta NEC (L252). Where the codes were non-specific, further investigation showed that the diagnostic and specialty codes suggested that some of these were carried out for cardiothoracic diagnoses and the cases were, therefore, limited to those with a treatment specialty or main specialty of general or vascular surgery.

Endovascular treatment

The OPCS codes have been modified in recent years to include a number of different endovascular procedures, including transluminal placement of stent, transluminal angioplasty, other transluminal procedures and separate codes for placement of different numbers of bare metallic or drug-eluting stents. Many of these codes do not specify a site; however, there are additional codes for transluminal procedures on the femoral or iliac arteries, but not for procedures distal to the knee. The transluminal procedures were, therefore, divided into three categories of iliac angioplasty, femoral angioplasty and unspecified angioplasty to include all transluminal therapeutic procedures. The unspecified group were found to contain a large number of procedures that were carried out under cardiac or cardiothoracic specialties, and these were, therefore, further filtered on the basis of the treatment or main specialty codes.

Amputation

The majority of lower limb amputations in the UK are carried out for vascular and diabetic disease and, therefore, fall largely within the remit of vascular services. There are, however, some that are carried out for malignancy, trauma or orthopaedic problems. The initial intention was, therefore, to limit amputations on the basis of specialty; however, it became apparent that in some places there is significant crossover, with orthopaedic surgeons carrying out some amputations on patients with diagnoses of diabetes or vascular disease, whereas in other areas vascular or general surgeons would be involved in amputations resulting from non-vascular causes. The amputations were, therefore, selected on the basis of excluding a set of diagnostic codes for trauma and malignancy, leaving a less specific group that could be explored further in relation to vascular treatment pathways.

Carotid disease

Carotid treatments were divided into endovascular treatments (codes L311–L319 and L767) and open procedures that included endarterectomy, carotid body operations and carotid bypass procedures.

Varicose veins

There have been recent changes in the treatments available for VV. Up until 2005/6, the only procedures for which OPCS codes were available were injection sclerotherapy and open surgical procedures. Since 2006/7, additional codes have been introduced for radiofrequency ablation and laser ablation. Where available, the category of VV has been split into five separate groups for open surgery, including high ligation and surgery on the truncal veins, phlebectomy/avulsions, laser treatment, radiofrequency ablation and sclerotherapy.

Venous ulceration was originally intended to be defined as a separate category based on ICD codes; however, sampling of records demonstrated that the codes for leg ulcers were non-specific and sometimes associated with other codes and procedures that suggested complex venous disease or mixed arterial disease. It was, therefore, considered that these would be best analysed as part of the PAD pathway.

Other procedures

There are a large number of other procedures that may potentially fall under the remit of vascular services. Although these include a large number of codes, many of them are not specific to vascular services and the overall numbers that appear to have been admitted under the care of vascular services are relatively small compared with the main diagnostic groups. However, examination of this showed that some were procedures that may represent complications of other treatments for vascular disease, they also contain a large number of therapeutic endovascular procedures, many of which may be carried out by a vascular interventional radiologist, as a service to other specialties and may therefore represent an important group in respect to potential reconfiguration of services. These were, therefore, identified and grouped for subsequent analysis; these resulted in a number of different groups that may require separate consideration.

Arteriovenous malformations

There are separate codes for open and endovascular treatment of arteriovenous malformations; however, these do not specify the treatment site. Although there is the facility for identifying sites within the ICD codes, examination of the records showed that these were used inconsistently and many arteriovenous malformations are treated by other specialties. These were, therefore, divided into two groups for endovascular and open treatments but restricted to those cases in which the treatment and/or main specialty was general surgery, vascular surgery or interventional radiology.

Upper limb procedures

Again, these were divided into open and endovascular procedures on the basis of the OPCS codes.

Vascular access procedures

There is considerable variation in practice as to the specialties that undertake vascular access procedures, particularly those required for cancer treatments and for renal access. In some places these are carried out by vascular surgeons and there is an increasing use of endovascular placement, often with the involvement of interventional radiologists. It was, therefore, decided to include these procedures in the analysis and, for the purpose of categorisation, they were divided into four groups for renal access and other forms of access, each of which were subdivided into endovascular and open procedures.

