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For peer review only HEALTH ECONOMIC BURDEN THAT WOUNDS IMPOSE ON THE NATIONAL HEALTH SERVICE IN THE U.K. Journal: BMJ Open Manuscript ID: bmjopen-2015-009283 Article Type: Research Date Submitted by the Author: 01-Jul-2015 Complete List of Authors: Guest, Julian; Catalyst Health Economics Consultants, ; King's College London, Ayoub, Naria; Catalyst Health Economics Consultants, Mcilwraith, Tracey; Catalyst Health Economics Consultants, Uchegbu, Ijeoma; Catalyst Health Economics Consultants, Gerrish, Alyson; Catalyst Health Economics Consultants, Weidlich, Diana; Catalyst Health Economics Consultants, Vowden, Kathryn; Bradford Teaching Hospitals NHS Foundation Trust, Vowden, Peter; Bradford Teaching Hospitals NHS Foundation Trust, <b>Primary Subject Heading</b>: Health economics Secondary Subject Heading: Epidemiology, General practice / Family practice, Health economics, Health policy Keywords: WOUND MANAGEMENT, HEALTH ECONOMICS, Health economics < HEALTH SERVICES ADMINISTRATION & MANAGEMENT For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml BMJ Open on March 4, 2021 by guest. Protected by copyright. http://bmjopen.bmj.com/ BMJ Open: first published as 10.1136/bmjopen-2015-009283 on 7 December 2015. Downloaded from

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Page 1: HEALTH ECONOMIC BURDEN THAT WOUNDS IMPOSE ON THE … · wound-related health outcomes and all healthcare resource use were quantified and the total NHS cost of patient management

For peer review only

HEALTH ECONOMIC BURDEN THAT WOUNDS IMPOSE ON

THE NATIONAL HEALTH SERVICE IN THE U.K.

Journal: BMJ Open

Manuscript ID: bmjopen-2015-009283

Article Type: Research

Date Submitted by the Author: 01-Jul-2015

Complete List of Authors: Guest, Julian; Catalyst Health Economics Consultants, ; King's College London, Ayoub, Naria; Catalyst Health Economics Consultants, Mcilwraith, Tracey; Catalyst Health Economics Consultants, Uchegbu, Ijeoma; Catalyst Health Economics Consultants, Gerrish, Alyson; Catalyst Health Economics Consultants, Weidlich, Diana; Catalyst Health Economics Consultants, Vowden, Kathryn; Bradford Teaching Hospitals NHS Foundation Trust,

Vowden, Peter; Bradford Teaching Hospitals NHS Foundation Trust,

<b>Primary Subject Heading</b>:

Health economics

Secondary Subject Heading: Epidemiology, General practice / Family practice, Health economics, Health policy

Keywords: WOUND MANAGEMENT, HEALTH ECONOMICS, Health economics < HEALTH SERVICES ADMINISTRATION & MANAGEMENT

For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml

BMJ Open on M

arch 4, 2021 by guest. Protected by copyright.

http://bmjopen.bm

j.com/

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J Open: first published as 10.1136/bm

jopen-2015-009283 on 7 Decem

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ORIGINAL RESEARCH

HEALTH ECONOMIC BURDEN THAT WOUNDS

IMPOSE ON THE NATIONAL HEALTH SERVICE IN THE U.K.

1,2Julian F Guest,

1Nadia Ayoub,

1Tracey Mcilwraith,

1Ijeoma Uchegbu,

1Alyson Gerrish,

1Diana Weidlich,

3Kathryn Vowden,

3Peter Vowden

1Catalyst Health Economics Consultants, Northwood, Middlesex, U.K.;

2Faculty of Life

Sciences and Medicine, King’s College, London, U.K.; 3Bradford Teaching Hospitals

NHS Foundation Trust and University of Bradford, U.K.

Correspondence to:

Professor Julian F Guest

CATALYST Health Economics Consultants

34b High Street

Northwood

Middlesex HA6 1BN

U.K.

Tel: +44 (0) 1923 450045

Fax: +44 (0) 1923 450046

E-mail: [email protected]

Running title: Annual NHS cost of managing wounds in the U.K.

Keywords: Burden, cost, wounds, ulcers, U.K.

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ABSTRACT

Objective: To estimate the prevalence of wounds managed by the U.K.’s National Health

Service (NHS) in an average year and the annual levels of healthcare resource use attributable

to their management and corresponding costs.

Methods: This was a retrospective cohort analysis of the records of patients in The Health

Improvement Network (THIN) Database (a nationally representative database of patients

registered with general practitioners in the U.K.). 1,000 records of adult patients who had a

wound during 2012/13 (cases) were randomly selected from the database and matched with

1,000 patients with no previous history of a wound (controls). Patients' characteristics,

wound-related health outcomes and all healthcare resource use were quantified and the total

NHS cost of patient management was estimated at 2013/14 prices.

Results: Patients’ mean age was 69.0 years and 45% were male. 76% of patients presented

with a new wound in the study year and 61% of wounds healed during the study year.

Nutritional deficiency (Odds ratio 0.534; p <001) and diabetes (Odds ratio 0.651; p<001)

were independent risk factors for non-healing. The study estimated that 2.2 million wounds

were managed by the NHS (equivalent to 4% of the adult population in the U.K.) in 2012/13.

Annual levels of resource use attributable to managing 2.2 million wounds and associated

comorbidities included 18.6 million practice nurse visits, 10.9 million community nurse

visits, 7.7 million GP visits and 3.4 million hospital outpatient visits. The annual NHS cost of

managing 2.2 million wounds and associated comorbidities was £5.3 billion. After adjusting

for the cost of managing comorbidities, this was reduced to £4.8 billion. Sixty-six percent of

the cost was attributable to management in the community and the remainder in secondary

care. However, 48% and 78% of the cost of managing acute and chronic wounds respectively

was incurred in the community and the remainder in secondary care.

Conclusion: This real world evidence highlights that wound management is predominantly a

nurse-led discipline. Approximately 30% of wounds lacked a differential diagnosis,

indicative of the practical difficulties experienced by non-specialist clinicians in the

community. Wounds impose a substantial health economic burden on the U.K.’s NHS,

comparable to that of managing obesity (£5.0 billion) and should be given similar priority.

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Strengths and Limitations of this Study

• This study estimated the health outcomes, resource implications and associated costs

attributable to managing wounds in an average year using real world evidence obtained

from the THIN database (a nationally representative database of clinical practice among

9 million patients registered with general practitioners in the U.K.).

• The estimates were derived following a systematic analysis of patients' characteristics,

wound-related health outcomes and all community-based and secondary care resource

use contained in the patients' electronic records.

• Computerised information in the THIN database is collected by GPs for clinical care

purposes and not for research. Additionally, prescriptions issued by GPs and practice

nurses are recorded in the database, but it does not specify whether the prescriptions

were dispensed or patient compliance with the product.

• The analysis does not consider the potential impact of those wounds that remained

unhealed beyond the study period. Nor does it consider the potential impact of managing

patients with wounds being cared for in nursing homes. The THIN database may have

under-recorded use of some healthcare resources outside the GP’s surgery. However, the

impact of this was addressed in sensitivity analyses.

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Funding

This study was commisioned and funded by the NIHR Wound Prevention and Treatment

Healthcare Technology Co-operative (NIHR WoundTec HTC), Bradford Institute For Health

Research, Bradford, West Yorkshire, U.K. following an open tendering process. Additional

funding was provided by 3M Limited, Loughborough, Leicestershire, U.K.; Activa

Healthcare Limited, Burton On Trent, Staffordshire, U.K.; Blanson Limited, Narborough,

Leicestershire, U.K.; Brightwake Limited, Kirkby In Ashfield, Nottinghamshire, U.K.; KCI

Medical Limited, Crawley, West Sussex, U.K.; Medira Ltd, Cambridge, Cambridgeshire,

U.K.; Molnlycke Health Care Limited, Dunstable, Bedfordshire, U.K.; Park House

Healthcare Limited, Elland, West Yorkshire, U.K.; Perfectus Biomed Ltd, Daresbury,

Warrington, U.K.; Smith & Nephew Medical Limited, Hull, East Riding Of Yorkshire, U.K.;

Sozo Woundcare Limited, Harrogate, North Yorkshire, U.K.; Systagenix Wound

Management Limited, Gatwick Airport, West Sussex, U.K.; Urgo Limited, Loughborough,

Leicestershire, U.K.; Willingsford Limited, Southampton, Hampshire, U.K.

The views expressed in this article are those of the authors and not necessarily those of the

NHS, the NIHR, the Department of Health or any of the other sponsors.

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Authors' Contribution

J.F.G. designed the study, managed the analyses, performed some analyses, checked all the

other analyses, and wrote the manuscript.

N.A. and T.M conducted much of the analyses.

I.U. and A.G conducted some of the analyses.

D.W. scrutinized the analyses and edited the manuscript.

K.V and P.V scrutinized the analyses, suggested further analyses, helped interpret some of

the findings, and edited the manuscript.

J.F.G. is the guarantor of this work and, as such, had full access to all the data in the study

and takes responsibility for the integrity of the data and the accuracy of the data analysis.

The analyses have also been reviewed by the following strategic partners of the NIHR

Bradford Wound Prevention & Treatment Healthcare Technology Co-operative

(www.woundtec.htc.nihr.ac.uk): Prof Andrea Nelson, Head of School of Healthcare,

University of Leeds, Leeds; Prof Jane Nixon, Deputy Director, Leeds Institute of Clinical

Trials Research, Leeds; Professor Dan L Bader, Faculty of Health Sciences, University of

Southampton, Southampton; Dr Patricia Grocott, Reader in Palliative Wound Care

Technology Transfer, King's College, London; Hussein Dharma, Project Manager, NIHR

WoundTec Healthcare Technology Co-operative, Bradford Institute for Health Research,

Bradford.

The Corresponding Author has the right to grant on behalf of all authors and does grant on

behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in

all forms, formats and media (whether known now or created in the future), to i) publish,

reproduce, distribute, display and store the Contribution, ii) translate the Contribution into

other languages, create adaptations, reprints, include within collections and create summaries,

extracts and/or, abstracts of the Contribution and convert or allow conversion into any format

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including without limitation audio, iii) create any other derivative work(s) based in whole or

part on the on the Contribution, iv) to exploit all subsidiary rights to exploit all subsidiary

rights that currently exist or as may exist in the future in the Contribution, v) the inclusion of

electronic links from the Contribution to third party material where-ever it may be located;

and, vi) licence any third party to do any or all of the above.

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INTRODUCTION

Patients requiring wound care can be found in the community, secondary care and in long-

term care institutions and range from infants to the elderly. The patient population with

wounds is managed across the spectrum of different healthcare disciplines that includes

general practice, specialist physicians, surgeons, nurses and allied healthcare practitioners,

such as podiatrists [1-3].

Wound care should be viewed as a specialised segment of healthcare that requires clinicians

with specialist training to diagnose and manage appropriately. However, the evidence

suggests this is not the case [1-3], Moreover, it has been suggested that better wound care,

such as effective diagnosis and treatment and effective prevention of wound complications

would help minimise treatment costs. Studies have highlighted that there is potential for

better patient management and wound care product selection that would improve outcomes

and reduce costs [1-5].

There have been previous attempts to estimate the costs and burden associated with wound

management. However, they were based on published literature or broad estimates derived

from incidence or prevalence rates and extrapolations from relatively small-scale studies. The

objectives of the present study were to estimate: the annual prevalence of wounds and annual

number of wounds that are treated by the U.K.'s National Health Service (NHS); the annual

amount of NHS resource use that is utilised on wound management; and the amount the NHS

spends on managing wounds in an average year. The remit of this study was limited to open

external acute and chronic cutaneous wounds. Surgical wounds healing within four weeks

were excluded as cost were considered to be related to the surgery and not to ongoing wound

complications.

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METHODS

Study Design

This was a retrospective cohort analysis of the records of patients in The Health

Improvement Network (THIN) Database.

The Health Improvement Network (THIN) Database

The THIN database (Cegedim, London, U.K.) contains computerised information on 9

million anonymised patients entered by GPs from 500 practices across the U.K. General

practices across the U.K. using Vision Practice Management Software are invited to

participate in the database and are self-selecting. The patient data within THIN have been

shown to be representative of the U.K. population in terms of demographics and disease

distribution [6]. Read codes are a coded thesaurus of clinical terms that have been in use in

the NHS since 1985 [7], and have been used to code specific diagnoses in the THIN database.

A drug dictionary based on data from the Multilex classification has been used to code drugs

in the database. Successive updates of patients’ records to the database include any

subsequent changes made by GPs.

The computerised information in the THIN database includes patients’ demographics, details

from GP consultations, specialist referrals, nurse and other clinician visits, hospital

admissions, diagnostic and therapeutic procedures, laboratory tests, and prescriptions issued

in primary care that are directly generated by the general practice’s information technology

system. Hence, the information contained in the THIN database reflects real clinical practice,

as it is based on actual patient records. Moreover, GPs are the gatekeepers to health care in

the U.K., and patients’ entire medical history is theoretically stored in their primary care

record.

Study Population

The study population comprised the anonymised case records of a randomly selected cohort

of 1,000 patients from the THIN database who had a wound between 1 May 2012 and 30

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April 2013 (cases) and a randomly selected cohort of 1,000 control patients (controls) from

the database, who were matched with the cases according to age, gender, and the patient's

general practice.

Inclusion criteria for the cases were:

• Had to be ≥18 years of age or over.

• Had to have a Read code for a wound.

• Had to have continuous medical history in their case record from the first mention of a

wound in the study year up to the time the data was extracted from the database, unless

they died, in order to exclude patients who had moved or changed their general practice.

Exclusion criteria for the cases were:

• Patients with a surgical wound if they healed within four weeks of the surgical procedure

(since any resource use incurred will be due to the surgical procedure and not the wound).

• Patients with a dermatological tumour.

