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Scantlebury A, Sivey P, Anteneh Z, Ayres B, Bloor K, Castelli A, Castro-Avila AC, Davies F, Davies S, Glerum-Brooks K, Gutacker N, Lampard P, Rangan A, Saad A, Street A, Wen J, Adamson J. Mixed Methods EvAluation of the high-volume low-complexity Surgical hUb pRogrammE (MEASURE): a mixed methods study protocol. BMJ Open 2024; 14:e086338. [PMID: 38643003 PMCID: PMC11033628 DOI: 10.1136/bmjopen-2024-086338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 03/25/2024] [Indexed: 04/22/2024] Open
Abstract
INTRODUCTION The waiting list for elective surgery in England recently reached over 7.8 million people and waiting time targets have been missed since 2010. The high-volume low complexity (HVLC) surgical hubs programme aims to tackle the backlog of patients awaiting elective surgery treatment in England. This study will evaluate the impact of HVLC surgical hubs on productivity, patient care and the workforce. METHODS AND ANALYSIS This 4-year project consists of six interlinked work packages (WPs) and is informed by the Consolidated Framework for Implementation Research. WP1: Mapping current and future HVLC provision in England through document analysis, quantitative data sets (eg, Hospital Episodes Statistics) and interviews with national service leaders. WP2: Exploring the effects of HVLC hubs on key performance outcomes, primarily the volume of low-complexity patients treated, using quasi-experimental methods. WP3: Exploring the impact and implementation of HVLC hubs on patients, health professionals and the local NHS through approximately nine longitudinal, multimethod qualitative case studies. WP4: Assessing the productivity of HVLC surgical hubs using the Centre for Health Economics NHS productivity measure and Lord Carter's operational productivity measure. WP5: Conducting a mixed-methods appraisal will assess the influence of HVLC surgical hubs on the workforce using: qualitative data (WP3) and quantitative data (eg, National Health Service (NHS) England's workforce statistics and intelligence from WP2). WP6: Analysing the costs and consequences of HVLC surgical hubs will assess their achievements in relation to their resource use to establish value for money. A patient and public involvement group will contribute to the study design and materials. ETHICS AND DISSEMINATION The study has been approved by the East Midlands-Nottingham Research Ethics Committee 23/EM/0231. Participants will provide informed consent for qualitative study components. Dissemination plans include multiple academic and non-academic outputs (eg, Peer-reviewed journals, conferences, social media) and a continuous, feedback-loop of findings to key stakeholders (eg, NHS England) to influence policy development. TRIAL REGISTRATION Research registry: Researchregistry9364 (https://www.researchregistry.com/browse-the-registry%23home/registrationdetails/64cb6c795cbef8002a46f115/).
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Affiliation(s)
| | - Peter Sivey
- Centre for Health Economics, University of York, York, Yorkshire, UK
| | - Zecharias Anteneh
- Centre for Health Economics, University of York, York, Yorkshire, UK
| | - Ben Ayres
- St George's University Hospitals NHS Foundation Trust, London, UK
| | - Karen Bloor
- Department of Health Sciences, University of York, York, Yorkshire, UK
| | - Adriana Castelli
- Centre for Health Economics, University of York, York, Yorkshire, UK
| | | | - Firoza Davies
- York Trials Unit, Department of Health Sciences, University of York, York, UK
| | - Simon Davies
- Centre for Health and Population Sciences, Hull York Medical School, Hull, UK
| | - Karen Glerum-Brooks
- York Trials Unit, Department of Health Sciences, University of York, York, UK
| | - Nils Gutacker
- Centre for Health Economics, University of York, York, Yorkshire, UK
| | - Pete Lampard
- Department of Health Sciences, University of York, York, Yorkshire, UK
| | - Amar Rangan
- Department of Health Sciences, University of York, York, Yorkshire, UK
- Trauma and Orthopaedics, James Cook University Hospital, Middlesbrough, UK
| | - Ahmed Saad
- Opthamology, James Cook University Hospital, Middlesbrough, UK
- Hull York Medical School, Hull, UK
| | | | - Jinglin Wen
- Centre for Health Economics, University of York, York, Yorkshire, UK
| | - Joy Adamson
- York Trials Unit, Department of Health Sciences, University of York, York, UK
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Bodnar O, Gravelle H, Gutacker N, Herr A. Financial incentives and prescribing behavior in primary care. Health Econ 2024; 33:696-713. [PMID: 38151480 DOI: 10.1002/hec.4793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 11/29/2023] [Accepted: 12/04/2023] [Indexed: 12/29/2023]
Abstract
Many healthcare systems prohibit primary care physicians from dispensing the drugs they prescribe due to concerns that this encourages excessive, ineffective or unnecessarily costly prescribing. Using data from the English National Health Service for 2011-2018, we estimate the impact of physician dispensing rights on prescribing behavior at the extensive margin (comparing practices that dispense and those that do not) and the intensive margin (comparing practices with different proportions of patients to whom they dispense). We control for practices selecting into dispensing based on observable (OLS, entropy balancing) and unobservable practice characteristics (2SLS). We find that physician dispensing increases drug costs per patient by 3.1%, due to more, and more expensive, drugs being prescribed. Reimbursement is partly based on a fixed fee per package dispensed and we find that dispensing practices prescribe smaller packages. As the proportion of the practice population for whom they can dispense increases, dispensing practices behave more like non-dispensing practices.
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Affiliation(s)
- Olivia Bodnar
- DICE, Heinrich-Heine-University, Düsseldorf, Germany
| | - Hugh Gravelle
- Centre for Health Economics, University of York, York, UK
| | - Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | - Annika Herr
- DICE, Heinrich-Heine-University, Düsseldorf, Germany
- Institute of Health Economics, Leibniz University, Hannover, Germany
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Fabiano G, Cole S, Barea C, Cullati S, Agoritsas T, Gutacker N, Silman A, Hannouche D, Lübbeke A, Pinedo-Villanueva R. Patients' experience on pain outcomes after hip arthroplasty: insights from an information tool based on registry data. BMC Musculoskelet Disord 2024; 25:255. [PMID: 38561701 PMCID: PMC10986127 DOI: 10.1186/s12891-024-07357-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 03/13/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Arthroplasty registries are rarely used to inform encounters between clinician and patient. This study is part of a larger one which aimed to develop an information tool allowing both to benefit from previous patients' experience after total hip arthroplasty (THA). This study focuses on generating the information tool specifically for pain outcomes. METHODS Data from the Geneva Arthroplasty Registry (GAR) about patients receiving a primary elective THA between 1996 and 2019 was used. Selected outcomes were identified from patient and surgeon surveys: pain walking, climbing stairs, night pain, pain interference, and pain medication. Clusters of patients with homogeneous outcomes at 1, 5, and 10 years postoperatively were generated based on selected predictors evaluated preoperatively using conditional inference trees (CITs). RESULTS Data from 6,836 THAs were analysed and 14 CITs generated with 17 predictors found significant (p < 0.05). Baseline WOMAC pain score, SF-12 self-rated health (SRH), number of comorbidities, SF-12 mental component score, and body mass index (BMI) were the most common predictors. Outcome levels varied markedly by clusters whilst predictors changed at different time points for the same outcome. For example, 79% of patients with good to excellent SRH and less than moderate preoperative night pain reported absence of night pain at 1 year after THA; in contrast, for those with fair/poor SHR this figure was 50%. Also, clusters of patients with homogeneous levels of night pain at 1 year were generated based on SRH, Charnley, WOMAC night and pain scores, whilst those at 10 years were based on BMI alone. CONCLUSIONS The information tool generated under this study can provide prospective patients and clinicians with valuable and understandable information about the experiences of "patients like them" regarding their pain outcomes.
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Affiliation(s)
- Gianluca Fabiano
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Sophie Cole
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Christophe Barea
- Division of Orthopaedics & Trauma Surgery, University Hospitals of Geneva, Geneva, Switzerland
| | - Stéphane Cullati
- Quality of Care Service, University Hospitals of Geneva, Geneva, Switzerland
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
| | - Thomas Agoritsas
- Division General Internal Medicine, University Hospitals of Geneva, Geneva, Switzerland
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Ontario, Canada
- MAGIC Evidence Ecosystem Foundation, Lovisenbergetta, 17C, Oslo, Norway
| | - Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | - Alan Silman
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Didier Hannouche
- Division of Orthopaedics & Trauma Surgery, University Hospitals of Geneva, Geneva, Switzerland
| | - Anne Lübbeke
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
- Division of Orthopaedics & Trauma Surgery, University Hospitals of Geneva, Geneva, Switzerland
| | - Rafael Pinedo-Villanueva
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
- Oxford NIHR Biomedical Research Centre, Oxford, UK.