Visceral and renal artery procedures

These are relatively uncommon procedures and, therefore, renal and visceral procedures were grouped together but subdivided into endovascular and open procedures.

There are a range of other procedures that may contribute to the workload of vascular services; those that are open procedures largely relate to unspecified procedures on arteries and veins, which were found to be unusual on their own, but often combined with another procedure. These were classified as ‘other open vascular procedures’. There is also a wide range of miscellaneous endovascular procedures including therapeutic occlusion of vessels, procedures relating to thrombolysis, embolisation, embolectomy and insertion of filters. Some of these may represent a significant workload for vascular radiology services and they were, therefore, identified as a separate group for further evaluation.

Hierarchy of procedures

To ensure consistency across the entire data set, the first 12 fields containing procedure codes were checked for relevant OPCS codes that could be assigned to one of the above categories. Because each episode contains multiple procedure fields and each admission may have multiple episodes, a process was developed to flag whether or not a specific episode and a specific admission contained codes that would result in assignment to each of the groups. A hierarchy was then developed on the basis of consultation with clinicians to assign those cases that contained codes relating to multiple case-mix groups to the most appropriate primary grouping (see Report Supplementary Material 2).

In general, the rationale was that specific categories were preferred to non-specific ones (e.g. if there were codes for femoral angioplasty and non-specific codes relating to angioplasty, the case would be assigned as a femoral angioplasty). There were some specific instances that required value judgements that were made in consultation with the clinical expert advisers:

• Cases with both aneurysm procedures and peripheral arterial procedures were categorised as aneurysm. The rationale for this was that when arterial procedures and aneurysm-related procedures are carried out in the same admission, it is often the case that the arterial procedure either is an aspect of the aneurysm treatment (e.g. iliac angioplasty or embolisation related to endovascular aneurysm repair) or might relate to a complication of the aneurysm treatment, such as distal embolisation, bypass or limb loss following aneurysm surgery.

• In the aneurysm group, those with both endovascular and open procedures were assigned to endovascular procedures. The basis of this was examination of records, which suggested that codes for aneurysm repair are sometimes used in conjunction with endovascular procedures and, where an OR and an endovascular procedure occur separately in the same admission, it was felt most likely that the OR represented a failure of an intended endovascular procedure. This latter point will be investigated further when looking at multiple procedures within the same admission.

• In the VV category, episodes often contained multiple codes for procedures and the clinical advice was that certain surgical procedures or sclerotherapy may be carried out in conjunction with laser or radiofrequency treatment for truncal veins. Cases where there were codes for the newer procedures were, therefore, assigned to these, with other open procedures taking precedence over avulsions or sclerotherapy.

• Where groups within the ‘other’ category were present alongside codes for aneurysm, PAD or carotid treatments the case was assigned to one of the last two categories.

• Although cases were assigned to a single group and category to allow the development of pathways, the flags for each of the individual groups were retained to allow subsequent consideration of patterns of activity in which there were multiple procedures or multiple categories of treatment.

Identification of treatment sites

One of the main aspects of the analysis of HES data was to characterise the relationship between hospital volume and aspects of practice, resource use and outcome to model the effects of changes in service configuration. To do this, it is necessary to identify the sites at which procedures are carried out. The HES data set contains two fields that identify the provider site. The first is ‘procode’, which should contain the provider code for the NHS provider under which the episode is categorised, and the second is ‘sitetret’, which should identify the site at which the treatment takes place. Examination of these fields showed that there is considerable variation in the way in which the codes are used, and this is compounded by changes in organisational structures, as a result of which the relationship between individual sites and NHS providers may have changed over the years.

In theory, all NHS acute trusts should be represented by a three-digit alphanumeric code beginning with the letter R. NHS trust sites are identified by a five-digit alphanumeric in which the first three digits are those of the provider trust and the last two digits identify the specific site. There is, however, considerable inconsistency in the way that these codes are used. In some cases, the full five-digit site appears in the provider code, whereas in others there is a three-digit code or three digits followed by non-specific digits, such as 00 or XX. In some cases, the ‘sitetret’ field contains just two digits representing the site; in others it contains a full five digits. There are some instances of the initials of the hospital being used rather than the published code and some hospitals have multiple site codes representing different wards or units within the hospital.