1,000 control patients were matched with 1,000 cases according to the following criteria:

• Age.

• Gender.

• Being managed at the same general practice.

• No history of a wound in their medical record at anytime.

• Had continuous medical history in their case record from the matched start date up to the

time the data was extracted from the database unless they died.

Sample Size

The sample size was 1,000 patients in each group. It is notoriously difficult to power a cost of

illness study where the outcome is the use of different resources or a range of morbidities

which are as yet unknown. Based on the Authors’ previous cost of illness studies, a sample

size of 1,000 patients in each group was considered sufficiently large to detect the differences

in resource use between the groups with 95% power and a Type I (alpha) error of 0.05.

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Ethics Approval

Ethics approval to use patients’ records from the THIN database for this study was obtained

from Cegedim's Research Ethics Committee that appraises studies using the THIN database

(Reference number 13-061).

Study Variables and Statistical Analyses

Information was systematically extracted from the patients’ records over the study period

according to the protocol approved by the ethics committee. Wound type was documented in

the patients' records and the Authors categorised them as being either acute (i.e. abscess,

burn, open wound, unhealed surgical wound, trauma) or chronic (i.e. diabetic foot ulcer,

arterial leg ulcer, mixed leg ulcer, venous leg ulcer, pressure ulcer).

Patients' characteristics, wound-related health outcomes and all community-based and

secondary care resource use were extracted from the electronic records. All the data was

quantified for cases and controls and stratified according to wound type. Differences between

the groups were tested for statistical significance using either a Mann-Whitney U-test or a

Chi-Square test.

Logistic regression was used to investigate relationships between baseline variables and

clinical outcomes. Multiple linear regression was also used to assess the impact of patients’

baseline variables on resource use and clinical outcomes. All statistical analyses were

performed using IBM SPSS Statistics (version 21.0; IBM Corporation).

Health Economic Modeling

Using the THIN data set, a computer-based model was constructed depicting the treatment

pathways and associated management of the 1000 patients with a wound and the 1000

matched patients who had never had a wound. The model spans the 12 months period from 1

May 2012 to 30 April 201.

Unit costs at 2013/14 prices [8-10] were applied to the resource use in the model to estimate

the total NHS cost of patient management from the time a patient entered the data set (i.e.

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from the 1 May 2012 or the start time of their wound if it occurred later, and the equivalent

date in the matched control) up to the time their wound healed or the end of the study period,

whichever came first. Differences between cases and controls were considered to be

attributable to wound care and associated comorbidities.

Sensitivity Analyses

Deterministic sensitivity analyses were performed on all of the model’s inputs to identify

how the cost of wound management and associated comorbidities would change by varying

the different parameters in the model.

Two methods were used to adjust for the cost of managing patients’ comorbidities.

1. The first involved generating an incremental cost among control patients between those

who had no comorbidities and those who had one, two, three, four or five or more

comorbidities. These incremental costs were then applied to both groups so that all the

patients were modelled to have the maximum number of comorbidities. The resulting

cost difference between the two groups was considered to be solely due to the wounds.

2. The second method involved the removal of a case-control match from the analysis if

they did not have the same number of comorbidities. The resulting cost difference

between the two groups was considered to be solely due to the wounds.

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RESULTS

Patients' Characteristics

Patients' mean age in the cases and controls was 69.0 and 67.3 years respectively and 55% of

patients in both groups were female. Mean blood pressure was 133/76 in the cases and 132/77

in the controls. Additionally, patients' BMI was a mean 29.0 kg/m2 and 26.1 kg/m

2 in the

cases and controls respectively. 18% of the cases were smokers, 39% were non-smokers and

40% were ex-smokers. In the controls, 17% were smokers, 47% were non-smokers and 32%

were ex-smokers. 76% of cases presented with a new wound in the study year.

Significantly more patients with a wound (94%) than control patients (77%) had at least one

chronic comorbidity in the year before the start of their wound. Moreover, the mean number

of comorbid conditions in the cases was 3.9 per patient compared to 2.1 per patient in the

controls. The percentage of patients with different chronic comorbidities in the year before

the start of their wound (and not necessarily the year before the start of the study) is

summarised in Table 1.

Insert Table 1

Binary logistic regression suggests that the following comorbidities were independent risk

factors for developing a wound:

• Dermatological symptoms: Odds ratio 3.26 (95% CI: 2.66; 4.00); p < 0.001.

• Nutritional deficiency: Odds ratio 2.30 (95% CI: 1.80; 2.95); p < 0.001.

• Musculoskeletal disease: Odds ratio 1.62 (95% CI: 1.29; 2.03); p < 0.001.

• Cardiovascular disease: Odds ratio 1.35 (95% CI: 1.09; 1.67); p = 0.005.

• Gastrointestinal disease: Odds ratio 1.32 (95% CI: 1.06; 1.64); p = 0.015.

Prevalence of Wounds in the U.K.

The base population of active patients in the THIN database in 2012/13 was 3.9 million, from

which there were an estimated 135,000 patients with a wound that matched the study

protocol's inclusion and exclusion criteria. When this was extrapolated to the whole U.K.

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population (63.7 million people in mid-2013), it was estimated that there were 2.2 million

patients with a wound, equivalent to 4% of the adult population, in the study year (Table 2).

12% of all wounds had no diagnosis and it was not possible to infer a wound type from the

patients' records. Additionally, 19% of all wounds were a leg ulcer without any further

characterisation (i.e. venous, arterial or mixed). In total, there were 730,000 leg ulcers, which

equates to 1.5% of the adult population having a leg ulcer in the study year. The number of

diagnosed venous leg ulcers (278,000) indicates that 1 in 170 adults had such an ulcer in the

study year. There were also an estimated 169,000 diabetic foot ulcers, which equates to 5% of

adult diabetic patients having a foot ulcer in the study year, of which 66% were male.

Insert Table 2

Clinical Outcomes

61% of all wounds healed in the study year; 79% of acute wounds healed and 43% of chronic

wounds. Binary logistic regression suggests that nutritional deficiency (Odds ratio 0.53 (95%

CI: 0.41; 0.70); p < 0.001) and diabetes (Odds ratio 0.65 (95% CI: 0.50; 0.85); p < 0.001)

were independent risk factors for non-healing during the study period. Additionally, 4% of

patients with a wound and 1% of control patients died in the study year.

Health Care Resource Use Associated with Patient Management

Patients in both groups were predominantly managed in the community by GPs and nurses.

Table 3 summarises the percentage of patients in each group who utilised different resources

during the study year.

Insert Table 3

Table 4 shows the annual number of resources associated with managing 2.2 million patients

with a wound and 2.2 million control patients. The differences were considered to be the

incremental amounts of resource use attributable to managing 2.2 million wounds and

associated comorbidities and included 18.6 million practice nurse visits, 10.9 million

community nurse visits, 7.7 million GP visits, 3.4 million hospital outpatient visits, 97.1

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million drug prescriptions, 262.2 million dressings, 73.4 million bandages and 9.0 million

compression bandages. Assessment of peripheral perfusion is a recognised requirement for

leg ulcer and diabetic foot management, yet only 16% of all cases with a leg or foot ulcer had

a Doppler ankle brachial pressure index recorded in their records.

Insert Table 4

The total annual NHS cost of managing 2.2 million patients with a wound was estimated to

be £6.0 billion (Table 5). The corresponding cost of managing the matched controls was £0.7

billion. Hence the total annual NHS cost of managing 2.2 million wounds and associated

comorbidities was estimated to be £5.3 billion. Of this, £1.65 billion and £3.67 billion was

associated with managing those wounds that healed and remained unhealed respectively.

Insert Table 5

66% of the total annual NHS cost was incurred in the community and the remainder in

secondary care. However, the distribution of costs varied according to wound type, with 48%

and 72% of the total annual NHS cost of managing acute and chronic wounds respectively

being incurred in the community and the remainder in secondary care.

Sensitivity Analyses

The estimated amounts of individual resource use were reduced and increased by 25%.

However, this only affected the total annual NHS cost of managing 2.2 million wounds and

associated comorbidities by 6% or less.

When the cost of surgery was excluded from the cost of managing patients with an unhealed

surgical wound, the total annual NHS cost of managing 2.2 million wounds and associated

comorbidities was reduced from £5.3 billion to £4.8 billion.

When the NHS cost of managing patients was adjusted for their comorbidities, the total

annual NHS cost of managing 2.2 million wounds was reduced from £5.3 billion to £5.1

billion when method 1 was used and to £4.5 billion when method 2 was used. Hence, the total

annual NHS cost of managing the comorbidities among 2.2 million patients with a wound

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was estimated to be between £250 and £788 million. After adjusting for comorbidities, the

total annual NHS cost of managing healed wounds and unhealed wounds was estimated to be

£1.53 billion and £3.49 billion respectively.

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DISCUSSION

This study estimated the health outcomes, resource implications and associated costs

attributable to managing wounds in an average year. After adjustment for comorbidities, the

annual NHS cost of managing wounds was estimated to be £4.5-5.1 billion, two-thirds of

which is incurred in the community and the rest in secondary care. This is comparable to the

annual NHS cost of managing obesity which was estimated at £5.0 billion in 2013 [11].

For patients to be included in the data set, they had to have had a wound in the study year or

be matched to these patients on the basis of their age, sex, the same general practice, and no

evidence of a wound in their medical history. Patients in both groups were managed primarily

by clinicians in the community. Only half the patients with a wound saw a hospital physician

although consultation may not have been wound related. However, the evidence shows that

wound management is predominantly a nurse-led discipline. Approximately 30% of wounds

lacked a differential diagnosis. This may be indicative of the practical difficulties esperienced

by non-specialist healthcare professionals in the community with establishing a working

diagnosis. Moreover, it appears that only 16% of patients with a leg or foot ulcer had a

Doppler. Hence, these findings suggest (1) the need to refer patients to a specialist for

investigation and a differential diagnosis and a shared management plan to be implemented in

the community and (2) training of non-specialist clinicians in the fundamentals of wound

management. These two measures should help overcome some of the problems encountered

in clinical practice and achieve better health outcomes, thereby reducing the high levels of

resource use and corresponding costs, and improving compliance with appropriate NICE and

best practice guidelines. The study highlighted that despite being a nurse-led discipline, there

is a lack of involvement of tissue viability nurses and other specialist nurses in the

management of patients with wounds. Recent articles [12,13] highlight the lack of a clear

definition, and therefore confusion regarding the role of these nurses.

The wound patients had significantly more comorbidities than their matched controls.

However, it was surprising to find such a high level of illness among the controls. For

example, 53% had cardiovascular disease. Moreover, 34% of patients with a wound and 13%

of controls had nutritional deficiency that warranted supplementation with clinical nutritional

formulae. The THIN data set in this study covers the period 2012/13 and comprises patients

with a wide age range (19 to 98 years), so this level of illness may be a proxy for the health of

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a proportion of the general population at that time. Furthermore, the presence of nutritional

deficiency was an independent risk factor for wound non-healing. Hence, community-

prevention of patients developing nutritional deficiency should help improve healing rates

following the onset of a wound. Moreover, if patients’ wounds and their comorbidities were

treated more holistically with appropriate involvement of allied healthcare professionals,

rather than just focusing on the wounds, better health outcomes might be achieved at lower

cost.

Other studies have assessed the prevalence and costs of wound care. A district-wide survey in

the Bradford and Airedale area of the U.K. estimated the annual NHS cost of wound care to

be £2.0 million per 100,000 population [14], which equates to £1.27 billion for the U.K. as a

whole. In another study, the NHS cost of caring for patients with a chronic wound was

estimated to be £2.3-3.1billion per year at 2005/06 prices [15]. Previous prevalence studies

suggest there may be up to 190,000 individuals with a venous leg ulcers in the U.K. at any

time [15]. However, this is likely to be an underestimate as our analysis estimated that the

NHS manages 278,000 venous leg ulcers per annum plus an additional 420,000 unspecified

leg ulcers (i.e. those lacking a true working diagnosis), some of which will undoubtedly be

venous in origin. The prevalence of pressure ulcers has been previously estimated to be 0.103

in 2005/06 [16], and another study estimated the incidence to be 400,000 new pressure ulcers

per annum in the U.K. [15]. These figures are substantially higher than our estimate of the

NHS managing 153,000 pressure ulcers per annum. The difference may be due to people

residing in nursing homes not having been included in our study. It may also be due to under-

recording of pressure ulcers in patients' records and/or an over-estimation in the previous

studies, and/or a lower prevalence in 2012/13 than 2005/06. The present study also estimated

that 5% of patients with diabetes have a foot ulcer which is consistent with other estimates

[17].

The advantage of using the THIN database is that the patient pathways and associated

resource use are based on real world evidence derived from clinical practice. However, health

outcomes and resource use, whilst collected prospectively, were analysed retrospectively.

Hence, confounding factors may exist. While the study results are compelling, the analyses

were based on clinicians’ entries into their patients’ records and inevitably subject to a certain

amount of imprecision and lack of detail. Moreover, the computerised information in the

THIN database is collected by GPs for clinical care purposes and not for research.

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Prescriptions issued by GPs and practice nurses are recorded in the database, but it does not

specify whether the prescriptions were dispensed or patient compliance with the product.

Despite these limitations, it is the Authors’ opinion that the THIN database affords one of the

best sources of real world evidence for clinical practice in the U.K.

The analysis does not consider the potential impact of those wounds that remained unhealed

beyond the study period, nor does it consider the potential impact of managing patients with

wounds being cared for in nursing/residential homes. The THIN database may have under-

recorded use of some healthcare resources outside the GP’s surgery if not documented in the

GP records, such as home visits made by clinicians, hospital outpatient visits, hospital

admissions and accident and emergency attendances. The impact of this was addressed in

sensitivity analyses. The analysis excludes hospital-based prescribing, but this should have

minimal impact on the results since most prescribing is undertaken by GPs and nurses in the

community.