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Anderson M, Gutacker N, Wimmer S, Mossialos E. Information gaps in England's independent healthcare sector. BMJ 2024; 384:e079261. [PMID: 38503446 DOI: 10.1136/bmj-2024-079261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/21/2024]
Affiliation(s)
- Michael Anderson
- Health Organisation, Policy, Economics (HOPE), Centre for Primary Care and Health Services Research, University of Manchester, Manchester, UK
- LSE Health, Department of Health Policy, London School of Economics and Political Science, London, UK
| | - Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | - Sabrina Wimmer
- Manchester University NHS Foundation Trust, Manchester, UK
| | - Elias Mossialos
- Health Organisation, Policy, Economics (HOPE), Centre for Primary Care and Health Services Research, University of Manchester, Manchester, UK
- Institute of Global Health Innovation, Imperial College London, London, UK
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Aragón MJ, Gravelle H, Castelli A, Goddard M, Gutacker N, Mason A, Rowen D, Mannion R, Jacobs R. Measuring the overall performance of mental healthcare providers. Soc Sci Med 2024; 344:116582. [PMID: 38394864 DOI: 10.1016/j.socscimed.2024.116582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 12/27/2023] [Accepted: 01/08/2024] [Indexed: 02/25/2024]
Abstract
To date there have been no attempts to construct composite measures of healthcare provider performance which reflect preferences for health and non-health benefits, as well as costs. Health and non-health benefits matter to patients, healthcare providers and the general public. We develop a novel provider performance measurement framework that combines health gain, non-health benefit, and cost and illustrate it with an application to 54 English mental health providers. We apply estimates from a discrete choice experiment eliciting the UK general population's valuation of non-health benefits relative to health gains, to administrative and patient survey data for years 2013-2015 to calculate equivalent health benefit (eHB) for providers. We measure costs as forgone health and quantify the relative performance of providers in terms of equivalent net health benefit (eNHB): the value of the health and non-health benefits minus the forgone benefit equivalent of cost. We compare rankings of providers by eHB, eNHB, and by the rankings produced by the hospital sector regulator. We find that taking account of the non-health benefits in the eNHB measure makes a substantial difference to the evaluation of provider performance. Our study demonstrates that the provider performance evaluation space can be extended beyond measures of health gain and cost, and that this matters for comparison of providers.
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Affiliation(s)
- María José Aragón
- HCD Economics, Daresbury Innovation Centre, Keckwick Lane, Daresbury, Warrington, WA4 4FS, UK
| | - Hugh Gravelle
- Centre for Health Economics, University of York, Heslington York, YO10 5DD, UK
| | - Adriana Castelli
- Centre for Health Economics, University of York, Heslington York, YO10 5DD, UK
| | - Maria Goddard
- Centre for Health Economics, University of York, Heslington York, YO10 5DD, UK
| | - Nils Gutacker
- Centre for Health Economics, University of York, Heslington York, YO10 5DD, UK
| | - Anne Mason
- Centre for Health Economics, University of York, Heslington York, YO10 5DD, UK
| | - Donna Rowen
- Sheffield Centre for Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
| | - Russell Mannion
- Health Services Management Centre, School of Social Policy, Park House, University of Birmingham, Edgbaston, Birmingham, B15 2RT, UK
| | - Rowena Jacobs
- Centre for Health Economics, University of York, Heslington York, YO10 5DD, UK.
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Matias MA, Jacobs R, Aragón MJ, Fernandes L, Gutacker N, Siddiqi N, Kasteridis P. Assessing the uptake of incentivised physical health checks for people with serious mental illness. Br J Gen Pract 2024:BJGP.2023.0532. [PMID: 38331443 DOI: 10.3399/bjgp.2023.0532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 01/29/2024] [Indexed: 02/10/2024] Open
Abstract
BACKGROUND People with serious mental illness (SMI) are more likely to suffer from physical illnesses. The onset of many of these illnesses can be prevented if detected early. Physical health screening for people with SMI is incentivised in primary care in England through the Quality and Outcomes Framework (QOF). General Practitioners are paid to conduct annual physical health checks (PHCs) on their SMI patients, including checks on body mass index (BMI), cholesterol, and alcohol consumption. AIM To assess the impact of removing and reintroducing QOF financial incentives on uptake of three PHCs (BMI, cholesterol, and alcohol consumption) for patients with SMI. DESIGN AND SETTING Cohort study using UK primary care data from the Clinical Practice Research Datalink between April 2011 and March 2020. METHOD We employed a difference-in-difference analysis to compare differences in the uptake before and after the intervention accounting for relevant observed and unobserved confounders. RESULTS We found an immediate change in uptake after PHCs were removed from, and after they were added back to the QOF list. For BMI, cholesterol, and alcohol checks the overall impact of removal was a reduction in uptake of 14.3, 6.8, and 11.9 percentage points, respectively. The reintroduction of BMI screening in the QOF increased the uptake by 10.2 percentage points. CONCLUSION Our analysis supports the hypothesis that QOF incentives lead to better uptake of PHCs.
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Affiliation(s)
- Maria Ana Matias
- University of York, Centre for Health Economics, York, United Kingdom
| | - Rowena Jacobs
- University of York, Centre for Health Economics, York, United Kingdom
| | | | | | - Nils Gutacker
- University of York, Centre for Health Economics, York, United Kingdom
| | - Najma Siddiqi
- University of York, Centre for Health Economics, York, United Kingdom
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Villaseñor A, Gaughan J, Aragón Aragón MJM, Gutacker N, Gravelle H, Goddard M, Mason A, Castelli A, Jacobs R. The impact of COVID-19 on mental health service utilisation in England. SSM Ment Health 2023; 3:100227. [PMID: 37292123 PMCID: PMC10234368 DOI: 10.1016/j.ssmmh.2023.100227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 05/15/2023] [Accepted: 05/24/2023] [Indexed: 06/10/2023] Open
Abstract
The COVID-19 pandemic has had a significant impact on population mental health and the need for mental health services in many countries, while also disrupting critical mental health services and capacity, as a response to the pandemic. Mental health providers were asked to reconfigure wards to accommodate patients with COVID-19, thereby reducing capacity to provide mental health services. This is likely to have widened the existing mismatch between demand and supply of mental health care in the English NHS. We quantify the impact of these rapid service reconfigurations on activity levels for mental health providers in England during the first thirteen months (March 2020-March 2021) of the COVID-19 pandemic. We use monthly mental health service utilisation data for a large subset of mental health providers in England from January 1, 2015 to March 31, 2021. We use multivariate regression to estimate the difference between observed and expected utilisation from the start of the pandemic in March 2020. Expected utilisation levels (i.e. the counterfactual) are estimated from trends in utilisation observed during the pre-pandemic period January 1, 2015 to February 31, 2020. We measure utilisation as the monthly number of inpatient admissions, discharges, net admissions (admissions less discharges), length of stay, bed days, number of occupied beds, patients with outpatient appointments, and total outpatient appointments. We also calculate the accumulated difference in utilisation from the start of the pandemic period. There was a sharp reduction in total inpatient admissions and net admissions at the beginning of the pandemic, followed by a return to pre-pandemic levels from September 2020. Shorter inpatient stays are observed over the whole period and bed days and occupied bed counts had not recovered to pre-pandemic levels by March 2021. There is also evidence of greater use of outpatient appointments, potentially as a substitute for inpatient care.