Expert opinion was that it was important to identify the sites in which procedures were carried out rather than to rely on provider codes alone, as there have been many changes in provider trusts and the merger of several hospitals into a large single provider for administrative processes may or may not be accompanied by changes in the sites at which vascular services are delivered. An exercise was, therefore, carried out to try to identify hospital sites in a consistent way, so that changes in practice with regard to the sites at which procedures are carried out could be comparable across the years of the study. It was felt that this was particularly important for major vascular procedures and, therefore, an attempt was made to identify specifically all sites where elective AAA repair were carried out during the period of study.

To achieve this, all combinations of provider and site code were identified and all combinations of codes were examined individually. Where the provider and site codes did not correspond and map to a consistent specific site, both codes were examined individually to categorise them wherever possible. In many cases, it was possible to identify the site in this way. A further exercise was carried out to identify multiple sites that represented different units or wards within the same hospital and to reclassify sites where the coding had changed owing to organisational codes and to map these onto the current provider sites.

In this way, a look-up table was produced of all sites at which aortic aneurysm repair had been carried out. These were identified by a site identifier (ID) consisting of the current three-digit provider code plus a fourth digit that represented the individual site. Where a provider had only a single site carrying out aortic surgery or where there was insufficient coding to identify the site beyond the three-digit provider code this was designated XYZ0 (where XYZ is the three-digit provider code), and where a specific site was identified these would be numbered XYZ1, XYZ2, etc. In this way, a look-up table was generated that allowed the concatenated provider and site codes to be used to look-up the specific four-digit site identifier. In addition, as some sites had changed name and some hospital moves had taken place, further identification and amalgamation of sites was carried out by matching site postcodes.

Since the introduction of the NAASP, aneurysm services in England have been grouped into 43 screening areas and, based on digitised mapping of these areas, all resident LSOAs and provider sites were classified to a specific screening area for consideration of geographical variations in configuration and practice (see Report Supplementary Material 3).

Identification of admissions

The HES provides records at the level of consultant episode. Where patients are transferred between consultants or units within a single admission, this may generate multiple episodes within the same stay in hospital. Each episode may have duplicate or unique information regarding procedures, diagnoses or other fields within the HES record. To develop patient pathways for specific treatments and conditions it is necessary to combine the episode-level data into admissions. In the majority of cases, a single episode is present in an admission so that the episode start and end dates are the same as the admission and discharge dates; however, where there were multiple episodes it is necessary to aggregate the relevant information across multiple episodes to produce an admission-level set of data.

A significant proportion of episodes do not contain a discharge date, so the first stage in this procedure was to identify admissions as being all unique combinations of admission and anonymised HES ID for the same patient. In some cases, this results in admissions with multiple discharge dates. This may occur if there is a day-case admission followed by re-admission or transfer to another hospital on the same day, or if one or more of the episodes contains an incorrect discharge date.

In developing the admission-level data set, all admissions on the same date for an individual patient were combined while retaining the episode-level data to identify transfers between sites, re-admissions and multiple procedures within the same admission. To create an overall admission record, the discharge dates were aggregated to identify the last discharge date, taken as the end of the full admission.

Examination of the data showed that there are a number of anomalies within the records. For example, there may be multiple admissions that appear to have the same discharge date for the same patient. This may occur if, for example, a patient is discharged and then re-admitted and discharged or dies on the same day. It may also be due to a data entry error. Because the former circumstance in particular is relevant to the outcome of treatment, these episodes were combined into the same admission record by creating a minimum admission date for all admissions with the same end date.

Further evaluation of the data showed that there are numerous anomalous situations in which there appear to be concurrent or overlapping admissions. Theoretically, if the rules for characterising admissions and discharges are followed, there should not be overlapping episodes, or episodes where admission and discharge dates are within another admission. However, the HES data show that this is not uncommon, and examination of records where this occurred suggested different circumstances where it seems to happen. One is commonly associated with admissions for investigations or dialysis, where it would appear that patients may remain in the HES data as apparently being an inpatient in one hospital, while having a separate admission for dialysis or an investigation, often as a day case. The other situation is where there are apparently discrepancies in the recorded admission or discharge date for what appear to be episodes within the same admission.

To allow further analysis of these situations, all overlapping and coincident admissions were combined into a single record based on a combined maximum discharge date and minimum admission date, with those in which there were multiple sites or conflicting dates being flagged for further consideration.