The analysis only considered the annual cost of NHS resource use for the “average patient,”

and no attempt was made to stratify resource use and costs according to gender,

comorbidities, wound size, wound severity, and other disease-related factors. Also excluded

were the costs incurred by patients and indirect costs incurred by society as a result of

patients taking time off work. However, patients’ mean age was >65 years, so it is unlikely

that many were in employment.

Notwithstanding the study's limitations, the real world evidence in our study demonstrates

that wounds impose a substantial health economic burden on the U.K.’s NHS, comparable to

that of managing obesity and should be given similar priority.

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CONFLICTS OF INTEREST

The authors have no potential conflicts of interest relevant to this article.

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REFERENCES

1. Guest JF, Taylor RR, Vowden K, Vowden P. Relative cost-effectiveness of a skin

protectant in managing venous leg ulcers in the UK. Journal of Wound Care 2012;

21(8): 389-398.

2. Panca M, Cutting K, Guest JF. Clinical and cost-effectiveness of absorbent dressings in

the treatment of highly exuding VLUs. Journal of Wound Care 2013; 22(3): 109-118.

3. Guest JF, Gerrish A, Ayoub N, Vowden K, Vowden P. Clinical outcomes and cost-

effectiveness of using a two-layer cohesive compression bandage compared with a two-

layer compression system and a four-layer compression system in clinical practice in

the UK. Journal of Wound Care 2015; Accepted for publication.

4. Guest JF, Charles H, Cutting K. Is it time to re-appraise the role of compression in non-

healing venous leg ulcers? Journal of Wound Care 2013;22(9):453-60.

5. National Institute for Health and Care Excellence. NICE advice [KTT14] January 2015.

Available on line at: https://www.nice.org.uk/advice/ ktt14/chapter/Evidence-context.

Accessed 14 May 2015.

6. Blak BT, Thompson M, Dattani H, Bourke A. Generalisability of The Health

Improvement Network (THIN) database: demographics, chronic disease prevalence and

mortality rates. Informatics in Primary Care 2011;19:251–255.

7. Read Codes. Department for Health. 2010. Available from

http://systems.hscic.gov.uk/data/uktc/readcodes. Accessed 12 May 2015.

8. Department of Health. NHS reference costs 2013/14 [article online]. Available from

https://www.gov.uk/government/publications/nhs-reference-costs-2013-to-2014.

Accessed 25 April 2015.

9. Curtis L. Unit Costs of Health and Social Care 2014. Canterbury: University of Kent.

Personal Social Services Research Unit, 2014. Available from http://www.pssru.ac.uk/

project-pages/unit-costs/2014. Accessed 25 April 2015.

10. Drug Tariff 2014. Available from https://www.drugtariff.co.uk. Accessed 25 April

2015.

11. Royal College of Physicians 2013. Action on obesity: Comprehensive care for all

Report of a working party January 2013. Available on line at

http://www.evidence.nhs.uk/search?q=obesity%20AND%20costs%20nhs. Accessed 26

April 2015.

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12. Ousey K, Atkin L, Milne J, Henderson V. The Changing Role of the Tissue Viability

Nurse: an exploration of this multifaceted role. Wounds UK 2014; 10 (4): 54–61.

13. Ousey K, Milne J, Atkin L, Henderson V, King N, Stephenson J. Exploring the role of

the Tissue Viability Nurse. Wounds UK (EWMA Special) 2015; 36-45.

14. Vowden K, Vowden P, Posnett J. The resource cost of wound care in the Bradford and

Airedale primary care trust in the UK. Journal of Wound Care 2009; 18(3): 93-102.

15. Posnett J, Franks P. The burden of chronic wounds in the UK. Nursing Times 2008;

104(3): 44-5.

16. Philips, L. & Busby J. Pressure Ulcer Epidemiology in the UK: 2005-2006. Poster

Presentation at Wounds UK 2006.

17. Diabetes in the UK 2012: Key statistics on diabetes Available on line at:

http://www.diabetes.org.uk/About_us/What-we-say/Statistics/Diabetes-in-the-UK-

2012. Accessed 12 May 2015.

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Percentage of patients

Comorbidity Cases Controls p value

Cardiovascular 73% 53% <0.005

Dermatological 59% 25% <0.001

Endocrinological 45% 27% <0.01

Gastroenterological 43% 25% <0.01

Immunological 3% 0% ns

Musculoskeletal 37% 19% <0.005

Neurological 23% 13% ns

Nutritional deficiency 34% 13% <0.001

Other 14% 7% ns

Psychiatric 31% 18% <0.05

Respiratory 28% 15% ns

None 6% 23% <0.001

Table 1: Percentage of patients with a comorbidity in the year

before the start of their wound.

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Annual number of

wounds

Annual prevalence among

the adult U.K. population

Abscess 160,000 (7%) 0.0032

Burn 87,000 (4%) 0.0018

Diabetic foot ulcer 169,000 (8%) 0.0034

Leg ulcer (arterial) 9,000 (<1%) 0.0002

Leg ulcer (mixed) 24,000 (1%) 0.0005

Leg ulcer (unspecified) 420,000 (19%) 0.0085

Leg ulcer (venous) 278,000 (13%) 0.0056

Open wound 240,000 (11%) 0.0048

Pressure ulcer 153,000 (7%) 0.0031

Surgical wound 253,000 (11%) 0.0051

Trauma 158,000 (7%) 0.0032

Unspecified 271,000 (12%) 0.0055

Total 2,222,000 (100%) 0.0447

Table 2: Annual number and prevalence of different wound types

in the U.K. among the adult population (i.e. ≥≥≥≥ 18 years of age).

Percentage of total number of wounds is in parentheses.

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Percentage of patients

Resource Cases Controls p value

GP visits 86% 47% <0.001

Practise nurse visits 72% 29% <0.001

Community nurse visits 75% 2% <0.001

Specialist nurse visits 2% <1% ns

Allied healthcare visits 14% 3% 0.005

Hospital outpatient visits 53% 18% <0.001

Hospital admissions and day cases 29% 6% <0.001

Ambulance services <1% <1% ns

Accident and emergency attendances <1% <1% ns

Diagnostic tests 80% 45% <0.001

Non-wound care devices 36% 5% <0.001

Wound care products 100% 0% <0.001

Prescriptions for individual drugs 98% 72% <0.001

Table 3: Percentage of patients who utilised resources in the study year.

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Annual number

Resource Cases Controls Difference p value

GP visits 10,816,655 3,124,120 7,692,535 <0.001

Practise nurse visits 19,744,618 1,184,322 18,560,296 <0.001

Community nurse visits 10,932,199 75,548 10,856,651 <0.001

Specialist nurse visits 51,106 4,444 46,662 <0.001

Allied healthcare visits 537,722 77,770 459,952 <0.001

Hospital outpatient visits 4,277,334 828,803 3,448,531 <0.001

Hospital admissions and day cases 1,142,104 173,315 968,788 <0.001

Ambulance services 11,110 2,222 8,888 ns

Accident and emergency attendances 11,110 11,110 - ns

Diagnostic tests 60,284,855 24,068,613 36,216,242 <0.001

Devices 320,938,916 48,206,108 272,732,808 <0.001

Wound care products 354,954,275 13,332 354,940,943 <0.001

Prescriptions for individual drugs 135,859,234 38,769,310 97,089,924 <0.001

Table 4: Annual amount of NHS resource use attributable to managing 2.2 million patients with

a wound and 2.2 million matched controls.

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Annual cost

Resource Cases Controls Difference

GP visits £514,993,223 £145,951,520 £369,041,702

Practise nurse visits £256,760,021 £15,396,180 £241,363,841

Community nurse visits £682,382,518 £3,026,353 £679,356,166

Specialist nurse visits £3,650,732 £322,189 £3,328,543

Allied healthcare visits £34,451,980 £4,859,496 £29,592,485

Hospital outpatient visits £515,002,111 £99,947,406 £415,054,705

Hospital admissions and day cases £1,334,299,309 £135,277,073 £1,199,022,237

Ambulance services £2,555,290 £511,058 £2,044,232

Accident and emergency attendances £666,597 £666,597 £0

Diagnostic tests £282,646,224 £113,238,466 £169,407,758

Devices £282,261,975 £17,525,292 £264,736,682

Wound care products £742,703,819 £185,181 £742,518,638

Prescriptions for individual drugs £1,390,246,214 £187,989,869 £1,202,256,346

TOTAL £6,042,620,014 £724,896,679 £5,317,723,335

Table 5: Annual cost of NHS resource use attributable to managing 2.2 million

patients with a wound and 2.2 million matched controls.

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STROBE 2007 (v4) Statement—Checklist of items that should be included in reports of case-control studies

Section/Topic Item

# Recommendation

Reported on

page #

Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract 1,7

(b) Provide in the abstract an informative and balanced summary of what was done and what was found 1

Introduction

Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 6

Objectives 3 State specific objectives, including any prespecified hypotheses 6

Methods

Study design 4 Present key elements of study design early in the paper 7

Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection 7,8

Participants 6 (a) Give the eligibility criteria, and the sources and methods of case ascertainment and control selection. Give the rationale for

the choice of cases and controls

7,8

(b) For matched studies, give matching criteria and the number of controls per case 7,8

Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if

applicable

9

Data sources/

measurement

8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability

of assessment methods if there is more than one group

9

Bias 9 Describe any efforts to address potential sources of bias 9,10

Study size 10 Explain how the study size was arrived at 9

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Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why 9

Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding 9,10

(b) Describe any methods used to examine subgroups and interactions 9,10

(c) Explain how missing data were addressed N/A

(d) If applicable, explain how matching of cases and controls was addressed 8-10

(e) Describe any sensitivity analyses 10

Results

Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, confirmed

eligible, included in the study, completing follow-up, and analysed

10,11

(b) Give reasons for non-participation at each stage N/A

(c) Consider use of a flow diagram N/A

Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential

confounders

11

(b) Indicate number of participants with missing data for each variable of interest N/A

Outcome data 15* Report numbers in each exposure category, or summary measures of exposure 11,12,21,22

Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence

interval). Make clear which confounders were adjusted for and why they were included

12,13,23-25

(b) Report category boundaries when continuous variables were categorized 12,13,23-25

(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period N/A

Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses 13,14

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Discussion

Key results 18 Summarise key results with reference to study objectives 15

Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision.

Discuss both direction and magnitude of any potential bias

15-17

Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar

studies, and other relevant evidence

16

Generalisability 21 Discuss the generalisability (external validity) of the study results 16,17

Other information

Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on which the

present article is based

3

*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.

Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE

checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at

http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.

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HEALTH ECONOMIC BURDEN THAT WOUNDS IMPOSE ON

THE NATIONAL HEALTH SERVICE IN THE U.K.

Journal: BMJ Open

Manuscript ID bmjopen-2015-009283.R1

Article Type: Research

Date Submitted by the Author: 28-Aug-2015

Complete List of Authors: Guest, Julian; Catalyst Health Economics Consultants, ; King's College London, Ayoub, Naria; Catalyst Health Economics Consultants, Mcilwraith, Tracey; Catalyst Health Economics Consultants, Uchegbu, Ijeoma; Catalyst Health Economics Consultants, Gerrish, Alyson; Catalyst Health Economics Consultants, Weidlich, Diana; Catalyst Health Economics Consultants, Vowden, Kathryn; Bradford Teaching Hospitals NHS Foundation Trust,

Vowden, Peter; Bradford Teaching Hospitals NHS Foundation Trust,

<b>Primary Subject Heading</b>:

Health economics

Secondary Subject Heading: Epidemiology, General practice / Family practice, Health economics, Health policy

Keywords: WOUND MANAGEMENT, HEALTH ECONOMICS, Health economics < HEALTH SERVICES ADMINISTRATION & MANAGEMENT

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BMJ Open on M

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ORIGINAL RESEARCH

HEALTH ECONOMIC BURDEN THAT WOUNDS

IMPOSE ON THE NATIONAL HEALTH SERVICE IN THE U.K.

1,2Julian F Guest,

1Nadia Ayoub,

1Tracey Mcilwraith,

1Ijeoma Uchegbu,

1Alyson Gerrish,

1Diana Weidlich,

3Kathryn Vowden,

3Peter Vowden

1Catalyst Health Economics Consultants, Northwood, Middlesex, U.K.;

2Faculty of Life

Sciences and Medicine, King’s College, London, U.K.; 3Bradford Teaching Hospitals

NHS Foundation Trust and University of Bradford, U.K.

Correspondence to:

Professor Julian F Guest

CATALYST Health Economics Consultants

34b High Street

Northwood

Middlesex HA6 1BN

U.K.

Tel: +44 (0) 1923 450045

Fax: +44 (0) 1923 450046

E-mail: [email protected]

Running title: Annual NHS cost of managing wounds in the U.K.

Keywords: Burden, cost, wounds, ulcers, U.K.

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ABSTRACT

Objective: To estimate the prevalence of wounds managed by the U.K.’s National Health

Service (NHS) in 2012/13 and the annual levels of healthcare resource use attributable to

their management and corresponding costs.

Methods: This was a retrospective cohort analysis of the records of patients in The Health

Improvement Network (THIN) Database (a nationally representative database of patients

registered with general practitioners in the U.K.). 1,000 records of adult patients who had a

wound between 1 May 2012 and 30 April 2013 (cases) were randomly selected from the

database and matched with 1,000 patients with no previous history of a wound (controls).

Patients' characteristics, wound-related health outcomes and all healthcare resource use were

quantified and the total NHS cost of patient management was estimated at 2013/14 prices.

Results: Patients’ mean age was 69.0 years and 45% were male. 76% of patients presented

with a new wound in the study year and 61% of wounds healed during the study year.

Nutritional deficiency (Odds ratio 0.534; p <001) and diabetes (Odds ratio 0.651; p<001)

were independent risk factors for non-healing. The study estimated that 2.2 million wounds

were managed by the NHS (equivalent to 4% of the adult population in the U.K.) in 2012/13.