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Affiliation(s)
- Adrián Villaseñor
- Centre for Health Economics (CHE), University of York, United Kingdom
| | - James Gaughan
- Centre for Health Economics (CHE), University of York, United Kingdom
| | | | - Nils Gutacker
- Centre for Health Economics (CHE), University of York, United Kingdom
| | - Hugh Gravelle
- Centre for Health Economics (CHE), University of York, United Kingdom
| | - Maria Goddard
- Centre for Health Economics (CHE), University of York, United Kingdom
| | - Anne Mason
- Centre for Health Economics (CHE), University of York, United Kingdom
| | - Adriana Castelli
- Centre for Health Economics (CHE), University of York, United Kingdom
| | - Rowena Jacobs
- Centre for Health Economics (CHE), University of York, United Kingdom
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Gutacker N, Kinge JM, Olsen JA. Inequality in quality-adjusted life expectancy by educational attainment in Norway: an observational study. BMC Public Health 2023; 23:805. [PMID: 37138293 PMCID: PMC10155341 DOI: 10.1186/s12889-023-15663-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 04/12/2023] [Indexed: 05/05/2023] Open
Abstract
BACKGROUND Health inequalities are often assessed in terms of life expectancy or health-related quality of life (HRQoL). Few studies combine both aspects into quality-adjusted life expectancy (QALE) to derive comprehensive estimates of lifetime health inequality. Furthermore, little is known about the sensitivity of estimated inequalities in QALE to different sources of HRQoL information. This study assesses inequalities in QALE by educational attainment in Norway using two different measures of HRQoL. METHODS We combine full population life tables from Statistics Norway with survey data from the Tromsø study, a representative sample of the Norwegian population aged ≥ 40. HRQoL is measured using the EQ-5D-5L and EQ-VAS instruments. Life expectancy and QALE at 40 years of age are calculated using the Sullivan-Chiang method and are stratified by educational attainment. Inequality is measured as the absolute and relative gap between individuals with lowest (i.e. primary school) and highest (university degree 4 + years) educational attainment. RESULTS People with the highest educational attainment can expect to live longer lives (men: + 17.9% (95%CI: 16.4 to 19.5%), women: + 13.0% (95%CI: 10.6 to 15.5%)) and have higher QALE (men: + 22.4% (95%CI: 20.4 to 24.4%), women: + 18.3% (95%CI: 15.2 to 21.6%); measured using EQ-5D-5L) than individuals with primary school education. Relative inequality is larger when HRQoL is measured using EQ-VAS. CONCLUSION Health inequalities by educational attainment become wider when measured in QALE rather than LE, and the degree of this widening is larger when measuring HRQoL by EQ-VAS than by EQ-5D-5L. We find a sizable educational gradient in lifetime health in Norway, one of the most developed and egalitarian societies in the world. Our estimates provide a benchmark against which other countries can be compared.
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Affiliation(s)
- Nils Gutacker
- Centre for Health Economics, University of York, Alcuin A Block, Heslington, YO10 5DD, UK.
| | - Jonas Minet Kinge
- Norwegian Institute of Public Health, Oslo, Norway
- Department of Health Management and Health Economics, University of Oslo, Oslo, Norway
| | - Jan Abel Olsen
- Norwegian Institute of Public Health, Oslo, Norway
- Department of Community Medicine, UiT - the Arctic University of Norway, Tromsø, Norway
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Love-Koh J, Schneider P, McNamara S, Doran T, Gutacker N. Decomposition of Quality-Adjusted Life Expectancy Inequalities by Mortality and Health-Related Quality of Life Dimensions. Pharmacoeconomics 2023; 41:831-841. [PMID: 37129775 DOI: 10.1007/s40273-023-01264-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/06/2023] [Indexed: 05/03/2023]
Abstract
BACKGROUND Quality-adjusted life expectancy (QALE) combines mortality risk and multidimensional health-related quality of life (HRQoL) information to measure healthy life expectancy in terms of quality-adjusted life years (QALYs). This paper estimates the relative importance of individual quality of life dimensions in explaining inequalities in QALE. METHODS We combined EQ-5D-5L data from the Health Survey for England for 2017 and 2018 (N = 14,412) with full population mortality data from the Office for National Statistics to calculate QALE by age, sex and deprivation quintile. The effect of HRQoL dimensions on the socioeconomic gradient in QALE was decomposed using an iterative imputation approach, in which inequalities associated with socioeconomic status in each domain were removed by imputing the response distribution of the richest quintile for all participants. Sampling uncertainty in the HRQoL data was evaluated using bootstrapping. RESULTS People in the least deprived fifth of neighbourhoods in England can expect to live 7.0 years longer and experience 11.1 more QALYs than those in the most deprived fifth. Inequalities in HRQoL accounted for 28.0% and 45.7% of QALE inequalities for males and females, respectively. Pain/discomfort, anxiety/depression and mobility were the most influential HRQoL domains. DISCUSSION Our results identify the extent of inequalities associated with socioeconomic status in lifetime health and the relative importance of inequalities by mortality and HRQoL. The contributions of the individual dimensions of HRQoL towards lifetime inequalities vary substantially by sex. Our findings can help to identify the types of interventions most likely to alleviate health inequalities, which may be different for males and females.
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Affiliation(s)
- James Love-Koh
- Centre for Health Economics, University of York, York, UK.
- National Institute for Health and Care Excellence, Manchester, UK.
| | - Paul Schneider
- School of Health and Related Research, University of Sheffield, Sheffield, UK
| | - Simon McNamara
- School of Health and Related Research, University of Sheffield, Sheffield, UK
- Lumanity, Sheffield, UK
| | - Tim Doran
- Department of Health Sciences, University of York, York, UK
| | - Nils Gutacker
- Centre for Health Economics, University of York, York, UK
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Ride J, Kasteridis P, Gutacker N, Gravelle H, Rice N, Mason A, Goddard M, Doran T, Jacobs R. Impact of prevention in primary care on costs in primary and secondary care for people with serious mental illness. Health Econ 2023; 32:343-355. [PMID: 36309945 PMCID: PMC10092448 DOI: 10.1002/hec.4623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 10/13/2022] [Accepted: 10/15/2022] [Indexed: 06/16/2023]
Abstract
A largely unexplored part of the financial incentive for physicians to participate in preventive care is the degree to which they are the residual claimant from any resulting cost savings. We examine the impact of two preventive activities for people with serious mental illness (care plans and annual reviews of physical health) by English primary care practices on costs in these practices and in secondary care. Using panel two-part models to analyze patient-level data linked across primary and secondary care, we find that these preventive activities in the previous year are associated with cost reductions in the current quarter both in primary and secondary care. We estimate that there are large beneficial externalities for which the primary care physician is not the residual claimant: the cost savings in secondary care are 4.7 times larger than the cost savings in primary care. These activities are incentivized in the English National Health Service but the total financial incentives for primary care physicians to participate were considerably smaller than the total cost savings produced. This suggests that changes to the design of incentives to increase the marginal reward for conducting these preventive activities among patients with serious mental illness could have further increased welfare.
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Affiliation(s)
- Jemimah Ride
- Health Economics UnitMelbourne School of Population and Global HealthUniversity of MelbourneParkvilleVictoriaAustralia
| | | | | | | | - Nigel Rice
- Centre for Health EconomicsUniversity of YorkYorkUK
| | - Anne Mason
- Centre for Health EconomicsUniversity of YorkYorkUK
| | | | - Tim Doran
- Health SciencesUniversity of YorkYorkUK
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McNamara S, Schneider PP, Love-Koh J, Doran T, Gutacker N. Quality-Adjusted Life Expectancy Norms for the English Population. Value in Health 2023; 26:163-169. [PMID: 35965226 DOI: 10.1016/j.jval.2022.07.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Revised: 06/21/2022] [Accepted: 07/05/2022] [Indexed: 06/15/2023]
Abstract
OBJECTIVES The National Institute for Health and Care Excellence in England has implemented severity-of-disease modifiers that give greater weight to health benefits accruing to patients who experience a larger shortfall in quality-adjusted life-years (QALYs) under current standard of care than healthy individuals. This requires an estimate of quality-adjusted life expectancy (QALE) of the general population based on age and sex. Previous QALE population norms are based on nearly 30-year-old assessments of health-related quality of life in the general population. This study provides updated QALE estimates for the English population based on age and sex. METHODS 5-level version of EQ-5D data for 14 412 participants from the Health Survey for England (waves 2017 and 2018) were pooled, and health-related quality of life population norms were calculated. These norms were combined with official life tables from the Office for National Statistics for 2017 to 2019 using the Sullivan method to derive QALE estimates based on age and sex. Values were discounted using 0%, 1.5%, and 3.5% discount rates. RESULTS QALE at birth is 68.24 QALYs for men and 68.21 QALYs for women. These values are significantly lower than previously published QALE population norms based on the older 3-level version of EQ-5D data. CONCLUSION This study provides new QALE population norms for England that serve to establish absolute and relative QALY shortfalls for the purpose of health technology assessments.