Identification of outcome measures

There are a number of potential outcome measures that can be identified from within HES data and different outcome measures are particularly relevant to particular case-mix categories. This section deals briefly with some of the issues in identifying outcome measures from the routine data set, but further details are provided in Report Supplementary Material 4 and in published papers. 7,11,208

Qualitative interviews topic guide patient number XXXXXXXXXXXXXXXXXX

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Section 1: comments on the invite letter

Is the invite letter clearly written and easy to understand? (if you feel there are elements of the invite letter that could be improved, please elaborate on this in your answer).

Reviewer 1 – Yes.

Reviewer 2 – I think that the letter is written in a clearly and easy to understand way mostly, and the layout is also clear and easy to understand. The part of the letter that mentions types of vascular problems that you can have could be taken out. This is because there would be very few people that would know what they were and even less understands them. As the participants of the projects are healthy therefore don’t suffer from any vascular problems, they probably won’t know what the conditions are, so the names of some of the problems would just confuse them when they read it.

Reviewer 3 – Is the invite letter clearly written and easy to understand? (if you feel there are elements of the invite letter that could be improved, please elaborate on this in your answer) Yes it is clearly written and understandable. It could be improved by defining the terms: vascular, services and vascular insufficiency, and also by using less medical terminology i.e. talking about blood circulation problems rather than vascular conditions.

Reviewer 4 – The letter is fairly clearly written, although terms are used that might not be understood and I wasn’t entirely clear about the purpose of the research from the letter.

It isn’t clear what a ‘healthy’ adult is – whether other conditions are excluded or just vascular conditions.

Also, it would be better to have the explanation of what ‘vascular problems’ are right at the start as the term is used in the title and first paragraph without explanation.

What are vascular ‘services’? in-patient/out-patient and/or community services?

I was confused as to how ‘public’ views on ‘vascular’ services could be explored.

Many people won’t know what ‘aortic aneurysm’ or ‘venous insufficency’ mean and there’s no explanation of ‘health-care treatments’ and ‘interventions’ ‘patient-focused’ may not be a familiar term to everyone.

Reviewer 5 – Reasonably clear however a description of what ‘Vascular’ services are, is needed. I feel the word vascular itself is too technical.

Also most of paragraph 3 needs to come before paragraph 2.

Using the phrase general public is condescending ‘public’ is fine.

Reviewer 6 – The letter is brief and to the point. I did however keep rereading to try to understand why you want the opinion of people who do not need to access this service.

Reviewer 7 – I think you should make it clear at the very beginning that this is an interview study, not a clinical trial or experiment.

Reviewer 8 – It is a well written, clear, logical and just the right length. This is difficult as not sure how it could be improved. It’s the correct length and gets right to the point without any unnecesarry information. I would perhaps want to maybe know a bit more information on how this study would impact the health service.

Reviewer 9 – The letter is very clearly written in plain English and easy to understand.

Reviewer 10 – It is clear, but I suggest the actual details of the participant’s contribution – the short interview possibly face to face-could be set out in the first paragraph just to engage them more.

Reviewer 11 – I am very happy that the invite letter is clearly written and easy to understand. It clearly states that the research is aimed at improving patient-focused care: I feel this is important when embarking upon a research study.

Reviewer 12 – It is, but where are you getting their name from? I think that needs including as you are hinting at the fact you know something about them as you know they don’t have a vascular condition. I think people need to assured that their contribution can make a difference and explain the rationale for interviewing this group. A lot of people will think they cannot comment on a condition they have no experience of and a service they have never used. I certainly fall into this category.

Having read the invite letter, do you think it is a project that you would consider taking part in?

Reviewer 1 – Yes.

Reviewer 2 – I would consider it, because it doesn’t sound like it would inconvenience me too much, as the interview is mostly likely to take place over telephone, and would only take around 20–30 minutes.

Reviewer 3 – Yes. It appears to be a worthwhile project in which to become involved.

Reviewer 4 – Not without more explanation – and I was put off by the technical nature of both documents and the hypothetical scenario methodology.

Reviewer 5 – Yes.

Reviewer 6 – I see no reason not to take part, it’s a painless half an hour of my time; I would like to know why you’re seeking the opinions of the general public, people unaffected by the service, to help shape the service. Why should I be interested?