Annual levels of resource use attributable to managing 2.2 million wounds and associated

comorbidities included 18.6 million practice nurse visits, 10.9 million community nurse

visits, 7.7 million GP visits and 3.4 million hospital outpatient visits. The annual NHS cost of

managing 2.2 million wounds and associated comorbidities was £5.3 billion. After adjusting

for the cost of managing comorbidities, this was reduced to £4.8 billion. Sixty-six percent of

the cost was attributable to management in the community and the remainder in secondary

care. However, 48% and 78% of the cost of managing acute and chronic wounds respectively

was incurred in the community and the remainder in secondary care.

Conclusion: This real world evidence highlights that wound management is predominantly a

nurse-led discipline. Approximately 30% of wounds lacked a differential diagnosis,

indicative of the practical difficulties experienced by non-specialist clinicians in the

community. Wounds impose a substantial health economic burden on the U.K.’s NHS,

comparable to that of managing obesity (£5.0 billion) Clinical and economic benefits could

accrue from improved systems of care and an increased awareness of the impact that wounds

impose on both patients and the NHS.

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Strengths and Limitations of this Study

• This study estimated the health outcomes, resource implications and associated costs

attributable to managing wounds in 2012/13 using real world evidence obtained from the

THIN database (a nationally representative database of clinical practice among 9 million

patients registered with general practitioners in the U.K.).

• The estimates were derived following a systematic analysis of patients' characteristics,

wound-related health outcomes and all community-based and secondary care resource

use contained in the patients' electronic records.

• Computerised information in the THIN database is collected by GPs for clinical care

purposes and not for research. Additionally, prescriptions issued by GPs and practice

nurses are recorded in the database, but it does not specify whether the prescriptions

were dispensed or patient compliance with the product.

• The analysis does not consider the potential impact of those wounds that remained

unhealed beyond the study period. Nor does it consider the potential impact of managing

patients with wounds being cared for in nursing homes. The THIN database may have

under-recorded use of some healthcare resources outside the GP’s surgery. However, the

impact of this was addressed in sensitivity analyses.

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INTRODUCTION

Patients requiring wound care can be found in the community, secondary care and in long-

term care institutions and range from infants to the elderly. The patient population with

wounds is managed across the spectrum of different healthcare disciplines that includes

general practice, specialist physicians, surgeons, nurses and allied healthcare practitioners,

such as podiatrists [1-3].

Wound care should be viewed as a specialised segment of healthcare that requires clinicians

with specialist training to diagnose and manage appropriately [4,5]. However, the evidence

suggests this is not the case [1-3], Moreover, it has been suggested that better wound care,

such as effective diagnosis and treatment and effective prevention of wound complications

would help minimise treatment costs. Studies have highlighted that there is potential for

better patient management and wound care product selection that would improve outcomes

and reduce costs [1-3,6,7].

There have been previous attempts to estimate the costs and burden associated with wound

management in the U.K. However, they were based on published literature or broad estimates

derived from incidence or prevalence rates and extrapolations from relatively small-scale

studies. The objectives of the present study were to estimate: the annual prevalence of

wounds and annual number of wounds that are treated by the U.K.'s publicly-funded

National Health Service (NHS); the annual amount of NHS resource use that is utilised on

wound management; and the amount the NHS spends on managing wounds in 2012/13. The

remit of this study was limited to open external acute and chronic cutaneous wounds.

Surgical wounds healing within four weeks were excluded as cost were considered to be

related to the surgery and not to ongoing wound complications.

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METHODS

Study Design

This was a retrospective cohort analysis of the records of patients in The Health Improvement

Network (THIN) Database.

The Health Improvement Network (THIN) Database

The THIN database (Cegedim, London, U.K.) contains computerised information on 9

million anonymised patients entered by GPs from 500 practices across the U.K. General

practices across the U.K. using Vision Practice Management Software are invited to

participate in the database and are self-selecting. The patient data within THIN have been

shown to be representative of the U.K. population in terms of demographics and disease

distribution [8]. Read codes are a coded thesaurus of clinical terms that have been in use in

the NHS since 1985 [9], and have been used to code specific diagnoses in the THIN database.

A drug dictionary based on data from the Multilex classification has been used to code drugs

in the database. Successive updates of patients’ records to the database include any

subsequent changes made by GPs.

The computerised information in the THIN database includes patients’ demographics, details

from GP consultations, specialist referrals, nurse and other clinician visits, hospital

admissions, diagnostic and therapeutic procedures, laboratory tests, and prescriptions issued

in primary care that are directly generated by the general practice’s information technology

system. Hence, the information contained in the THIN database reflects real clinical practice,

as it is based on actual patient records. Moreover, GPs are the gatekeepers to health care in

the U.K., and patients’ entire medical history should be stored in their primary care record.

Study Population

The study population comprised the anonymised case records of a randomly selected cohort

of 1,000 patients from the THIN database who had a wound between 1 May 2012 and 30

April 2013 (cases) and a randomly selected cohort of 1,000 control patients (controls) from

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the database, who were matched with the cases according to age, gender, and the patient's

general practice.

Inclusion criteria for the cases were:

• Had to be ≥18 years of age or over.

• Had to have a Read code for a wound.

• Had to have continuous medical history in their case record from the first mention of a

wound in the study year up to the time the data was extracted from the database, unless

they died, in order to exclude patients who had moved or changed their general practice.

Exclusion criteria for the cases were:

• Patients with a surgical wound if they healed within four weeks of the surgical procedure

(since any resource use incurred will be due to the surgical procedure and not the wound).

• Patients with a dermatological tumour.

1,000 control patients were matched with 1,000 cases according to the following criteria:

• Age.

• Gender.

• Being managed at the same general practice.

• No history of a wound in their medical record at anytime.

• Had continuous medical history in their case record from the matched start date up to the

time the data was extracted from the database unless they died.

The Authors obtained the complete medical records of the 2,000 patients in the data set,

which enabled analysis of data both within and outside of the study period.

Ethics Approval

Ethics approval to use the complete patients’ records from the THIN database for this study

was obtained from Cegedim's Research Ethics Committee that appraises studies using the

THIN database (Reference number 13-061).

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Study Variables and Statistical Analyses

Information was systematically extracted from the patients’ records over the study period

according to the protocol approved by the ethics committee. Wound type was documented in

the patients' records and the Authors categorised them as being either acute (i.e. abscess,

burn, open wound, unhealed surgical wound, trauma) or chronic (i.e. diabetic foot ulcer,

arterial leg ulcer, mixed leg ulcer, venous leg ulcer, pressure ulcer).

Patients' characteristics, comorbidities (defined as a non-acute condition that patients were

suffering from in the year before the start of their wound and not necessarily the year before

the start of the study), wound-related health outcomes and all community-based and

secondary care resource use were extracted from the electronic records. All the data was

quantified for cases and controls and stratified according to wound type. Differences between

the groups were tested for statistical significance using either a Mann-Whitney U-test or a

Chi-Square test.

Logistic regression was used to investigate relationships between baseline variables and

clinical outcomes. Multiple linear regression was also used to assess the impact of patients’

baseline variables on resource use and clinical outcomes. All statistical analyses were

performed using IBM SPSS Statistics (version 22.0; IBM Corporation).

Health Economic Modeling

Using the THIN data set, a computer-based model was constructed depicting the treatment

pathways and associated management of the 1,000 patients with a wound and the 1,000

matched patients who had never had a wound. The model spans the 12 months period from 1

May 2012 to 30 April 201.

Unit costs at 2013/14 prices [10-12] were applied to the resource use in the model to estimate

the total NHS cost of patient management from the time a patient entered the data set (i.e.

from 1 May 2012 or the start time of their wound if it occurred later, and the equivalent date

in the matched control) up to the time their wound healed or the end of the study period,

whichever came first. Differences between cases and controls were considered to be

attributable to wound care and associated comorbidities.

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Sensitivity Analyses

Deterministic sensitivity analyses were performed on all of the model’s inputs to identify

how the cost of wound management and associated comorbidities would change by varying

the different parameters in the model.

Two methods were used to adjust for the cost of managing patients’ comorbidities.

1. The first involved generating an incremental cost among control patients between those

who had no comorbidities and those who had one, two, three, four or five or more

comorbidities. These incremental costs were then applied to both groups so that all the

patients were modelled to have the maximum number of comorbidities. The resulting

cost difference between the two groups was considered to be solely due to the wounds.

2. The second method involved the removal of a case-control match from the analysis if

they did not have the same number of comorbidities. The resulting cost difference

between the two groups was considered to be solely due to the wounds.

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RESULTS

Patients' Characteristics

Patients' mean age in the cases and controls was 69.0 and 67.3 years respectively and 55% of

patients in both groups were female. Mean blood pressure was 133/76 in the cases and 132/77

in the controls. Additionally, patients' body mass index (BMI) was a mean 29.0 kg/m2

and

26.1 kg/m2

in the cases and controls respectively. 18% of the cases were smokers, 39% were

non-smokers and 40% were ex-smokers. In the controls, 17% were smokers, 47% were non-

smokers and 32% were ex-smokers. 76% of cases presented with a new wound in the study

year (patients’ records predated the onset of the study period, enabling both pre-existing and

new wounds to be identified. A similar process allowed wound healing to be characterised).

There is no evidence that patients in the data set had more than one wound. However, 72% of

patients had a wound a mean 4.9 years prior to the one being evaluated in the study period.

Significantly more patients with a wound (94%) than control patients (77%) had at least one

comorbidity in the year before the start of their wound. Moreover, the mean number of

comorbid conditions in the cases was 3.9 per patient compared to 2.1 per patient in the

controls. The percentage of patients with different comorbidities in the year before the start of

their wound (and not necessarily the year before the start of the study) is summarised in Table

1.

Insert Table 1

Binary logistic regression was performed on patients’ age, gender, smoking status and all

comorbidities, Those variables that yielded a p value ≥0.05 were omitted from the analysis

resulting in the following comorbidities being considered as independent risk factors for

developing a wound:

• Dermatological symptoms: Odds ratio 3.26 (95% CI: 2.66; 4.00); p < 0.001.

• Nutritional deficiency: Odds ratio 2.30 (95% CI: 1.80; 2.95); p < 0.001.

• Musculoskeletal disease: Odds ratio 1.62 (95% CI: 1.29; 2.03); p < 0.001.

• Cardiovascular disease: Odds ratio 1.35 (95% CI: 1.09; 1.67); p = 0.005.

• Gastrointestinal disease: Odds ratio 1.32 (95% CI: 1.06; 1.64); p = 0.015.

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Prevalence of Wounds in the U.K.

The base population of active patients in the THIN database in 2012/13 was 3.9 million, from

which there were an estimated 135,000 patients with a wound that matched the study

protocol's inclusion and exclusion criteria. When this was extrapolated to the whole U.K.

population (63.7 million people in mid-2013), it was estimated that there were 2.2 million

patients with a wound, equivalent to 4% of the adult population, in the study year (Table 2).

12% of all wounds had no diagnosis and it was not possible to infer a wound type from the

patients' records. Additionally, 19% of all wounds were a leg ulcer without any further

characterisation (i.e. venous, arterial or mixed). In total, there were 730,000 leg ulcers, which

equates to 1.5% of the adult population having a leg ulcer in the study year. The number of

diagnosed venous leg ulcers (278,000) indicates that 1 in 170 adults had such an ulcer in the

study year. There were also an estimated 169,000 diabetic foot ulcers, which equates to 5% of

adult diabetic patients having a foot ulcer in the study year, of which 66% were male.

Insert Table 2

Clinical Outcomes

61% of all wounds healed in the study year; 79% of acute wounds healed and 43% of chronic

wounds. Binary logistic regression suggests that nutritional deficiency (Odds ratio 0.53 (95%

CI: 0.41; 0.70); p < 0.001) and diabetes (Odds ratio 0.65 (95% CI: 0.50; 0.85); p < 0.001)

were independent risk factors for non-healing during the study period. Additionally, 4% of

patients with a wound and 1% of control patients died in the study year.

Health Care Resource Use Associated with Patient Management

Patients in both groups were predominantly managed in the community by GPs and nurses.

Table 3 summarises the percentage of patients in each group who utilised different resources

during the study year.

Insert Table 3

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Table 4 shows the annual number of resources associated with managing 2.2 million patients

with a wound and 2.2 million control patients. The differences were considered to be the

incremental amounts of resource use attributable to managing 2.2 million wounds and

associated comorbidities and included 18.6 million practice nurse visits, 10.9 million

community nurse visits, 7.7 million GP visits, 3.4 million hospital outpatient visits, 97.1

million drug prescriptions, 262.2 million dressings, 73.4 million bandages and 9.0 million

compression bandages. Assessment of peripheral perfusion is a recognised requirement for

leg ulcer and diabetic foot management, yet only 16% of all cases with a leg or foot ulcer had

a Doppler ankle brachial pressure index recorded in their records.

Insert Table 4

The total annual NHS cost of managing 2.2 million patients with a wound was estimated to

be £6.0 billion (Table 5). The corresponding cost of managing the matched controls was £0.7

billion. Hence the total annual NHS cost of managing 2.2 million wounds and associated

comorbidities was estimated to be £5.3 billion. Of this, £1.65 billion and £3.67 billion was

associated with managing those wounds that healed and remained unhealed respectively.

Insert Table 5

66% of the total annual NHS cost was incurred in the community and the remainder in

secondary care. However, the distribution of costs varied according to wound type, with 48%

and 72% of the total annual NHS cost of managing acute and chronic wounds respectively

being incurred in the community and the remainder in secondary care.

Sensitivity Analyses

The estimated amounts of individual resource use were reduced and increased by 25%.

However, this only affected the total annual NHS cost of managing 2.2 million wounds and

associated comorbidities by 6% or less.

The cost of an initial surgical procedure may not be relevant to the cost incurred in managing

an unhealed surgical wound. Therefore, a sensitivity analysis was performed to exclude this

cost from the cost of managing patients with an unhealed surgical wound. The analysis found

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that when the cost of surgery was excluded from the cost of managing patients with an

unhealed surgical wound, the total annual NHS cost of managing 2.2 million wounds and

associated comorbidities was reduced from £5.3 billion to £4.8 billion.