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Affiliation(s)
- Simon McNamara
- Lumanity, Sheffield, England, UK; School of Health and Related Research, University of Sheffield, Sheffield, England, UK.
| | - Paul P Schneider
- School of Health and Related Research, University of Sheffield, Sheffield, England, UK
| | - James Love-Koh
- Centre for Health Economics, University of York, York, England, UK; The National Institute for Health and Care Excellence, London, England, UK
| | - Tim Doran
- Department of Health Sciences, University of York, York, England, UK
| | - Nils Gutacker
- Centre for Health Economics, University of York, York, England, UK
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Scantlebury A, Adamson J, Salisbury C, Brant H, Anderson H, Baxter H, Bloor K, Cowlishaw S, Doran T, Gaughan J, Gibson A, Gutacker N, Leggett H, Purdy S, Voss S, Benger JR. Do general practitioners working in or alongside the emergency department improve clinical outcomes or experience? A mixed-methods study. BMJ Open 2022; 12:e063495. [PMID: 36127084 PMCID: PMC9490584 DOI: 10.1136/bmjopen-2022-063495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
OBJECTIVES To examine the effect of general practitioners (GPs) working in or alongside the emergency department (GPED) on patient outcomes and experience, and the associated impacts of implementation on the workforce. DESIGN Mixed-methods study: interviews with service leaders and NHS managers; in-depth case studies (n=10) and retrospective observational analysis of routinely collected national data. We used normalisation process theory to map our findings to the theory's four main constructs of coherence, cognitive participation, collective action and reflexive monitoring. SETTING AND PARTICIPANTS Data were collected from 64 EDs in England. Case site data included: non-participant observation of 142 clinical encounters; 467 semistructured interviews with policy-makers, service leaders, clinical staff, patients and carers. Retrospective observational analysis used routinely collected Hospital Episode Statistics alongside information on GPED service hours from 40 hospitals for which complete data were available. RESULTS There was disagreement at individual, stakeholder and organisational levels regarding the purpose and potential impact of GPED (coherence). Participants criticised policy development and implementation, and staff engagement was hindered by tensions between ED and GP staff (cognitive participation). Patient 'streaming' processes, staffing and resource constraints influenced whether GPED became embedded in routine practice. Concerns that GPED may increase ED attendance influenced staff views. Our quantitative analysis showed no detectable impact on attendance (collective action). Stakeholders disagreed whether GPED was successful, due to variations in GPED model, site-specific patient mix and governance arrangements. Following statistical adjustment for multiple testing, we found no impact on: ED reattendances within 7 days, patients discharged within 4 hours of arrival, patients leaving the ED without being seen; inpatient admissions; non-urgent ED attendances and 30-day mortality (reflexive monitoring). CONCLUSIONS We found a high degree of variability between hospital sites, but no overall evidence that GPED increases the efficient operation of EDs or improves clinical outcomes, patient or staff experience. TRIAL REGISTRATION NUMBER ISCRTN5178022.
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Affiliation(s)
| | - Joy Adamson
- Department of Health Sciences, University of York, York, UK
| | - Chris Salisbury
- Centre for Academic Primary Care, School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Heather Brant
- School of Health and Social Wellbeing, College of Health, Science and Society, University of the West of England, Bristol, UK
| | - Helen Anderson
- Department of Health Sciences, University of York, York, UK
| | - Helen Baxter
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Karen Bloor
- Department of Health Sciences, University of York, York, UK
| | - Sean Cowlishaw
- Centre for Academic Primary Care, School of Social and Community Medicine, University of Bristol, Bristol, UK
- Department of Psychiatry, The University of Melbourne, Melbourne, Victoria, Australia
| | - Tim Doran
- Department of Health Sciences, University of York, York, UK
| | - James Gaughan
- Department of Health Sciences, University of York, York, UK
| | - Andy Gibson
- School of Health and Social Wellbeing, College of Health, Science and Society, University of the West of England, Bristol, UK
| | - Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | | | - Sarah Purdy
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Sarah Voss
- School of Health and Social Wellbeing, College of Health, Science and Society, University of the West of England, Bristol, UK
| | - Jonathan Richard Benger
- School of Health and Social Wellbeing, College of Health, Science and Society, University of the West of England, Bristol, UK
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13
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Berthung E, Gutacker N, Abelsen B, Olsen JA. Inequality of opportunity in a land of equal opportunities: The impact of parents' health and wealth on their offspring's quality of life in Norway. BMC Public Health 2022; 22:1691. [PMID: 36068512 PMCID: PMC9450446 DOI: 10.1186/s12889-022-14084-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 08/25/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The literature on Inequality of opportunity (IOp) in health distinguishes between circumstances that lie outside of own control vs. efforts that - to varying extents - are within one's control. From the perspective of IOp, this paper aims to explain variations in individuals' health-related quality of life (HRQoL) by focusing on two separate sets of variables that clearly lie outside of own control: Parents' health is measured by their experience of somatic diseases, psychological problems and any substance abuse, while parents' wealth is indicated by childhood financial conditions (CFC). We further include own educational attainment which may represent a circumstance, or an effort, and examine associations of IOp for different health outcomes. HRQoL are measured by EQ-5D-5L utility scores, as well as the probability of reporting limitations on specific HRQoL-dimensions (mobility, self-care, usual-activities, pain & discomfort, and anxiety and depression). METHOD We use unique survey data (N = 20,150) from the egalitarian country of Norway to investigate if differences in circumstances produce unfair inequalities in health. We estimate cross-sectional regression models which include age and sex as covariates. We estimate two model specifications. The first represents a narrow IOp by estimating the contributions of parents' health and wealth on HRQoL, while the second includes own education and thus represents a broader IOp, alternatively it provides a comparison of the relative contributions of an effort variable and the two sets of circumstance variables. RESULTS We find strong associations between the circumstance variables and HRQoL. A more detailed examination showed particularly strong associations between parental psychological problems and respondents' anxiety and depression. Our Shapley decomposition analysis suggests that parents' health and wealth are each as important as own educational attainment for explaining inequalities in adult HRQoL. CONCLUSION We provide evidence for the presence of the lasting effect of early life circumstances on adult health that persists even in one of the most egalitarian countries in the world. This suggests that there may be an upper limit to how much a generous welfare state can contribute to equal opportunities.
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Affiliation(s)
- Espen Berthung
- Department of Community Medicine, Faculty of Health Sciences, UIT The Arctic University of Norway, Tromsø, Norway.
| | - Nils Gutacker
- Centre of Health Economics, University of York, York, United Kingdom
| | - Birgit Abelsen
- Department of Community Medicine, Faculty of Health Sciences, UIT The Arctic University of Norway, Tromsø, Norway
| | - Jan Abel Olsen
- Department of Community Medicine, Faculty of Health Sciences, UIT The Arctic University of Norway, Tromsø, Norway
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Schneider P, Love-Koh J, McNamara S, Doran T, Gutacker N. Socioeconomic inequalities in HRQoL in England: an age-sex stratified analysis. Health Qual Life Outcomes 2022; 20:121. [PMID: 35918765 PMCID: PMC9347153 DOI: 10.1186/s12955-022-02024-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 07/20/2022] [Indexed: 11/19/2022] Open
Abstract
Background Socioeconomic status is a key predictor of lifetime health: poorer people can expect to live shorter lives with lower average health-related quality-of-life (HRQoL) than richer people. In this study, we aimed to improve understanding of the socioeconomic gradient in HRQoL by exploring how inequalities in different dimensions of HRQoL differ by age. Methods Data were derived from the Health Survey for England for 2017 and 2018 (14,412 participants). HRQoL was measured using the EQ-5D-5L instrument. We estimated mean EQ-5D utility scores and reported problems on five HRQoL dimensions (mobility, self-care, usual activities, pain/discomfort, anxiety/depression) for ages 16 to 90+ and stratified by neighbourhood deprivation quintiles. Relative and absolute measures of inequality were assessed. Results Mean EQ-5D utility scores declined with age and followed a socioeconomic gradient, with the lowest scores in the most deprived areas. Gaps between the most and least deprived quintiles emerged around the age of 35, reached their greatest extent at age 60 to 64 (relative HRQoL of most deprived compared to least deprived quintile: females = 0.77 (95% CI: 0.68–0.85); males = 0.78 (95% CI: 0.69–0.87)) before closing again in older age groups. Gaps were apparent for all five EQ-5D dimensions but were greatest for mobility and self-care. Conclusion There are stark socioeconomic inequalities in all dimensions of HRQoL in England. These inequalities start to develop from early adulthood and increase with age but reduce again around retirement age. Supplementary Information The online version contains supplementary material available at 10.1186/s12955-022-02024-7.
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Affiliation(s)
- Paul Schneider
- School of Health and Related Research, University of Sheffield, Sheffield, UK
| | - James Love-Koh
- Centre for Health Economics, University of York, York, UK
| | - Simon McNamara
- School of Health and Related Research, University of Sheffield, Sheffield, UK.,Lumanity, Sheffield, UK
| | - Tim Doran
- Department of Health Sciences, University of York, York, UK
| | - Nils Gutacker
- Centre for Health Economics, University of York, York, UK.