Reviewer 7 – Yes.

Reviewer 8 – I would be interested in taking part to see how the services are being changed and from the letter it would suggest that re-structuring of services are taking place, and the researchers and clinicians are asking the public what they want and what they would benefit from.

Reviewer 9 – It is a project I would take part in, although there is no direct benefit to myself, it may help others.

Reviewer 10 – Yes, if I were ‘healthy’!

Reviewer 11 – Yes, I would be keen to take part in this project.

Reviewer 12 – Not currently, I would want the information I have asked for above.

Section 2: comments on the participant information sheet

Does the document clearly describe and explain what will be involved for a patient who wants to participate in the research?

Reviewer 1 – “Participant interviews will most likely take place over the phone, but some interviews will be in person”: Better said in Invite Letter: “This will most likely be a telephone interview, but in some cases could be in person, either at a clinic or hospital”. Why one or the other, and why not knowing in advance?

Reviewer 2 – Yes, apart from the part that mentions about some of the interviews being in person at clinic or in hospital. Is there a reason why some people would be interviewed in person, or is that an option in case some people can’t do the interview by phone? This would need clarifying, as it may put some people off, as they would find it an inconvenience for them if they would have to go in in person.

Reviewer 3 – Yes I believe so. The use of the term “patient” here is inappropriate I think as it is addressed to “healthy volunteers”.

Reviewer 4 – No – I don’t think so. It still uses medical terms and I found the interview structure unclear.

Reviewer 5 – Not really I found it very confusing is it about quality of services or how far I would travel for the service. Also, as a patient, would I be interviewed over the phone or face to face – why the difference and who decides? Finally what is described in the structure doesn’t seem like an interview to me more like a ‘virtual or imaginary game’ and this does need more clarification.

Reviewer 6 – Very clear, easy to read. Describes the process well.

Reviewer 7 – Yes I think it’s very clear.

Reviewer 8 – This document very clearly starts with something I look out for. ‘No obligation to complete this study’ and ‘contact details can be found at the end’. It then follows into what is expected and a general example of how the interview will be conducted.

‘The disadvantages and risks involved are minimal’. – I’m not sure about this? How can a phone call be risky? This is too general, you need to outline the risk clearly or if no, which I suspect, say “there are no risks involved with the interview”.

Reviewer 9 – The document is very thorough and clear on what would be involved for the patient. There is no harm involved in the study and data storage and use was explain clearly and thoroughly.

Reviewer 10 – yes.

Reviewer 11 – The participant information sheet is very clearly written, and explains everything in good detail. I feel it also sets out the aims of the project very clearly.

Reviewer 12 – It is, but I think it could have more information in it as described for the invitation letter above. A description of the documents they will be sent would be useful, as it sounds offputting and bit much like hard work for no benefit. It would be useful to give some examples of where this type of research has been successful before.

Would you say that the document is written in a language that patients would understand, if not, what parts need changing?

Reviewer 1 – Definition of “Trade-off techniques”.

Reviewer 2 – It is mainly written in a language that the patients would understand, apart from one part. The paragraph that talks about the purpose of the study includes a list of vascular problems near the end, “peripheral arterial disease, aortic aneurysm, carotid arterial disease, varicose veins and venous insufficiency”. The inclusion of this is confusing and not really that necessary for the patient information sheet as they won’t understand what they’re reading.

Reviewer 3 – As in my response to Section 1 I would like to see the terms vascular, services, insufficiency, explained in more everyday language so as to be more readily understood by lay persons.

Reviewer 4 – The ‘purpose’ paragraph is unclear – if this is aimed at the public who don’t have vascular conditions they are unlikely to understand the medical terms used. Also – it still doesn’t explain how public views can be related to services they don’t access. Same points as above re letter – use of ‘healthy’ ‘patient-focused’, etc. I found the interview structure unclear – would I be asked entirely hypothetical questions? And how much explanation would there be of the health states and treatments?

Reviewer 5 – I think a lot of the language is quite technical such as ‘vascular health-care treatments’ and ‘rank them in order of how good or bad’ and ‘trade-off technique’ So they need descriptions in short and simple sentences. Also what do you mean by good or bad? This is very vague does it mean ‘is this painful or uncomfortable or embarrassing?’ I found a lot of the language quite patronising.