When the NHS cost of managing patients was adjusted for their comorbidities (see

description of method 1 and 2 under Sensitivity Analyses), the total annual NHS cost of

managing 2.2 million wounds was reduced from £5.3 billion to £5.1 billion when method 1

was used and to £4.5 billion when method 2 was used. Hence, the total annual NHS cost of

managing the comorbidities among 2.2 million patients with a wound was estimated to be

between £250 and £788 million. After adjusting for comorbidities, the total annual NHS cost

of managing healed wounds and unhealed wounds was estimated to be £1.53 billion and

£3.49 billion respectively.

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DISCUSSION

This study estimated the health outcomes, resource implications and associated costs

attributable to managing wounds in 2012/13. After adjustment for comorbidities, the annual

NHS cost of managing wounds was estimated to be £4.5-5.1 billion, two-thirds of which is

incurred in the community and the rest in secondary care. This is comparable to the annual

NHS cost of managing obesity which was estimated at £5.0 billion in 2013 [13].

For patients to be included in the data set, they had to have had a wound in the study year or

be matched to these patients on the basis of their age, sex, the same general practice, and no

evidence of a wound in their medical history. Patients in both groups were managed primarily

by clinicians in the community. Only half the patients with a wound saw a hospital physician

although the consultation may not have been wound-related. However, the evidence shows

that wound management is predominantly a nurse-led discipline. Approximately 30% of

wounds lacked a differential diagnosis. This may be indicative of the practical difficulties

esperienced by non-specialist healthcare professionals in the community with establishing a

working diagnosis. Moreover, it appears that only 16% of patients with a leg or foot ulcer had

a Doppler. However, national guidance in the UK for both leg ulcer management and the

management of diabetic foot ulceration requires arterial assessment by Doppler ultrasound

measurement of the ankle-brachial pressure index [14,15]. Hence, these findings suggest (1)

the need to refer patients to a specialist for investigation and a differential diagnosis and a

shared management plan to be implemented in the community and (2) training of non-

specialist clinicians in the fundamentals of wound management. These two measures should

help overcome some of the problems encountered in clinical practice and achieve better

health outcomes, thereby reducing the high levels of resource use and corresponding costs,

and improving compliance with appropriate NICE and best practice guidelines. The study

highlighted that despite being a nurse-led discipline, there is a lack of involvement of tissue

viability nurses and other specialist nurses in the management of patients with wounds.

Recent articles [16,17] highlight the lack of a clear definition, and therefore confusion

regarding the role of these nurses.

The wound patients had significantly more comorbidities than their matched controls.

However, it was surprising to find such a high level of illness among the controls. For

example, 53% had cardiovascular disease. Moreover, 34% of patients with a wound and 13%

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of controls had nutritional deficiency that warranted supplementation with clinical nutritional

formulae. The THIN data set in this study covers the period 2012/13 and comprises patients

with a wide age range (19 to 98 years), so this level of illness may be a proxy for the health of

a proportion of the general population at that time. Furthermore, the presence of nutritional

deficiency was an independent risk factor for wound non-healing. Hence, community-

prevention of patients developing nutritional deficiency should help improve healing rates

following the onset of a wound. Moreover, if patients’ wounds and their comorbidities were

treated more holistically with appropriate involvement of allied healthcare professionals,

rather than just focusing on the wounds, better health outcomes might be achieved at lower

cost.

Other studies have assessed the prevalence and costs of wound care. A district-wide survey in

the Bradford and Airedale area of the U.K. estimated the annual NHS cost of wound care to

be £2.0 million per 100,000 population [18], which equates to £1.27 billion for the U.K. as a

whole. In another study, the NHS cost of caring for patients with a chronic wound was

estimated to be £2.3-3.1billion per year at 2005/06 prices [19]. Previous prevalence studies

suggest there may be up to 190,000 individuals with a venous leg ulcers in the U.K. at any

time [19]. However, this is likely to be an underestimate as our analysis estimated that the

NHS manages 278,000 venous leg ulcers per annum plus an additional 420,000 unspecified

leg ulcers (i.e. those lacking a true working diagnosis), some of which will undoubtedly be

venous in origin. The prevalence of pressure ulcers has been previously estimated to be 0.103

in 2005/06 [20], and another study estimated the incidence to be 400,000 new pressure ulcers

per annum in the U.K. [19]. These figures are substantially higher than our estimate of the

NHS managing 153,000 pressure ulcers per annum. The difference may be due to people

residing in nursing homes not having been included in our study. It may also be due to under-

recording of pressure ulcers in patients' records and/or an over-estimation in the previous

studies, and/or a lower prevalence in 2012/13 than in 2005/06. The present study also

estimated that 5% of patients with diabetes have a foot ulcer which is consistent with other

estimates [21].

The advantage of using the THIN database is that the patient pathways and associated

resource use are based on real world evidence derived from clinical practice. However, health

outcomes and resource use, whilst collected prospectively, were analysed retrospectively.

Hence, confounding factors may exist. While the study results are compelling, the analyses

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were based on clinicians’ entries into their patients’ records and inevitably subject to a certain

amount of imprecision and lack of detail. Moreover, the computerised information in the

THIN database is collected by GPs for clinical care purposes and not for research.

Prescriptions issued by GPs and practice nurses are recorded in the database, but it does not

specify whether the prescriptions were dispensed or patient compliance with the product.

Despite these limitations, it is the Authors’ opinion that the THIN database affords one of the

best sources of real world evidence for clinical practice in the U.K.

The analysis does not consider the potential impact of those wounds that remained unhealed

beyond the study period, nor does it consider the potential impact of managing patients with

wounds being cared for in nursing/residential homes. The THIN database may have under-

recorded use of some healthcare resources outside the GP’s surgery if not documented in the

GP records, such as home visits made by clinicians, hospital outpatient visits, hospital

admissions and accident and emergency attendances. The impact of this was addressed in

sensitivity analyses. The analysis excludes hospital-based prescribing, but this should have

minimal impact on the results since most prescribing is undertaken by GPs and nurses in the

community.

The analysis only considered the annual cost of NHS resource use for the “average patient,”

and no attempt was made to stratify resource use and costs according to gender,

comorbidities, wound size, wound severity, and other disease-related factors. Also excluded

were the costs incurred by patients and indirect costs incurred by society as a result of

patients taking time off work. However, patients’ mean age was >65 years, so it is unlikely

that many were in employment.

Notwithstanding the study's limitations, the real world evidence in our study demonstrates

that wounds impose a substantial health economic burden on the U.K.’s NHS, comparable to

that of managing obesity. Clinical and economic benefits could accrue from improved

systems of care and an increased awareness of the impact that wounds impose on both

patients and the NHS.

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CONFLICTS OF INTEREST

The authors have no potential conflicts of interest relevant to this article.

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FUNDING

This study was commisioned and funded by the NIHR Wound Prevention and Treatment

Healthcare Technology Co-operative (NIHR WoundTec HTC), Bradford Institute For Health

Research, Bradford, West Yorkshire, U.K. following an open tendering process. Additional

funding was provided by 3M Limited, Loughborough, Leicestershire, U.K.; Activa

Healthcare Limited, Burton On Trent, Staffordshire, U.K.; Blanson Limited, Narborough,

Leicestershire, U.K.; Brightwake Limited, Kirkby In Ashfield, Nottinghamshire, U.K.; KCI

Medical Limited, Crawley, West Sussex, U.K.; Medira Ltd, Cambridge, Cambridgeshire,

U.K.; Molnlycke Health Care Limited, Dunstable, Bedfordshire, U.K.; Park House

Healthcare Limited, Elland, West Yorkshire, U.K.; Perfectus Biomed Ltd, Daresbury,

Warrington, U.K.; Smith & Nephew Medical Limited, Hull, East Riding Of Yorkshire, U.K.;

Sozo Woundcare Limited, Harrogate, North Yorkshire, U.K.; Systagenix Wound

Management Limited, Gatwick Airport, West Sussex, U.K.; Urgo Limited, Loughborough,

Leicestershire, U.K.; Willingsford Limited, Southampton, Hampshire, U.K.

The study’s sponsors had no involvement in the study design, the collection, analysis and

interpretation of the data, the writing of this manuscript and the decision to submit this

article for publication.The views expressed in this article are those of the authors and not

necessarily those of the NHS, the NIHR, the Department of Health or any of the other

sponsors.

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AUTHORS' CONTRIBUTION

J.F.G. designed the study, managed the analyses, performed some analyses, checked all the

other analyses, and wrote the manuscript.

N.A. and T.M conducted much of the analyses.

I.U. and A.G conducted some of the analyses.

D.W. scrutinized the analyses and edited the manuscript.

K.V and P.V scrutinized the analyses, suggested further analyses, helped interpret some of

the findings, and edited the manuscript.

J.F.G. is the guarantor of this work and, as such, had full access to all the data in the study

and takes responsibility for the integrity of the data and the accuracy of the data analysis.

The analyses have also been reviewed by the following strategic partners of the NIHR

Bradford Wound Prevention & Treatment Healthcare Technology Co-operative

(www.woundtec.htc.nihr.ac.uk): Prof Andrea Nelson, Head of School of Healthcare,

University of Leeds, Leeds; Prof Jane Nixon, Deputy Director, Leeds Institute of Clinical

Trials Research, Leeds; Professor Dan L Bader, Faculty of Health Sciences, University of

Southampton, Southampton; Dr Patricia Grocott, Reader in Palliative Wound Care

Technology Transfer, King's College, London; Hussein Dharma, Project Manager, NIHR

WoundTec Healthcare Technology Co-operative, Bradford Institute for Health Research,

Bradford.

The Corresponding Author has the right to grant on behalf of all authors and does grant on

behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in

all forms, formats and media (whether known now or created in the future), to i) publish,

reproduce, distribute, display and store the Contribution, ii) translate the Contribution into

other languages, create adaptations, reprints, include within collections and create summaries,

extracts and/or, abstracts of the Contribution and convert or allow conversion into any format

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including without limitation audio, iii) create any other derivative work(s) based in whole or

part on the on the Contribution, iv) to exploit all subsidiary rights to exploit all subsidiary

rights that currently exist or as may exist in the future in the Contribution, v) the inclusion of

electronic links from the Contribution to third party material where-ever it may be located;

and, vi) licence any third party to do any or all of the above.

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REFERENCES

1. Guest JF, Taylor RR, Vowden K, Vowden P. Relative cost-effectiveness of a skin

protectant in managing venous leg ulcers in the UK. Journal of Wound Care 2012;

21(8): 389-398.

2. Panca M, Cutting K, Guest JF. Clinical and cost-effectiveness of absorbent dressings in

the treatment of highly exuding VLUs. Journal of Wound Care 2013; 22(3): 109-118.

3. Guest JF, Gerrish A, Ayoub N, Vowden K, Vowden P. Clinical outcomes and cost-

effectiveness of using a two-layer cohesive compression bandage compared with a two-

layer compression system and a four-layer compression system in clinical practice in

the UK. Journal of Wound Care 2015; Accepted for publication.

4. Harding K. 'Woundology'- an emerging clinical specialty. Int Wound J. 2008;5(5):597.

5. Kapp S, Santamaria N. Chronic wounds should be one of Australia's National Health

Priority Areas. Aust Health Rev. 2015 Jun 15. doi: 10.1071/AH14230. [Epub ahead of

print].

6. Guest JF, Charles H, Cutting K. Is it time to re-appraise the role of compression in non-

healing venous leg ulcers? Journal of Wound Care 2013;22(9):453-60.

7. National Institute for Health and Care Excellence. NICE advice [KTT14] January 2015.

Available on line at: https://www.nice.org.uk/advice/ ktt14/chapter/Evidence-context.

Accessed 14 May 2015.

8. Blak BT, Thompson M, Dattani H, Bourke A. Generalisability of The Health

Improvement Network (THIN) database: demographics, chronic disease prevalence and

mortality rates. Informatics in Primary Care 2011;19:251–255.

9. Read Codes. Department for Health. 2010. Available from

http://systems.hscic.gov.uk/data/uktc/readcodes. Accessed 12 May 2015.

10. Department of Health. NHS reference costs 2013/14 [article online]. Available from

https://www.gov.uk/government/publications/nhs-reference-costs-2013-to-2014.

Accessed 25 April 2015.

11. Curtis L. Unit Costs of Health and Social Care 2014. Canterbury: University of Kent.

Personal Social Services Research Unit, 2014. Available from http://www.pssru.ac.uk/

project-pages/unit-costs/2014. Accessed 25 April 2015.

12. Drug Tariff 2014. Available from https://www.drugtariff.co.uk. Accessed 25 April

2015.

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13. Royal College of Physicians 2013. Action on obesity: Comprehensive care for all

Report of a working party January 2013. Available on line at

http://www.evidence.nhs.uk/search?q=obesity%20AND%20costs%20nhs. Accessed 26

April 2015.

14. SIGN Guideline 120: Management of chronic venous leg ulcers. Scottish

Intercollegiate Guidelines Network 2010. Available at:

http://www.sign.ac.uk/pdf/sign120.pdf.

15. Diabetic foot problems: prevention and management. NICE guidelines [NG19].

National Institute for Health and Care Excellence (NICE) August 2015

16. Ousey K, Atkin L, Milne J, Henderson V. The Changing Role of the Tissue Viability

Nurse: an exploration of this multifaceted role. Wounds UK 2014; 10 (4): 54–61.

17. Ousey K, Milne J, Atkin L, Henderson V, King N, Stephenson J. Exploring the role of

the Tissue Viability Nurse. Wounds UK (EWMA Special) 2015; 36-45.

18. Vowden K, Vowden P, Posnett J. The resource cost of wound care in the Bradford and

Airedale primary care trust in the UK. Journal of Wound Care 2009; 18(3): 93-102.