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15
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Gaughan J, Liu D, Gutacker N, Bloor K, Doran T, Benger JR. Does the presence of general practitioners in emergency departments affect quality and safety in English NHS hospitals? A retrospective observational study. BMJ Open 2022; 12:e055976. [PMID: 35197350 PMCID: PMC8867306 DOI: 10.1136/bmjopen-2021-055976] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVES Emergency departments (EDs) in NHS hospitals in England have faced considerable increases in demand over recent years. Most hospitals have developed general practitioner services in emergency departments (GPEDs) to treat non-emergency patients, aiming to relieve pressure on other staff and to improve ED efficiency and patient experience. We measured the impact of GPED services on patient flows, health outcomes and ED workload. DESIGN Retrospective observational study. Differences in GPED service availability across EDs and time of day were used to identify the causal effect of GPED, as patients attending the ED at the same hour of the day are quasi-randomly assigned to treatment or control groups based on their local ED's service availability. PARTICIPANTS Attendances to 40 EDs in English NHS hospitals from April 2018 to March 2019, 4 441 349 observations. PRIMARY AND SECONDARY OUTCOMES MEASURED Outcomes measured were volume of attendances, 'non-urgent' attendances, waiting times over 4 hours, patients leaving without being treated, unplanned reattendances within 7 days, inpatient admissions and 30-day mortality. RESULTS We found a small, statistically significant reduction in unplanned reattendances within 7 days (OR 0.968, 95% CI 0.948 to 0.989), equivalent to 302 fewer reattendances per year for the average ED. The clinical impact of this was judged to be negligible. There was no detectable impact on any other outcome measure. CONCLUSIONS We found no adverse effects on patient outcomes; neither did we find any evidence of the hypothesised benefits of placing GPs in emergency settings beyond a marginal reduction in reattendances that was not considered clinically significant.
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Affiliation(s)
- James Gaughan
- Centre for Health Economics, University of York, York, UK
| | - Dan Liu
- Centre for Health Economics, University of York, York, UK
| | - Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | - Karen Bloor
- Department of Health Sciences, University of York, York, UK
| | - Tim Doran
- Department of Health Sciences, University of York, York, UK
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Berthung E, Gutacker N, Friborg O, Abelsen B, Olsen JA. Who keeps on working? The importance of resilience for labour market participation. PLoS One 2021; 16:e0258444. [PMID: 34644341 PMCID: PMC8513899 DOI: 10.1371/journal.pone.0258444] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 09/27/2021] [Indexed: 11/24/2022] Open
Abstract
Background It is widely recognized that individuals’ health and educational attainments, commonly referred to as their human capital, are important determinants for their labour market participation (LMP). What is less recognised is the influence of individuals’ latent resilience traits on their ability to sustain LMP after experiencing an adversity such as a health shock. Aim We investigate the extent to which resilience is independently associated with LMP and moderates the effect of health shocks on LMP. Method We analysed data from two consecutive waves of a Norwegian prospective cohort study. We followed 3,840 adults who, at baseline, were healthy and worked full time. Binary logistic regression models were applied to explain their employment status eight years later, controlling for age, sex, educational attainment, health status at baseline, as well as the occurrences of three types of health shocks (cardiovascular diseases, cancer, psychological problems). Individuals’ resilience, measured by the Resilience Scale for Adults (RSA), entered as an independent variable and as an interaction with the indicators of health shocks. In separate models, we explore the role of two further indicators of resilience; locus of control, and health optimism. Results As expected, health shocks reduce the probability to keep on working full-time. While both the RSA and the two related indicators all suggest that resilience increases the probability to keep on working, we did not find evidence that resilience moderates the association between health shocks and LMP. Conclusion Higher levels of resilience is associated with full-time work as individuals age.
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Affiliation(s)
- Espen Berthung
- Department of Community Medicine, Faculty of Health Sciences, UIT The Arctic University of Norway, Tromsø, Norway
- * E-mail:
| | - Nils Gutacker
- Centre of Health Economics, University of York, York, United Kingdom
| | - Oddgeir Friborg
- Department of Psychology, Faculty of Health Sciences, UIT The Arctic University of Norway, Tromsø, Norway
| | - Birgit Abelsen
- Department of Community Medicine, Faculty of Health Sciences, UIT The Arctic University of Norway, Tromsø, Norway
| | - Jan Abel Olsen
- Department of Community Medicine, Faculty of Health Sciences, UIT The Arctic University of Norway, Tromsø, Norway
- Division of Health Services, Norwegian Institute of Public Health, Oslo, Norway
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17
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Walker S, Fox A, Altunkaya J, Colbourn T, Drummond M, Griffin S, Gutacker N, Revill P, Sculpher M. Program Evaluation of Population- and System-Level Policies: Evidence for Decision Making. Med Decis Making 2021; 42:17-27. [PMID: 34041992 DOI: 10.1177/0272989x211016427] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Policy evaluations often focus on ex post estimation of causal effects on short-term surrogate outcomes. The value of such information is limited for decision making, as the failure to reflect policy-relevant outcomes and disregard for opportunity costs prohibits the assessment of value for money. Further, these evaluations do not always consider all relevant evidence, other courses of action, or decision uncertainty. METHODS In this article, we explore how policy evaluation could better meet the needs of decision making. We begin by defining the evidence required to inform decision making. We then conduct a literature review of challenges in evaluating policies. Finally, we highlight potential methods available to help address these challenges. RESULTS The evidence required to inform decision making includes the impacts on the policy-relevant outcomes, the costs and associated opportunity costs, and the consequences of uncertainty. Challenges in evaluating health policies are described using 8 categories: 1) valuation space; 2) comparators; 3) time of evaluation; 4) mechanisms of action; 5) effects; 6) resources, constraints, and opportunity costs; 7) fidelity, adaptation, and level of implementation; and 8) generalizability and external validity. Methods from a broad set of disciplines are available to improve policy evaluation, relating to causal inference, decision-analytic modeling, theory of change, realist evaluation, and structured expert elicitation. LIMITATIONS The targeted review may not identify all possible challenges, and the methods covered are not exhaustive. CONCLUSIONS Evaluations should provide appropriate evidence to inform decision making. There are challenges in evaluating policies, but methods from multiple disciplines are available to address these challenges. IMPLICATIONS Evaluators need to carefully consider the decision being informed, the necessary evidence to inform it, and the appropriate methods.[Box: see text].
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Affiliation(s)
- Simon Walker
- Centre for Health Economics, University of York, York, UK
| | - Aimee Fox
- Adelphi Values, Bollington, Cheshire, UK
| | - James Altunkaya
- Nuffield Department of Population Health, University of Oxford, Oxford, Oxfordshire, UK
| | - Tim Colbourn
- Institute for Global Health, University College London, London, UK
| | - Mike Drummond
- Centre for Health Economics, University of York, York, UK
| | - Susan Griffin
- Centre for Health Economics, University of York, York, UK
| | - Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | - Paul Revill
- Centre for Health Economics, University of York, York, UK
| | - Mark Sculpher
- Centre for Health Economics, University of York, York, UK
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18
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Gutacker N, Patton T, Shah K, Parkin D. Using EQ-5D Data to Measure Hospital Performance: Are General Population Values Distorting Patients' Choices? Med Decis Making 2020; 40:511-521. [PMID: 32486958 DOI: 10.1177/0272989x20927705] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background. The English National Health Service publishes hospital performance indicators based on average postoperative EQ-5D index scores after hip replacement surgery to inform prospective patients' choices of hospital. Unidimensional index scores are derived from multidimensional health-related quality-of-life data using preference weights estimated from a sample of the UK general population. This raises normative concerns if general population preferences differ from those of the patients who are to be informed. This study explores how the source of valuation affects hospital performance estimates. Methods. Four different value sets reflecting source of valuation (general population v. patients), valuation technique (visual analog scale [VAS] v. time tradeoff [TTO]), and experience with health states (currently experienced vs. experimentally estimated) were used to derive and compare performance estimates for 243 hospitals. Two value sets were newly estimated from EQ-5D-3L data on 122,921 hip replacement patients and 3381 members of the UK general public. Changes in hospital ranking (nationally) and performance outlier status (nationally; among patients' 5 closest hospitals) were compared across valuations. Results. National rankings were stable under different valuations (rank correlations >0.92). Twenty-three (9.5%) hospitals changed outlier status when using patient VAS valuations instead of general population TTO valuations, the current approach. Outlier status also changed substantially at the local level. This was explained mostly by the valuation technique, not the source of valuations or experience with the health states. Limitations. No patient TTO valuations were available. The effect of value set characteristics could be established only through indirect comparisons. Conclusion. Different value sets may lead to prospective patients choosing different hospitals. Normative concerns about the use of general population valuations are not supported by empirical evidence based on VAS valuations.