Reviewer 6 – Seems straightforward and easy to understand, clearly laid out. Being picky, I don’t like the use of ‘so therefore’ in the paragraph about disadvantages and risks. It’s clumsy and unnecessary to use both words.

Reviewer 7 – Yes but I think it might interest people more if you clarified what ‘vascular services’ comprises. Is it surgery, medicine and radiology? You might also consider encouraging potential subjects by telling them how their responses will make a difference.

Reviewer 8 – A very clear and logical information sheet. I cannot see anything that would need altering other than the disadvantages and risks involved section.

Reviewer 9 – Perhaps define ‘vascular’ slightly sooner. The document is understandable and clear. It is lengthy; however, I believe all the information is necessary.

Reviewer 10 – yes.

Reviewer 11 – I’m happy that it’s all written in a manner that’s easy to understand.

Reviewer 12 – The language is fine.

If you were given this document in clinic, would you have any questions for the researchers after reading this document?

Reviewer 1 – No.

Reviewer 2 – It says that they would be sent documents to prepare for the interview. Would they be long and time consuming to read, as this may not be possible for people who are very busy and wouldn’t have that much time to read long documents, therefore maybe making it an inconvenience and put them off.

Reviewer 3 – Yes as stated above.

Reviewer 4 – How can questions relating to hypothetical conditions and situations help to inform provision of a specific set of services for specific conditions? Wouldn’t it be better to ask those patients who already use them? Where are the locked cabinets for storing transcripts kept?

Reviewer 5 – I would be very worried about confidentiality I don’t find what has been written is reassuring in any way whatsoever. You need to be very specific about coding procedures and how all identifiers are removed. You need to state how researchers are monitored and what their access procedures are. Most patients are happy to give a researcher plenty of information about themselves just as long as they, the patient, is not identifiable.

Reviewer 6 – I still don’t understand why you want healthy volunteers with no interest in the service, I know what you want, and how it is carried out, and that it is part of a much larger study, but why would my opinion be valuable?

Reviewer 7 – I think the main question would be around the arrangements for the interview. Can it be done at the weekend or in the evening? If the subject has to travel are you facilitating this by paying their expenses? If I was sitting in a clinic waiting area reading this I’d like to know if the interview could be done during that visit to the hospital. This would benefit you because as they leave hospital they’ll forget all about the request to be involved.

Reviewer 8 – Is there a need for this study to decide where certain vascular services will be situated and structured in Sheffield because there will be some remodeling and moving? What do you expect to understand from the trade-off technique? How do my details, such as occupation, help the study? Why are you using healthy volunteers and not people with vascular disease states?

Reviewer 9 – I might wish for the researchers to elaborate on the meaning of ‘trade-off’ technique.

Reviewer 10 – yes, I would want to know more about ‘the broad structure of the interviews will be as follows:’ as I would be intrigued!

Reviewer 11 – If I have any other health conditions (i.e. not vascular), would this affect my eligibility to take part in the research? How many participants do you hope to interview? Do you have any links to the ‘larger research study’ you mention on the first page? Are there any factors that determine whether a phone interview or a face-to-face interview is conducted? Would I be able to read the transcript of my interview (after it’s been written up), such that I can confirm that it gives a true representative view of my interview?

Reviewer 12 – Why me? How can I possibly comment on something I know nothing about?

Section 3: do you have any other comments you would like to feedback to the researcher?

Reviewer 1 – None.

Reviewer 2 – None.

Reviewer 3 – None.

Reviewer 4 – None.

Reviewer 5 – You have decided that distance to the vascular service as a key factor, I would suggest most patients would consider local transport links and parking issues at a site are more important than distance

Reviewer 6 – None.

Reviewer 7 – None.

Reviewer 8 – None.

Reviewer 9 – The information looks thorough and clear.

Reviewer 10 – If you are going to tease the participant with the last section, either be more specific with what it entails, or leave it out altogether until the day. If you have any questions that you would like to ask the researcher regarding their project, please include them here.

Reviewer 11 – I think this is a really important project, especially given the aim is to assess current vascular treatment provision, and suggest improvements. I’d be very keen to be involved in the study. I wish you every success.

Reviewer 12 – None.

The design, development and commissioning of patient focused vascular services: public preferences for vascular treatment