19. Posnett J, Franks P. The burden of chronic wounds in the UK. Nursing Times 2008;

104(3): 44-5.

20. Philips, L. & Busby J. Pressure Ulcer Epidemiology in the UK: 2005-2006. Poster

Presentation at Wounds UK 2006.

21. Diabetes in the UK 2012: Key statistics on diabetes Available on line at:

http://www.diabetes.org.uk/About_us/What-we-say/Statistics/Diabetes-in-the-UK-

2012. Accessed 12 May 2015.

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Percentage of patients

Comorbidity Cases Controls p value

Cardiovascular 73% 53% <0.005

Dermatological 59% 25% <0.001

Endocrinological 45% 27% <0.01

Gastroenterological 43% 25% <0.01

Immunological 3% 0% ns

Musculoskeletal 37% 19% <0.005

Neurological 23% 13% ns

Nutritional deficiency 34% 13% <0.001

Other 14% 7% ns

Psychiatric 31% 18% <0.05

Respiratory 28% 15% ns

None 6% 23% <0.001

Table 1: Percentage of patients with a comorbidity in the year

before the start of their wound.

If the p value was ≥0.05 it was considered not significant (ns).

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Annual number of

wounds

Annual prevalence among

the adult U.K. population

Abscess 160,000 (7%) 0.0032

Burn 87,000 (4%) 0.0018

Diabetic foot ulcer 169,000 (8%) 0.0034

Leg ulcer (arterial) 9,000 (<1%) 0.0002

Leg ulcer (mixed) 24,000 (1%) 0.0005

Leg ulcer (unspecified) 420,000 (19%) 0.0085

Leg ulcer (venous) 278,000 (13%) 0.0056

Open wound 240,000 (11%) 0.0048

Pressure ulcer 153,000 (7%) 0.0031

Surgical wound 253,000 (11%) 0.0051

Trauma 158,000 (7%) 0.0032

Unspecified 271,000 (12%) 0.0055

Total 2,222,000 (100%) 0.0447

Table 2: Annual number and prevalence of different wound types

in the U.K. among the adult population (i.e. ≥≥≥≥ 18 years of age)

estimated from the THIN database.

Percentage of total number of wounds is in parentheses.

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Percentage of patients

Resource Cases Controls p value

GP visits 86% 47% <0.001

Practise nurse visits 72% 29% <0.001

Community nurse visits 75% 2% <0.001

Specialist nurse visits 2% <1% ns

Allied healthcare visits 14% 3% 0.005

Hospital outpatient visits 53% 18% <0.001

Hospital admissions and day cases 29% 6% <0.001

Ambulance services <1% <1% ns

Accident and emergency attendances <1% <1% ns

Diagnostic tests 80% 45% <0.001

Non-wound care devices 36% 5% <0.001

Wound care products 100% 0% <0.001

Prescriptions for individual drugs 98% 72% <0.001

Table 3: Percentage of patients who utilised resources in the study year.

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Annual number

Resource Cases Controls Difference p value

GP visits 10,816,655 3,124,120 7,692,535 <0.001

Practise nurse visits 19,744,618 1,184,322 18,560,296 <0.001

Community nurse visits 10,932,199 75,548 10,856,651 <0.001

Specialist nurse visits 51,106 4,444 46,662 <0.001

Allied healthcare visits 537,722 77,770 459,952 <0.001

Hospital outpatient visits 4,277,334 828,803 3,448,531 <0.001

Hospital admissions and day cases 1,142,104 173,315 968,788 <0.001

Ambulance services 11,110 2,222 8,888 ns

Accident and emergency attendances 11,110 11,110 - ns

Diagnostic tests 60,284,855 24,068,613 36,216,242 <0.001

Devices 320,938,916 48,206,108 272,732,808 <0.001

Wound care products 354,954,275 13,332 354,940,943 <0.001

Prescriptions for individual drugs 135,859,234 38,769,310 97,089,924 <0.001

Table 4: Annual amount of NHS resource use attributable to managing 2.2 million patients with

a wound and 2.2 million matched controls.

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Annual cost

Resource Cases Controls Difference

GP visits £514,993,223 £145,951,520 £369,041,702

Practise nurse visits £256,760,021 £15,396,180 £241,363,841

Community nurse visits £682,382,518 £3,026,353 £679,356,166

Specialist nurse visits £3,650,732 £322,189 £3,328,543

Allied healthcare visits £34,451,980 £4,859,496 £29,592,485

Hospital outpatient visits £515,002,111 £99,947,406 £415,054,705

Hospital admissions and day cases £1,334,299,309 £135,277,073 £1,199,022,237

Ambulance services £2,555,290 £511,058 £2,044,232

Accident and emergency attendances £666,597 £666,597 £0

Diagnostic tests £282,646,224 £113,238,466 £169,407,758

Devices £282,261,975 £17,525,292 £264,736,682

Wound care products £742,703,819 £185,181 £742,518,638

Prescriptions for individual drugs £1,390,246,214 £187,989,869 £1,202,256,346

TOTAL £6,042,620,014 £724,896,679 £5,317,723,335

Table 5: Annual cost of NHS resource use attributable to managing 2.2 million

patients with a wound and 2.2 million matched controls.

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STROBE 2007 (v4) Statement—Checklist of items that should be included in reports of case-control studies

Section/Topic Item

# Recommendation

Reported on

page #

Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract 1,7

(b) Provide in the abstract an informative and balanced summary of what was done and what was found 1

Introduction

Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 6

Objectives 3 State specific objectives, including any prespecified hypotheses 6

Methods

Study design 4 Present key elements of study design early in the paper 7

Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection 7,8

Participants 6 (a) Give the eligibility criteria, and the sources and methods of case ascertainment and control selection. Give the rationale for

the choice of cases and controls

7,8

(b) For matched studies, give matching criteria and the number of controls per case 7,8

Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if

applicable

9

Data sources/

measurement

8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability

of assessment methods if there is more than one group

9

Bias 9 Describe any efforts to address potential sources of bias 9,10

Study size 10 Explain how the study size was arrived at 9

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Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why 9

Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding 9,10

(b) Describe any methods used to examine subgroups and interactions 9,10

(c) Explain how missing data were addressed N/A

(d) If applicable, explain how matching of cases and controls was addressed 8-10

(e) Describe any sensitivity analyses 10

Results

Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, confirmed

eligible, included in the study, completing follow-up, and analysed

10,11

(b) Give reasons for non-participation at each stage N/A

(c) Consider use of a flow diagram N/A

Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential

confounders

11

(b) Indicate number of participants with missing data for each variable of interest N/A

Outcome data 15* Report numbers in each exposure category, or summary measures of exposure 11,12,21,22

Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence

interval). Make clear which confounders were adjusted for and why they were included

12,13,23-25

(b) Report category boundaries when continuous variables were categorized 12,13,23-25

(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period N/A

Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses 13,14

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Discussion

Key results 18 Summarise key results with reference to study objectives 15

Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision.

Discuss both direction and magnitude of any potential bias

15-17

Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar

studies, and other relevant evidence

16

Generalisability 21 Discuss the generalisability (external validity) of the study results 16,17

Other information

Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on which the

present article is based

3

*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.

Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE

checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at

http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.

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HEALTH ECONOMIC BURDEN THAT WOUNDS IMPOSE ON

THE NATIONAL HEALTH SERVICE IN THE U.K.

Journal: BMJ Open

Manuscript ID bmjopen-2015-009283.R2

Article Type: Research

Date Submitted by the Author: 19-Oct-2015

Complete List of Authors: Guest, Julian; Catalyst Health Economics Consultants, ; King's College London, Ayoub, Naria; Catalyst Health Economics Consultants, Mcilwraith, Tracey; Catalyst Health Economics Consultants, Uchegbu, Ijeoma; Catalyst Health Economics Consultants, Gerrish, Alyson; Catalyst Health Economics Consultants, Weidlich, Diana; Catalyst Health Economics Consultants, Vowden, Kathryn; Bradford Teaching Hospitals NHS Foundation Trust,

Vowden, Peter; Bradford Teaching Hospitals NHS Foundation Trust,

<b>Primary Subject Heading</b>:

Health economics

Secondary Subject Heading: Epidemiology, General practice / Family practice, Health economics, Health policy

Keywords: WOUND MANAGEMENT, HEALTH ECONOMICS, Health economics < HEALTH SERVICES ADMINISTRATION & MANAGEMENT

For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml

BMJ Open on M

arch 4, 2021 by guest. Protected by copyright.

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ORIGINAL RESEARCH

HEALTH ECONOMIC BURDEN THAT WOUNDS

IMPOSE ON THE NATIONAL HEALTH SERVICE IN THE U.K.

1,2Julian F Guest,

1Nadia Ayoub,

1Tracey Mcilwraith,

1Ijeoma Uchegbu,

1Alyson Gerrish,

1Diana Weidlich,

3Kathryn Vowden,

3Peter Vowden

1Catalyst Health Economics Consultants, Northwood, Middlesex, U.K.;

2Faculty of Life

Sciences and Medicine, King’s College, London, U.K.; 3Bradford Teaching Hospitals

NHS Foundation Trust and University of Bradford, U.K.

Correspondence to:

Professor Julian F Guest

CATALYST Health Economics Consultants

34b High Street

Northwood

Middlesex HA6 1BN

U.K.

Tel: +44 (0) 1923 450045

Fax: +44 (0) 1923 450046

E-mail: [email protected]

Running title: Annual NHS cost of managing wounds in the U.K.

Keywords: Burden, cost, wounds, ulcers, U.K.

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ABSTRACT

Objective: To estimate the prevalence of wounds managed by the U.K.’s National Health

Service (NHS) in 2012/13 and the annual levels of healthcare resource use attributable to

their management and corresponding costs.

Methods: This was a retrospective cohort analysis of the records of patients in The Health

Improvement Network (THIN) Database. Records of 1,000 adult patients who had a wound

in 2012/13 (cases) were randomly selected and matched with 1,000 patients with no previous

history of a wound (controls). Patients' characteristics, wound-related health outcomes and all

healthcare resource use were quantified and the total NHS cost of patient management was

estimated at 2013/14 prices.

Results: Patients’ mean age was 69.0 years and 45% were male. 76% of patients presented

with a new wound in the study year and 61% of wounds healed during the study year.

Nutritional deficiency (Odds ratio 0.534; p <001) and diabetes (Odds ratio 0.651; p<001)

were independent risk factors for non-healing. There were an estimated 2.2 million wounds

managed by the NHS in 2012/13. Annual levels of resource use attributable to managing

these wounds and associated comorbidities included 18.6 million practice nurse visits, 10.9

million community nurse visits, 7.7 million GP visits and 3.4 million hospital outpatient

visits. The annual NHS cost of managing these wounds and associated comorbidities was

£5.3 billion. This was reduced to £4.8 billion after adjusting for comorbidities.

Conclusion: Real world evidence highlights wound management is predominantly a nurse-

led discipline. Approximately 30% of wounds lacked a differential diagnosis, indicative of

practical difficulties experienced by non-specialist clinicians. Wounds impose a substantial

health economic burden on the U.K.’s NHS, comparable to that of managing obesity (£5.0

billion). Clinical and economic benefits could accrue from improved systems of care and an

increased awareness of the impact that wounds impose on both patients and the NHS.

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Strengths and Limitations of this Study

• This study estimated the health outcomes, resource implications and associated costs

attributable to managing wounds in 2012/13 using real world evidence obtained from the

THIN database (a nationally representative database of clinical practice among 9 million

patients registered with general practitioners in the U.K.).

• The estimates were derived following a systematic analysis of patients' characteristics,

wound-related health outcomes and all community-based and secondary care resource

use contained in the patients' electronic records.

• Computerised information in the THIN database is collected by GPs for clinical care

purposes and not for research. Additionally, prescriptions issued by GPs and practice

nurses are recorded in the database, but it does not specify whether the prescriptions

were dispensed or patient compliance with the product.

• The analysis does not consider the potential impact of those wounds that remained

unhealed beyond the study period. Nor does it consider the potential impact of managing

patients with wounds being cared for in nursing homes. The THIN database may have

under-recorded use of some healthcare resources outside the GP’s surgery. However, the

impact of this was addressed in sensitivity analyses.

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INTRODUCTION

Patients requiring wound care can be found in the community, secondary care and in long-

term care institutions and range from infants to the elderly. The patient population with

wounds is managed across the spectrum of different healthcare disciplines that includes

general practice, specialist physicians, surgeons, nurses and allied healthcare practitioners,

such as podiatrists [1-3].

Wound care should be viewed as a specialised segment of healthcare that requires clinicians

with specialist training to diagnose and manage appropriately [4,5]. However, the evidence

suggests this is not the case [1-3], Moreover, it has been suggested that better wound care,

such as effective diagnosis and treatment and effective prevention of wound complications

would help minimise treatment costs. Studies have highlighted that there is potential for

better patient management and wound care product selection that would improve outcomes

and reduce costs [1-3,6,7].

There have been previous attempts to estimate the costs and burden associated with wound

management in the U.K. However, they were based on published literature or broad estimates

derived from incidence or prevalence rates and extrapolations from relatively small-scale

studies. The objectives of the present study were to estimate: the annual prevalence of

wounds and annual number of wounds that are treated by the U.K.'s publicly-funded National

Health Service (NHS); the annual amount of NHS resource use that is utilised on wound

management; and the amount the NHS spends on managing wounds in 2012/13. The remit of

this study was limited to open external acute and chronic cutaneous wounds. Surgical wounds

healing within four weeks were excluded as cost were considered to be related to the surgery

and not to ongoing wound complications.

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METHODS

Study Design

This was a retrospective cohort analysis of the records of patients in The Health Improvement

Network (THIN) Database.