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Affiliation(s)
- Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | - Thomas Patton
- Centre for Health Economics, University of York, York, UK
| | | | - David Parkin
- Office of Health Economics, London, UK, and Department of Economics, City University of London, London, UK
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Jacobs R, Aylott L, Dare C, Doran T, Gilbody S, Goddard M, Gravelle H, Gutacker N, Kasteridis P, Kendrick T, Mason A, Rice N, Ride J, Siddiqi N, Williams R. The association between primary care quality and health-care use, costs and outcomes for people with serious mental illness: a retrospective observational study. Health Serv Deliv Res 2020. [DOI: 10.3310/hsdr08250] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Background
Serious mental illness, including schizophrenia, bipolar disorder and other psychoses, is linked with high disease burden, poor outcomes, high treatment costs and lower life expectancy. In the UK, most people with serious mental illness are treated in primary care by general practitioners, who are financially incentivised to meet quality targets for patients with chronic conditions, including serious mental illness, under the Quality and Outcomes Framework. The Quality and Outcomes Framework, however, omits important aspects of quality.
Objectives
We examined whether or not better quality of primary care for people with serious mental illness improved a range of outcomes.
Design and setting
We used administrative data from English primary care practices that contribute to the Clinical Practice Research Datalink GOLD database, linked to Hospital Episode Statistics, accident and emergency attendances, Office for National Statistics mortality data and community mental health records in the Mental Health Minimum Data Set. We used survival analysis to estimate whether or not selected quality indicators affect the time until patients experience an outcome.
Participants
Four cohorts of people with serious mental illness, depending on the outcomes examined and inclusion criteria.
Interventions
Quality of care was measured with (1) Quality and Outcomes Framework indicators (care plans and annual physical reviews) and (2) non-Quality and Outcomes Framework indicators identified through a systematic review (antipsychotic polypharmacy and continuity of care provided by general practitioners).
Main outcome measures
Several outcomes were examined: emergency admissions for serious mental illness and ambulatory care sensitive conditions; all unplanned admissions; accident and emergency attendances; mortality; re-entry into specialist mental health services; and costs attributed to primary, secondary and community mental health care.
Results
Care plans were associated with lower risk of accident and emergency attendance (hazard ratio 0.74, 95% confidence interval 0.69 to 0.80), serious mental illness admission (hazard ratio 0.67, 95% confidence interval 0.59 to 0.75), ambulatory care sensitive condition admission (hazard ratio 0.73, 95% confidence interval 0.64 to 0.83), and lower overall health-care (£53), primary care (£9), hospital (£26) and mental health-care costs (£12). Annual reviews were associated with reduced risk of accident and emergency attendance (hazard ratio 0.80, 95% confidence interval 0.76 to 0.85), serious mental illness admission (hazard ratio 0.75, 95% confidence interval 0.67 to 0.84), ambulatory care sensitive condition admission (hazard ratio 0.76, 95% confidence interval 0.67 to 0.87), and lower overall health-care (£34), primary care (£9) and mental health-care costs (£30). Higher general practitioner continuity was associated with lower risk of accident and emergency presentation (hazard ratio 0.89, 95% confidence interval 0.83 to 0.97) and ambulatory care sensitive condition admission (hazard ratio 0.77, 95% confidence interval 0.65 to 0.92), but not with serious mental illness admission. High continuity was associated with lower primary care costs (£3). Antipsychotic polypharmacy was not statistically significantly associated with the risk of unplanned admission, death or accident and emergency presentation. None of the quality measures was statistically significantly associated with risk of re-entry into specialist mental health care.
Limitations
There is risk of bias from unobserved factors. To mitigate this, we controlled for observed patient characteristics at baseline and adjusted for the influence of time-invariant unobserved patient differences.
Conclusions
Better performance on Quality and Outcomes Framework measures and continuity of care are associated with better outcomes and lower resource utilisation, and could generate moderate cost savings.
Future work
Future research should examine the impact of primary care quality on measures that capture broader aspects of health and functioning.
Funding
This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 8, No. 25. See the NIHR Journals Library website for further project information.
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Affiliation(s)
- Rowena Jacobs
- Centre for Health Economics, University of York, York, UK
| | - Lauren Aylott
- Expert by experience
- Hull York Medical School, York, UK
| | | | | | - Simon Gilbody
- Hull York Medical School, York, UK
- Department of Health Sciences, University of York, York, UK
| | - Maria Goddard
- Centre for Health Economics, University of York, York, UK
| | - Hugh Gravelle
- Centre for Health Economics, University of York, York, UK
| | - Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | | | - Tony Kendrick
- Primary Care and Population Sciences, Aldermoor Health Centre, University of Southampton, Southampton, UK
| | - Anne Mason
- Centre for Health Economics, University of York, York, UK
| | - Nigel Rice
- Centre for Health Economics, University of York, York, UK
| | - Jemimah Ride
- Centre for Health Economics, University of York, York, UK
| | - Najma Siddiqi
- Hull York Medical School, York, UK
- Department of Health Sciences, University of York, York, UK
- Bradford District Care NHS Foundation Trust, Bradford, UK
| | - Rachael Williams
- Clinical Practice Research Datalink, Medicines and Healthcare products Regulatory Agency, London, UK
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Ride J, Kasteridis P, Gutacker N, Aragon Aragon MJ, Jacobs R. Healthcare Costs for People with Serious Mental Illness in England: An Analysis of Costs Across Primary Care, Hospital Care, and Specialist Mental Healthcare. Appl Health Econ Health Policy 2020; 18:177-188. [PMID: 31701484 PMCID: PMC7085478 DOI: 10.1007/s40258-019-00530-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
BACKGROUND Serious mental illness (SMI) is a set of disabling conditions associated with poor outcomes and high healthcare utilisation. However, little is known about patterns of utilisation and costs across sectors for people with SMI. OBJECTIVE The aim was to develop a costing methodology and estimate annual healthcare costs for people with SMI in England across primary and secondary care settings. METHODS A retrospective observational cohort study was conducted using linked administrative records from primary care, emergency departments, inpatient admissions, and community mental health services, covering financial years 2011/12-2013/14. Costs were calculated using bottom-up costing and are expressed in 2013/14 British pounds (GBP). Determinants of annual costs by sector were estimated using generalised linear models. RESULTS Mean annual total healthcare costs for 13,846 adults with SMI were £4989 (median £1208), comprising 19% from primary care (£938, median £531), 34% from general hospital care (£1717, median £0), and 47% from inpatient and community-based specialist mental health services (£2334, median £0). Mean annual costs related specifically to mental health, as distinct from physical health, were £2576 (median £290). Key predictors of total cost included physical comorbidities, ethnicity, neighbourhood deprivation, SMI diagnostic subgroup, and age. Some associations varied across care context; for example, older age was associated with higher primary care and hospital costs, but lower mental healthcare costs. CONCLUSIONS Annual healthcare costs for people with SMI vary significantly across clinical and socioeconomic characteristics and healthcare sectors. This analysis informs policy and research, including estimation of health budgets for particular patient profiles, and economic evaluation of health services and policies.
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Affiliation(s)
- Jemimah Ride
- Health Economics Unit, Melbourne School of Population and Global Health, University of Melbourne, Level 4, 207 Bouverie Street, Parkville, VIC 3010 Australia
| | | | - Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | | | - Rowena Jacobs
- Centre for Health Economics, University of York, York, UK
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21
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Gaughan J, Gutacker N, Grašič K, Kreif N, Siciliani L, Street A. Paying for efficiency: Incentivising same-day discharges in the English NHS. J Health Econ 2019; 68:102226. [PMID: 31521026 DOI: 10.1016/j.jhealeco.2019.102226] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Revised: 07/04/2019] [Accepted: 08/13/2019] [Indexed: 05/27/2023]
Abstract
We study a pay-for-efficiency scheme that encourages hospitals to admit and discharge patients on the same calendar day when clinically appropriate. Since 2010, hospitals in the English NHS are incentivised by a higher price for patients treated as same-day discharge than for overnight stays, despite the former being less costly. We analyse administrative data for patients treated during 2006-2014 for 191 conditions for which same-day discharge is clinically appropriate - of which 32 are incentivised. Using difference-in-difference and synthetic control methods, we find that the policy had generally a positive impact with a statistically significant effect in 14 out of the 32 conditions. The median elasticity is 0.24 for planned and 0.01 for emergency conditions. Condition-specific design features explain some, but not all, of the differential responses.
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Affiliation(s)
- James Gaughan
- Centre for Health Economics, University of York, United Kingdom.
| | - Nils Gutacker
- Centre for Health Economics, University of York, United Kingdom
| | - Katja Grašič
- Centre for Health Economics, University of York, United Kingdom
| | - Noemi Kreif
- Centre for Health Economics, University of York, United Kingdom
| | - Luigi Siciliani
- Department of Economics and Related Studies, University of York, United Kingdom
| | - Andrew Street
- Department of Health Policy, The London School of Economics and Political Science, United Kingdom
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Ride J, Kasteridis P, Gutacker N, Doran T, Rice N, Gravelle H, Kendrick T, Mason A, Goddard M, Siddiqi N, Gilbody S, Williams R, Aylott L, Dare C, Jacobs R. Impact of family practice continuity of care on unplanned hospital use for people with serious mental illness. Health Serv Res 2019; 54:1316-1325. [PMID: 31598965 PMCID: PMC6863233 DOI: 10.1111/1475-6773.13211] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Objective To investigate whether continuity of care in family practice reduces unplanned hospital use for people with serious mental illness (SMI). Data Sources Linked administrative data on family practice and hospital utilization by people with SMI in England, 2007‐2014. Study Design This observational cohort study used discrete‐time survival analysis to investigate the relationship between continuity of care in family practice and unplanned hospital use: emergency department (ED) presentations, and unplanned admissions for SMI and ambulatory care‐sensitive conditions (ACSC). The analysis distinguishes between relational continuity and management/ informational continuity (as captured by care plans) and accounts for unobserved confounding by examining deviation from long‐term averages. Data Collection/Extraction Methods Individual‐level family practice administrative data linked to hospital administrative data. Principal Findings Higher relational continuity was associated with 8‐11 percent lower risk of ED presentation and 23‐27 percent lower risk of ACSC admissions. Care plans were associated with 29 percent lower risk of ED presentation, 39 percent lower risk of SMI admissions, and 32 percent lower risk of ACSC admissions. Conclusions Family practice continuity of care can reduce unplanned hospital use for physical and mental health of people with SMI.
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Affiliation(s)
- Jemimah Ride
- Health Economics Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Vic., Australia
| | | | - Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | - Tim Doran
- Department of Health Sciences, University of York, York, UK
| | - Nigel Rice
- Centre for Health Economics, University of York, York, UK
| | - Hugh Gravelle
- Centre for Health Economics, University of York, York, UK
| | - Tony Kendrick
- Department of Primary Care, University of Southampton, Southampton, UK
| | - Anne Mason
- Centre for Health Economics, University of York, York, UK
| | - Maria Goddard
- Centre for Health Economics, University of York, York, UK
| | - Najma Siddiqi
- Department of Health Sciences, University of York, York, UK.,Hull York Medical School, York, UK.,Bradford District Care, NHS Foundation Trust, Bradford, UK
| | - Simon Gilbody
- Mental Health and Addiction Research Group, Department of Health Sciences, University of York, York, UK
| | | | - Lauren Aylott
- Health Professions Education Unit, Hull York Medical School, York, UK
| | - Ceri Dare
- Service User, York, North Yorkshire, UK
| | - Rowena Jacobs
- Centre for Health Economics, University of York, York, UK
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Kasteridis P, Ride J, Gutacker N, Aylott L, Dare C, Doran T, Gilbody S, Goddard M, Gravelle H, Kendrick T, Mason A, Rice N, Siddiqi N, Williams R, Jacobs R. Association Between Antipsychotic Polypharmacy and Outcomes for People With Serious Mental Illness in England. Psychiatr Serv 2019; 70:650-656. [PMID: 31109263 PMCID: PMC6890489 DOI: 10.1176/appi.ps.201800504] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Although U.K. and international guidelines recommend monotherapy, antipsychotic polypharmacy among patients with serious mental illness is common in clinical practice. However, empirical evidence on its effectiveness is scarce. Therefore, the authors estimated the effectiveness of antipsychotic polypharmacy relative to monotherapy in terms of health care utilization and mortality. METHODS Primary care data from Clinical Practice Research Datalink, hospital data from Hospital Episode Statistics, and mortality data from the Office of National Statistics were linked to compile a cohort of patients with serious mental illness in England from 2000 to 2014. The antipsychotic prescribing profile of 17,255 adults who had at least one antipsychotic drug record during the period of observation was constructed from primary care medication records. Survival analysis models were estimated to identify the effect of antipsychotic polypharmacy on the time to first occurrence of each of three outcomes: unplanned hospital admissions (all cause), emergency department (ED) visits, and mortality. RESULTS Relative to monotherapy, antipsychotic polypharmacy was not associated with increased risk of unplanned hospital admission (hazard ratio [HR]=1.14; 95% confidence interval [CI]=0.98-1.32), ED visit (HR=0.95; 95% CI=0.80-1.14), or death (HR=1.02; 95% CI=0.76-1.37). Relative to not receiving antipsychotic medication, monotherapy was associated with a reduced hazard of unplanned admissions to the hospital and ED visits, but it had no effect on mortality. CONCLUSIONS The study results support current guidelines for antipsychotic monotherapy in routine clinical practice. However, they also suggest that when clinicians have deemed antipsychotic polypharmacy necessary, health care utilization and mortality are not affected.
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Affiliation(s)
- Panagiotis Kasteridis
- Centre for Health Economics (Kasteridis, Ride, Gutacker, Goddard, Gravelle, Mason, Rice, Jacobs) and Department of Health Sciences (Doran, Gilbody, Siddiqi), University of York, York, England; Hull York Medical School, York, England (Aylott, Gilbody, Siddiqi); Primary Care and Population Sciences, University of Southampton, Southampton, England (Kendrick); Clinical Practice Research Datalink-Medicines and Healthcare Products Regulatory Agency, London (Williams). Mental health services consultant, York, United Kingdom (Dare)
| | - Jemimah Ride
- Centre for Health Economics (Kasteridis, Ride, Gutacker, Goddard, Gravelle, Mason, Rice, Jacobs) and Department of Health Sciences (Doran, Gilbody, Siddiqi), University of York, York, England; Hull York Medical School, York, England (Aylott, Gilbody, Siddiqi); Primary Care and Population Sciences, University of Southampton, Southampton, England (Kendrick); Clinical Practice Research Datalink-Medicines and Healthcare Products Regulatory Agency, London (Williams). Mental health services consultant, York, United Kingdom (Dare)
| | - Nils Gutacker
- Centre for Health Economics (Kasteridis, Ride, Gutacker, Goddard, Gravelle, Mason, Rice, Jacobs) and Department of Health Sciences (Doran, Gilbody, Siddiqi), University of York, York, England; Hull York Medical School, York, England (Aylott, Gilbody, Siddiqi); Primary Care and Population Sciences, University of Southampton, Southampton, England (Kendrick); Clinical Practice Research Datalink-Medicines and Healthcare Products Regulatory Agency, London (Williams). Mental health services consultant, York, United Kingdom (Dare)
| | - Lauren Aylott
- Centre for Health Economics (Kasteridis, Ride, Gutacker, Goddard, Gravelle, Mason, Rice, Jacobs) and Department of Health Sciences (Doran, Gilbody, Siddiqi), University of York, York, England; Hull York Medical School, York, England (Aylott, Gilbody, Siddiqi); Primary Care and Population Sciences, University of Southampton, Southampton, England (Kendrick); Clinical Practice Research Datalink-Medicines and Healthcare Products Regulatory Agency, London (Williams). Mental health services consultant, York, United Kingdom (Dare)
| | - Ceri Dare
- Centre for Health Economics (Kasteridis, Ride, Gutacker, Goddard, Gravelle, Mason, Rice, Jacobs) and Department of Health Sciences (Doran, Gilbody, Siddiqi), University of York, York, England; Hull York Medical School, York, England (Aylott, Gilbody, Siddiqi); Primary Care and Population Sciences, University of Southampton, Southampton, England (Kendrick); Clinical Practice Research Datalink-Medicines and Healthcare Products Regulatory Agency, London (Williams). Mental health services consultant, York, United Kingdom (Dare)
| | - Tim Doran
- Centre for Health Economics (Kasteridis, Ride, Gutacker, Goddard, Gravelle, Mason, Rice, Jacobs) and Department of Health Sciences (Doran, Gilbody, Siddiqi), University of York, York, England; Hull York Medical School, York, England (Aylott, Gilbody, Siddiqi); Primary Care and Population Sciences, University of Southampton, Southampton, England (Kendrick); Clinical Practice Research Datalink-Medicines and Healthcare Products Regulatory Agency, London (Williams). Mental health services consultant, York, United Kingdom (Dare)
| | - Simon Gilbody