The Health Improvement Network (THIN) Database

The THIN database (Cegedim, London, U.K.) contains computerised information on 9

million anonymised patients entered by GPs from 500 practices across the U.K. General

practices across the U.K. using Vision Practice Management Software are invited to

participate in the database and are self-selecting. The patient data within THIN have been

shown to be representative of the U.K. population in terms of demographics and disease

distribution [8]. Read codes are a coded thesaurus of clinical terms that have been in use in

the NHS since 1985 [9], and have been used to code specific diagnoses in the THIN database.

A drug dictionary based on data from the Multilex classification has been used to code drugs

in the database. Successive updates of patients’ records to the database include any

subsequent changes made by GPs.

The computerised information in the THIN database includes patients’ demographics, details

from GP consultations, specialist referrals, nurse and other clinician visits, hospital

admissions, diagnostic and therapeutic procedures, laboratory tests, and prescriptions issued

in primary care that are directly generated by the general practice’s information technology

system. Hence, the information contained in the THIN database reflects real clinical practice,

as it is based on actual patient records. Moreover, GPs are the gatekeepers to health care in

the U.K., and patients’ entire medical history should be stored in their primary care record.

Study Population

The study population comprised the anonymised case records of a randomly selected cohort

of 1,000 patients from the THIN database who had a wound between 1 May 2012 and 30

April 2013 (cases) and a randomly selected cohort of 1,000 control patients (controls) from

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the database, who were matched with the cases according to age, gender, and the patient's

general practice.

Inclusion criteria for the cases were:

• Had to be ≥18 years of age or over.

• Had to have a Read code for a wound.

• Had to have continuous medical history in their case record from the first mention of a

wound in the study year up to the time the data was extracted from the database, unless

they died, in order to exclude patients who had moved or changed their general practice.

Exclusion criteria for the cases were:

• Patients with a surgical wound if they healed within four weeks of the surgical procedure

(since any resource use incurred will be due to the surgical procedure and not the wound).

• Patients with a dermatological tumour.

1,000 control patients were matched with 1,000 cases according to the following criteria:

• Age.

• Gender.

• Being managed at the same general practice.

• No history of a wound in their medical record at anytime.

• Had continuous medical history in their case record from the matched start date up to the

time the data was extracted from the database unless they died.

The Authors obtained the complete medical records of the 2,000 patients in the data set,

which enabled analysis of data both within and outside of the study period.

Ethics Approval

Ethics approval to use the complete patients’ records from the THIN database for this study

was obtained from Cegedim's Research Ethics Committee that appraises studies using the

THIN database (Reference number 13-061).

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Study Variables and Statistical Analyses

Information was systematically extracted from the patients’ records over the study period

according to the protocol approved by the ethics committee. Wound type was documented in

the patients' records and the Authors categorised them as being either acute (i.e. abscess,

burn, open wound, unhealed surgical wound, trauma) or chronic (i.e. diabetic foot ulcer,

arterial leg ulcer, mixed leg ulcer, venous leg ulcer, pressure ulcer).

Patients' characteristics, comorbidities (defined as a non-acute condition that patients were

suffering from in the year before the start of their wound and not necessarily the year before

the start of the study), wound-related health outcomes and all community-based and

secondary care resource use were extracted from the electronic records. All the data was

quantified for cases and controls and stratified according to wound type. Differences between

the groups were tested for statistical significance using either a Mann-Whitney U-test or a

Chi-Square test.

Logistic regression was used to investigate relationships between baseline variables and

clinical outcomes. Multiple linear regression was also used to assess the impact of patients’

baseline variables on resource use and clinical outcomes. All statistical analyses were

performed using IBM SPSS Statistics (version 22.0; IBM Corporation).

Health Economic Modeling

Using the THIN data set, a computer-based model was constructed depicting the treatment

pathways and associated management of the 1,000 patients with a wound and the 1,000

matched patients who had never had a wound. The model spans the 12 months period from 1

May 2012 to 30 April 201.

Unit costs at 2013/14 prices [10-12] were applied to the resource use in the model to estimate

the total NHS cost of patient management from the time a patient entered the data set (i.e.

from 1 May 2012 or the start time of their wound if it occurred later, and the equivalent date

in the matched control) up to the time their wound healed or the end of the study period,

whichever came first. Differences between cases and controls were considered to be

attributable to wound care and associated comorbidities.

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Sensitivity Analyses

Deterministic sensitivity analyses were performed on all of the model’s inputs to identify

how the cost of wound management and associated comorbidities would change by varying

the different parameters in the model.

Two methods were used to adjust for the cost of managing patients’ comorbidities.

1. The first involved generating an incremental cost among control patients between those

who had no comorbidities and those who had one, two, three, four or five or more

comorbidities. These incremental costs were then applied to both groups so that all the

patients were modelled to have the maximum number of comorbidities. The resulting

cost difference between the two groups was considered to be solely due to the wounds.

2. The second method involved the removal of a case-control match from the analysis if

they did not have the same number of comorbidities. The resulting cost difference

between the two groups was considered to be solely due to the wounds.

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RESULTS

Patients' Characteristics

Patients' mean age in the cases and controls was 69.0 and 67.3 years respectively and 55% of

patients in both groups were female. Mean blood pressure was 133/76 in the cases and 132/77

in the controls. Additionally, patients' body mass index (BMI) was a mean 29.0 kg/m2

and

26.1 kg/m2

in the cases and controls respectively. 18% of the cases were smokers, 39% were

non-smokers and 40% were ex-smokers. In the controls, 17% were smokers, 47% were non-

smokers and 32% were ex-smokers. 76% of cases presented with a new wound in the study

year (patients’ records predated the onset of the study period, enabling both pre-existing and

new wounds to be identified. A similar process allowed wound healing to be characterised).

There is no evidence that patients in the data set had more than one wound. However, 72% of

patients had a wound a mean 4.9 years prior to the one being evaluated in the study period.

Significantly more patients with a wound (94%) than control patients (77%) had at least one

comorbidity in the year before the start of their wound. Moreover, the mean number of

comorbid conditions in the cases was 3.9 per patient compared to 2.1 per patient in the

controls. The percentage of patients with different comorbidities in the year before the start of

their wound (and not necessarily the year before the start of the study) is summarised in Table

1.

Insert Table 1

Binary logistic regression was performed on patients’ age, gender, smoking status and all

comorbidities, Those variables that yielded a p value ≥0.05 were omitted from the analysis

resulting in the following comorbidities being considered as independent risk factors for

developing a wound:

• Dermatological symptoms: Odds ratio 3.26 (95% CI: 2.66; 4.00); p < 0.001.

• Nutritional deficiency: Odds ratio 2.30 (95% CI: 1.80; 2.95); p < 0.001.

• Musculoskeletal disease: Odds ratio 1.62 (95% CI: 1.29; 2.03); p < 0.001.

• Cardiovascular disease: Odds ratio 1.35 (95% CI: 1.09; 1.67); p = 0.005.

• Gastrointestinal disease: Odds ratio 1.32 (95% CI: 1.06; 1.64); p = 0.015.

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Prevalence of Wounds in the U.K.

The base population of active patients in the THIN database in 2012/13 was 3.9 million, from

which there were an estimated 135,000 patients with a wound that matched the study

protocol's inclusion and exclusion criteria. When this was extrapolated to the whole U.K.

population (63.7 million people in mid-2013), it was estimated that there were 2.2 million

patients with a wound who matched the study protocol's inclusion and exclusion criteria,

equivalent to 4% of the adult population, in the study year (Table 2).

12% of all wounds had no diagnosis and it was not possible to infer a wound type from the

patients' records. Additionally, 19% of all wounds were a leg ulcer without any further

characterisation (i.e. venous, arterial or mixed). In total, there were 730,000 leg ulcers, which

equates to 1.5% of the adult population having a leg ulcer in the study year. The number of

diagnosed venous leg ulcers (278,000) indicates that 1 in 170 adults had such an ulcer in the

study year. There were also an estimated 169,000 diabetic foot ulcers, which equates to 5% of

adult diabetic patients having a foot ulcer in the study year, of which 66% were male. There

is no evidence that any of the patients in our data set had more than one wound.

Insert Table 2

Clinical Outcomes

61% of all wounds healed in the study year; 79% of acute wounds healed and 43% of chronic

wounds. Binary logistic regression suggests that nutritional deficiency (Odds ratio 0.53 (95%

CI: 0.41; 0.70); p < 0.001) and diabetes (Odds ratio 0.65 (95% CI: 0.50; 0.85); p < 0.001)

were independent risk factors for non-healing during the study period. Additionally, 4% of

patients with a wound and 1% of control patients died in the study year.

Health Care Resource Use Associated with Patient Management

Patients in both groups were predominantly managed in the community by GPs and nurses.

Table 3 summarises the percentage of patients in each group who utilised different resources

during the study year.

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Insert Table 3

Table 4 shows the annual number of resources associated with managing 2.2 million patients

with a wound and 2.2 million control patients. The differences were considered to be the

incremental amounts of resource use attributable to managing 2.2 million wounds and

associated comorbidities and included 18.6 million practice nurse visits, 10.9 million

community nurse visits, 7.7 million GP visits, 3.4 million hospital outpatient visits, 97.1

million drug prescriptions, 262.2 million dressings, 73.4 million bandages and 9.0 million

compression bandages. Assessment of peripheral perfusion is a recognised requirement for

leg ulcer and diabetic foot management, yet only 16% of all cases with a leg or foot ulcer had

a Doppler ankle brachial pressure index recorded in their records.

Insert Table 4

The total annual NHS cost of managing 2.2 million patients with a wound was estimated to

be £6.0 billion (Table 5). The corresponding cost of managing the matched controls was £0.7

billion. Hence the total annual NHS cost of managing 2.2 million wounds and associated

comorbidities was estimated to be £5.3 billion. Of this, £1.65 billion and £3.67 billion was

associated with managing those wounds that healed and remained unhealed respectively.

Insert Table 5

66% of the total annual NHS cost was incurred in the community and the remainder in

secondary care. However, the distribution of costs varied according to wound type, with 48%

and 72% of the total annual NHS cost of managing acute and chronic wounds respectively

being incurred in the community and the remainder in secondary care.

Sensitivity Analyses

The estimated amounts of individual resource use were reduced and increased by 25%.

However, this only affected the total annual NHS cost of managing 2.2 million wounds and

associated comorbidities by 6% or less.

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The cost of an initial surgical procedure may not be relevant to the cost incurred in managing

an unhealed surgical wound. Therefore, a sensitivity analysis was performed to exclude this

cost from the cost of managing patients with an unhealed surgical wound. The analysis found

that when the cost of surgery was excluded from the cost of managing patients with an

unhealed surgical wound, the total annual NHS cost of managing 2.2 million wounds and

associated comorbidities was reduced from £5.3 billion to £4.8 billion.

When the NHS cost of managing patients was adjusted for their comorbidities (see

description of method 1 and 2 under Sensitivity Analyses), the total annual NHS cost of

managing 2.2 million wounds was reduced from £5.3 billion to £5.1 billion when method 1

was used and to £4.5 billion when method 2 was used. Hence, the total annual NHS cost of

managing the comorbidities among 2.2 million patients with a wound was estimated to be

between £250 and £788 million. After adjusting for comorbidities, the total annual NHS cost

of managing healed wounds and unhealed wounds was estimated to be £1.53 billion and

£3.49 billion respectively.

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DISCUSSION

This study estimated the health outcomes, resource implications and associated costs

attributable to managing wounds in 2012/13. After adjustment for comorbidities, the annual

NHS cost of managing wounds was estimated to be £4.5-5.1 billion, two-thirds of which is

incurred in the community and the rest in secondary care. This is comparable to the annual

NHS cost of managing obesity which was estimated at £5.0 billion in 2013 [13].

For patients to be included in the data set, they had to have had a wound in the study year or

be matched to these patients on the basis of their age, sex, the same general practice, and no

evidence of a wound in their medical history. Patients in both groups were managed primarily

by clinicians in the community. Only half the patients with a wound saw a hospital physician

although the consultation may not have been wound-related. However, the evidence shows

that wound management is predominantly a nurse-led discipline. Approximately 30% of

wounds lacked a differential diagnosis. This may be indicative of the practical difficulties

esperienced by non-specialist healthcare professionals in the community with establishing a

working diagnosis. Moreover, it appears that only 16% of patients with a leg or foot ulcer had

a Doppler. However, national guidance in the UK for both leg ulcer management and the

management of diabetic foot ulceration requires arterial assessment by Doppler ultrasound

measurement of the ankle-brachial pressure index [14,15]. Hence, these findings suggest (1)

the need to refer patients to a specialist for investigation and a differential diagnosis and a

shared management plan to be implemented in the community and (2) training of non-

specialist clinicians in the fundamentals of wound management. These two measures should

help overcome some of the problems encountered in clinical practice and achieve better

health outcomes, thereby reducing the high levels of resource use and corresponding costs,

and improving compliance with appropriate NICE and best practice guidelines. The study

highlighted that despite being a nurse-led discipline, there is a lack of involvement of tissue

viability nurses and other specialist nurses in the management of patients with wounds.

Recent articles [16,17] highlight the lack of a clear definition, and therefore confusion

regarding the role of these nurses.

The wound patients had significantly more comorbidities than their matched controls.

However, it was surprising to find such a high level of illness among the controls. For

example, 53% had cardiovascular disease. Moreover, 34% of patients with a wound and 13%

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of controls had nutritional deficiency that warranted supplementation with clinical nutritional

formulae. The THIN data set in this study covers the period 2012/13 and comprises patients

with a wide age range (19 to 98 years), so this level of illness may be a proxy for the health of

a proportion of the general population at that time. Furthermore, the presence of nutritional

deficiency was an independent risk factor for wound non-healing. Hence, community-

prevention of patients developing nutritional deficiency should help improve healing rates

following the onset of a wound. Moreover, if patients’ wounds and their comorbidities were

treated more holistically with appropriate involvement of allied healthcare professionals,

rather than just focusing on the wounds, better health outcomes might be achieved at lower

cost.

Other studies have assessed the prevalence and costs of wound care. A district-wide survey in

the Bradford and Airedale area of the U.K. estimated the annual NHS cost of wound care to

be £2.0 million per 100,000 population [18], which equates to £1.27 billion for the U.K. as a

whole. In another study, the NHS cost of caring for patients with a chronic wound was

estimated to be £2.3-3.1billion per year at 2005/06 prices [19]. Previous prevalence studies

suggest there may be up to 190,000 individuals with a venous leg ulcers in the U.K. at any

time [19]. However, this is likely to be an underestimate as our analysis estimated that the

NHS manages 278,000 venous leg ulcers per annum plus an additional 420,000 unspecified

leg ulcers (i.e. those lacking a true working diagnosis), some of which will undoubtedly be

venous in origin. The prevalence of pressure ulcers has been previously estimated to be 0.103

in 2005/06 [20], and another study estimated the incidence to be 400,000 new pressure ulcers

per annum in the U.K. [19]. These figures are substantially higher than our estimate of the

NHS managing 153,000 pressure ulcers per annum. The difference may be due to people

residing in nursing homes not having been included in our study. It may also be due to under-

recording of pressure ulcers in patients' records and/or an over-estimation in the previous

studies, and/or a lower prevalence in 2012/13 than in 2005/06. The present study also

estimated that 5% of patients with diabetes have a foot ulcer which is consistent with other

estimates [21].

The advantage of using the THIN database is that the patient pathways and associated

resource use are based on real world evidence derived from clinical practice. However, health

outcomes and resource use, whilst collected prospectively, were analysed retrospectively.

Moreover, there was no intention to match patients for comorbidities, since differences in

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comorbidities between the groups were an intended outcome of the study. Sensitivity

analyses estimated that the cost of managing the comorbidities ranged between £250 and

£788 million. Nevertheless, the possibility of resource use associated with managing a

comorbidity being conflated with that of wound managment cannot be excluded. Hence,

confounding factors may exist. While the study results are compelling, the analyses were

based on clinicians’ entries into their patients’ records and inevitably subject to a certain

amount of imprecision and lack of detail. Moreover, the computerised information in the

THIN database is collected by GPs for clinical care purposes and not for research.

Prescriptions issued by GPs and practice nurses are recorded in the database, but it does not

specify whether the prescriptions were dispensed or patient compliance with the product.

Despite these limitations, it is the Authors’ opinion that the THIN database affords one of the

best sources of real world evidence for clinical practice in the U.K.

The analysis does not consider the potential impact of those wounds that remained unhealed

beyond the study period, nor does it consider the potential impact of managing patients with

wounds being cared for in nursing/residential homes. The THIN database may have under-

recorded use of some healthcare resources outside the GP’s surgery if not documented in the

GP records, such as home visits made by clinicians, hospital outpatient visits, hospital

admissions and accident and emergency attendances. The impact of this was addressed in

sensitivity analyses. The analysis excludes hospital-based prescribing, but this should have

minimal impact on the results since most prescribing is undertaken by GPs and nurses in the

community.

The analysis only considered the annual cost of NHS resource use for the “average patient,”

and no attempt was made to stratify resource use and costs according to gender,

comorbidities, wound size, wound severity, and other disease-related factors. Also excluded

were the costs incurred by patients and indirect costs incurred by society as a result of

patients taking time off work. However, patients’ mean age was >65 years, so it is unlikely

that many were in employment.

Notwithstanding the study's limitations, the real world evidence in our study demonstrates

that wounds impose a substantial health economic burden on the U.K.’s NHS, comparable to

that of managing obesity. Clinical and economic benefits could accrue from improved

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systems of care and an increased awareness of the impact that wounds impose on both

patients and the NHS.

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CONFLICTS OF INTEREST

The authors have no potential conflicts of interest relevant to this article.

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FUNDING

This study was commisioned and funded by the NIHR Wound Prevention and Treatment

Healthcare Technology Co-operative (NIHR WoundTec HTC), Bradford Institute For Health

Research, Bradford, West Yorkshire, U.K. following an open tendering process. Additional

funding was provided by 3M Limited, Loughborough, Leicestershire, U.K.; Activa

Healthcare Limited, Burton On Trent, Staffordshire, U.K.; Blanson Limited, Narborough,

Leicestershire, U.K.; Brightwake Limited, Kirkby In Ashfield, Nottinghamshire, U.K.; KCI

Medical Limited, Crawley, West Sussex, U.K.; Medira Ltd, Cambridge, Cambridgeshire,

U.K.; Molnlycke Health Care Limited, Dunstable, Bedfordshire, U.K.; Park House

Healthcare Limited, Elland, West Yorkshire, U.K.; Perfectus Biomed Ltd, Daresbury,

Warrington, U.K.; Smith & Nephew Medical Limited, Hull, East Riding Of Yorkshire, U.K.;

Sozo Woundcare Limited, Harrogate, North Yorkshire, U.K.; Systagenix Wound

Management Limited, Gatwick Airport, West Sussex, U.K.; Urgo Limited, Loughborough,

Leicestershire, U.K.; Willingsford Limited, Southampton, Hampshire, U.K.

The study’s sponsors had no involvement in the study design, the collection, analysis and

interpretation of the data, the writing of this manuscript and the decision to submit this article

for publication.The views expressed in this article are those of the authors and not necessarily

those of the NHS, the NIHR, the Department of Health or any of the other sponsors.

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AUTHORS' CONTRIBUTION

J.F.G. designed the study, managed the analyses, performed some analyses, checked all the

other analyses, and wrote the manuscript.

N.A. and T.M conducted much of the analyses.

I.U. and A.G conducted some of the analyses.

D.W. scrutinized the analyses and edited the manuscript.

K.V and P.V scrutinized the analyses, suggested further analyses, helped interpret some of

the findings, and edited the manuscript.

J.F.G. is the guarantor of this work and, as such, had full access to all the data in the study

and takes responsibility for the integrity of the data and the accuracy of the data analysis.

The analyses have also been reviewed by the following strategic partners of the NIHR

Bradford Wound Prevention & Treatment Healthcare Technology Co-operative

(www.woundtec.htc.nihr.ac.uk): Prof Andrea Nelson, Head of School of Healthcare,

University of Leeds, Leeds; Prof Jane Nixon, Deputy Director, Leeds Institute of Clinical

Trials Research, Leeds; Professor Dan L Bader, Faculty of Health Sciences, University of

Southampton, Southampton; Dr Patricia Grocott, Reader in Palliative Wound Care

Technology Transfer, King's College, London; Hussein Dharma, Project Manager, NIHR

WoundTec Healthcare Technology Co-operative, Bradford Institute for Health Research,

Bradford.

The Corresponding Author has the right to grant on behalf of all authors and does grant on

behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in

all forms, formats and media (whether known now or created in the future), to i) publish,

reproduce, distribute, display and store the Contribution, ii) translate the Contribution into

other languages, create adaptations, reprints, include within collections and create summaries,

extracts and/or, abstracts of the Contribution and convert or allow conversion into any format

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including without limitation audio, iii) create any other derivative work(s) based in whole or

part on the on the Contribution, iv) to exploit all subsidiary rights to exploit all subsidiary

rights that currently exist or as may exist in the future in the Contribution, v) the inclusion of

electronic links from the Contribution to third party material where-ever it may be located;

and, vi) licence any third party to do any or all of the above.

DATA SHARINGDATA SHARINGDATA SHARINGDATA SHARING

No additional data available.

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Percentage of patients

Comorbidity Cases Controls p value

Cardiovascular 73% 53% <0.005

Dermatological 59% 25% <0.001

Endocrinological 45% 27% <0.01

Gastroenterological 43% 25% <0.01

Immunological 3% 0% ns

Musculoskeletal 37% 19% <0.005

Neurological 23% 13% ns

Nutritional deficiency 34% 13% <0.001

Other 14% 7% ns

Psychiatric 31% 18% <0.05

Respiratory 28% 15% ns

None 6% 23% <0.001

Table 1: Percentage of patients with a comorbidity in the year

before the start of their wound.

If the p value was ≥0.05 it was considered not significant (ns).

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Annual number of

wounds

Annual prevalence among

the adult U.K. population

Abscess 160,000 (7%) 0.0032

Burn 87,000 (4%) 0.0018

Diabetic foot ulcer 169,000 (8%) 0.0034

Leg ulcer (arterial) 9,000 (<1%) 0.0002

Leg ulcer (mixed) 24,000 (1%) 0.0005

Leg ulcer (unspecified) 420,000 (19%) 0.0085

Leg ulcer (venous) 278,000 (13%) 0.0056

Open wound 240,000 (11%) 0.0048

Pressure ulcer 153,000 (7%) 0.0031

Surgical wound 253,000 (11%) 0.0051

Trauma 158,000 (7%) 0.0032

Unspecified 271,000 (12%) 0.0055

Total 2,222,000 (100%) 0.0447

Table 2: Annual number and prevalence of different wound types

in the U.K. among the adult population (i.e. ≥≥≥≥ 18 years of age)

estimated from the THIN database.

Percentage of total number of wounds is in parentheses.

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Percentage of patients

Resource Cases Controls p value

GP visits 86% 47% <0.001

Practise nurse visits 72% 29% <0.001

Community nurse visits 75% 2% <0.001

Specialist nurse visits 2% <1% ns

Allied healthcare visits 14% 3% 0.005

Hospital outpatient visits 53% 18% <0.001

Hospital admissions and day cases 29% 6% <0.001

Ambulance services <1% <1% ns

Accident and emergency attendances <1% <1% ns

Diagnostic tests 80% 45% <0.001

Non-wound care devices 36% 5% <0.001

Wound care products 100% 0% <0.001

Prescriptions for individual drugs 98% 72% <0.001

Table 3: Percentage of patients who utilised resources in the study year.

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Annual number

Resource Cases Controls Difference p value

GP visits 10,816,655 3,124,120 7,692,535 <0.001

Practise nurse visits 19,744,618 1,184,322 18,560,296 <0.001

Community nurse visits 10,932,199 75,548 10,856,651 <0.001

Specialist nurse visits 51,106 4,444 46,662 <0.001

Allied healthcare visits 537,722 77,770 459,952 <0.001

Hospital outpatient visits 4,277,334 828,803 3,448,531 <0.001

Hospital admissions and day cases 1,142,104 173,315 968,788 <0.001

Ambulance services 11,110 2,222 8,888 ns

Accident and emergency attendances 11,110 11,110 - ns

Diagnostic tests 60,284,855 24,068,613 36,216,242 <0.001

Devices 320,938,916 48,206,108 272,732,808 <0.001

Wound care products 354,954,275 13,332 354,940,943 <0.001

Prescriptions for individual drugs 135,859,234 38,769,310 97,089,924 <0.001

Table 4: Annual amount of NHS resource use attributable to managing 2.2 million patients with

a wound and 2.2 million matched controls.

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Annual cost

Resource Cases Controls Difference

GP visits £514,993,223 £145,951,520 £369,041,702

Practise nurse visits £256,760,021 £15,396,180 £241,363,841

Community nurse visits £682,382,518 £3,026,353 £679,356,166

Specialist nurse visits £3,650,732 £322,189 £3,328,543

Allied healthcare visits £34,451,980 £4,859,496 £29,592,485

Hospital outpatient visits £515,002,111 £99,947,406 £415,054,705

Hospital admissions and day cases £1,334,299,309 £135,277,073 £1,199,022,237

Ambulance services £2,555,290 £511,058 £2,044,232

Accident and emergency attendances £666,597 £666,597 £0

Diagnostic tests £282,646,224 £113,238,466 £169,407,758

Devices £282,261,975 £17,525,292 £264,736,682

Wound care products £742,703,819 £185,181 £742,518,638

Prescriptions for individual drugs £1,390,246,214 £187,989,869 £1,202,256,346

TOTAL £6,042,620,014 £724,896,679 £5,317,723,335

Table 5: Annual cost of NHS resource use attributable to managing 2.2 million

patients with a wound and 2.2 million matched controls.

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STROBE 2007 (v4) Statement—Checklist of items that should be included in reports of case-control studies

Section/Topic Item

# Recommendation

Reported on

page #

Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract 1,7

(b) Provide in the abstract an informative and balanced summary of what was done and what was found 1

Introduction

Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 6

Objectives 3 State specific objectives, including any prespecified hypotheses 6

Methods

Study design 4 Present key elements of study design early in the paper 7

Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection 7,8

Participants 6 (a) Give the eligibility criteria, and the sources and methods of case ascertainment and control selection. Give the rationale for

the choice of cases and controls

7,8

(b) For matched studies, give matching criteria and the number of controls per case 7,8

Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if

applicable

9

Data sources/

measurement

8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability

of assessment methods if there is more than one group

9

Bias 9 Describe any efforts to address potential sources of bias 9,10

Study size 10 Explain how the study size was arrived at 9

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Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why 9

Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding 9,10

(b) Describe any methods used to examine subgroups and interactions 9,10

(c) Explain how missing data were addressed N/A

(d) If applicable, explain how matching of cases and controls was addressed 8-10

(e) Describe any sensitivity analyses 10

Results

Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, confirmed

eligible, included in the study, completing follow-up, and analysed

10,11

(b) Give reasons for non-participation at each stage N/A

(c) Consider use of a flow diagram N/A

Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential

confounders

11

(b) Indicate number of participants with missing data for each variable of interest N/A

Outcome data 15* Report numbers in each exposure category, or summary measures of exposure 11,12,21,22

Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence

interval). Make clear which confounders were adjusted for and why they were included

12,13,23-25

(b) Report category boundaries when continuous variables were categorized 12,13,23-25

(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period N/A

Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses 13,14

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Discussion

Key results 18 Summarise key results with reference to study objectives 15

Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision.

Discuss both direction and magnitude of any potential bias

15-17

Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar

studies, and other relevant evidence

16

Generalisability 21 Discuss the generalisability (external validity) of the study results 16,17

Other information

Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on which the

present article is based

3

*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.

Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE

checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at

http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.

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