- Centre for Health Economics (Kasteridis, Ride, Gutacker, Goddard, Gravelle, Mason, Rice, Jacobs) and Department of Health Sciences (Doran, Gilbody, Siddiqi), University of York, York, England; Hull York Medical School, York, England (Aylott, Gilbody, Siddiqi); Primary Care and Population Sciences, University of Southampton, Southampton, England (Kendrick); Clinical Practice Research Datalink-Medicines and Healthcare Products Regulatory Agency, London (Williams). Mental health services consultant, York, United Kingdom (Dare)
| | - Maria Goddard
- Centre for Health Economics (Kasteridis, Ride, Gutacker, Goddard, Gravelle, Mason, Rice, Jacobs) and Department of Health Sciences (Doran, Gilbody, Siddiqi), University of York, York, England; Hull York Medical School, York, England (Aylott, Gilbody, Siddiqi); Primary Care and Population Sciences, University of Southampton, Southampton, England (Kendrick); Clinical Practice Research Datalink-Medicines and Healthcare Products Regulatory Agency, London (Williams). Mental health services consultant, York, United Kingdom (Dare)
| | - Hugh Gravelle
- Centre for Health Economics (Kasteridis, Ride, Gutacker, Goddard, Gravelle, Mason, Rice, Jacobs) and Department of Health Sciences (Doran, Gilbody, Siddiqi), University of York, York, England; Hull York Medical School, York, England (Aylott, Gilbody, Siddiqi); Primary Care and Population Sciences, University of Southampton, Southampton, England (Kendrick); Clinical Practice Research Datalink-Medicines and Healthcare Products Regulatory Agency, London (Williams). Mental health services consultant, York, United Kingdom (Dare)
| | - Tony Kendrick
- Centre for Health Economics (Kasteridis, Ride, Gutacker, Goddard, Gravelle, Mason, Rice, Jacobs) and Department of Health Sciences (Doran, Gilbody, Siddiqi), University of York, York, England; Hull York Medical School, York, England (Aylott, Gilbody, Siddiqi); Primary Care and Population Sciences, University of Southampton, Southampton, England (Kendrick); Clinical Practice Research Datalink-Medicines and Healthcare Products Regulatory Agency, London (Williams). Mental health services consultant, York, United Kingdom (Dare)
| | - Anne Mason
- Centre for Health Economics (Kasteridis, Ride, Gutacker, Goddard, Gravelle, Mason, Rice, Jacobs) and Department of Health Sciences (Doran, Gilbody, Siddiqi), University of York, York, England; Hull York Medical School, York, England (Aylott, Gilbody, Siddiqi); Primary Care and Population Sciences, University of Southampton, Southampton, England (Kendrick); Clinical Practice Research Datalink-Medicines and Healthcare Products Regulatory Agency, London (Williams). Mental health services consultant, York, United Kingdom (Dare)
| | - Nigel Rice
- Centre for Health Economics (Kasteridis, Ride, Gutacker, Goddard, Gravelle, Mason, Rice, Jacobs) and Department of Health Sciences (Doran, Gilbody, Siddiqi), University of York, York, England; Hull York Medical School, York, England (Aylott, Gilbody, Siddiqi); Primary Care and Population Sciences, University of Southampton, Southampton, England (Kendrick); Clinical Practice Research Datalink-Medicines and Healthcare Products Regulatory Agency, London (Williams). Mental health services consultant, York, United Kingdom (Dare)
| | - Najma Siddiqi
- Centre for Health Economics (Kasteridis, Ride, Gutacker, Goddard, Gravelle, Mason, Rice, Jacobs) and Department of Health Sciences (Doran, Gilbody, Siddiqi), University of York, York, England; Hull York Medical School, York, England (Aylott, Gilbody, Siddiqi); Primary Care and Population Sciences, University of Southampton, Southampton, England (Kendrick); Clinical Practice Research Datalink-Medicines and Healthcare Products Regulatory Agency, London (Williams). Mental health services consultant, York, United Kingdom (Dare)
| | - Rachael Williams
- Centre for Health Economics (Kasteridis, Ride, Gutacker, Goddard, Gravelle, Mason, Rice, Jacobs) and Department of Health Sciences (Doran, Gilbody, Siddiqi), University of York, York, England; Hull York Medical School, York, England (Aylott, Gilbody, Siddiqi); Primary Care and Population Sciences, University of Southampton, Southampton, England (Kendrick); Clinical Practice Research Datalink-Medicines and Healthcare Products Regulatory Agency, London (Williams). Mental health services consultant, York, United Kingdom (Dare)
| | - Rowena Jacobs
- Centre for Health Economics (Kasteridis, Ride, Gutacker, Goddard, Gravelle, Mason, Rice, Jacobs) and Department of Health Sciences (Doran, Gilbody, Siddiqi), University of York, York, England; Hull York Medical School, York, England (Aylott, Gilbody, Siddiqi); Primary Care and Population Sciences, University of Southampton, Southampton, England (Kendrick); Clinical Practice Research Datalink-Medicines and Healthcare Products Regulatory Agency, London (Williams). Mental health services consultant, York, United Kingdom (Dare)
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Love-Koh J, Cookson R, Gutacker N, Patton T, Griffin S. Aggregate Distributional Cost-Effectiveness Analysis of Health Technologies. Value Health 2019; 22:518-526. [PMID: 31104729 DOI: 10.1016/j.jval.2019.03.006] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Revised: 03/15/2019] [Accepted: 03/18/2019] [Indexed: 05/10/2023]
Abstract
BACKGROUND Health inequalities can be partially addressed through the range of treatments funded by health systems. Nevertheless, although health technology assessment agencies assess the overall balance of health benefits and costs, no quantitative assessment of health inequality impact is consistently undertaken. OBJECTIVES To assess the inequality impact of technologies recommended under the NICE single technology appraisal process from 2012 to 2014 using an aggregate distributional cost-effectiveness framework. METHODS Data on health benefits, costs, and patient populations were extracted from the NICE website. Benefits for each technology were distributed to social groups using the observed socioeconomic distribution of hospital utilization for the targeted disease. Inequality measures and estimates of cost-effectiveness were compared using the health inequality impact plane and combined using social welfare indices. RESULTS Twenty-seven interventions were evaluated. Fourteen interventions were estimated to increase population health and reduce health inequality, 8 to reduce population health and increase health inequality, and 5 to increase health and increase health inequality. Among the latter 5, social welfare analysis, using inequality aversion parameters reflecting high concern for inequality, indicated that the health gain outweighs the negative health inequality impact. CONCLUSIONS The methods proposed offer a way of estimating the health inequality impacts of new health technologies. The methods do not allow for differences in technology-specific utilization and health benefits, but require less resources and data than conducting full distributional cost-effectiveness analysis. They can provide useful quantitative information to help policy makers consider how far new technologies are likely to reduce or increase health inequalities.
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Affiliation(s)
- James Love-Koh
- Centre for Health Economics, University of York, York, England, UK.
| | - Richard Cookson
- Centre for Health Economics, University of York, York, England, UK
| | - Nils Gutacker
- Centre for Health Economics, University of York, York, England, UK
| | - Thomas Patton
- Centre for Health Economics, University of York, York, England, UK
| | - Susan Griffin
- Centre for Health Economics, University of York, York, England, UK
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Moscelli G, Jacobs R, Gutacker N, Aragón MJ, Chalkley M, Mason A, Böhnke J. Prospective payment systems and discretionary coding-Evidence from English mental health providers. Health Econ 2019; 28:387-402. [PMID: 30592102 PMCID: PMC6491985 DOI: 10.1002/hec.3851] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2017] [Revised: 06/15/2018] [Accepted: 11/19/2018] [Indexed: 06/09/2023]
Abstract
Reimbursement of English mental health hospitals is moving away from block contracts and towards activity and outcome-based payments. Under the new model, patients are categorised into 20 groups with similar levels of need, called clusters, to which prices may be assigned prospectively. Clinicians, who make clustering decisions, have substantial discretion and can, in principle, directly influence the level of reimbursement the hospital receives. This may create incentives for upcoding. Clinicians are supported in their allocation decision by a clinical clustering algorithm, the Mental Health Clustering Tool, which provides an external reference against which clustering behaviour can be benchmarked. The aims of this study are to investigate the degree of mismatch between predicted and actual clustering and to test whether there are systematic differences amongst providers in their clustering behaviour. We use administrative data for all mental health patients in England who were clustered for the first time during the financial year 2014/15 and estimate multinomial multilevel models of over, under, or matching clustering. Results suggest that hospitals vary systematically in their probability of mismatch but this variation is not consistently associated with observed hospital characteristics.
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Affiliation(s)
| | | | | | | | | | - Anne Mason
- Centre for Health EconomicsUniversity of YorkYorkUK
| | - Jan Böhnke
- Department of Health SciencesUniversity of YorkYorkUK
- Dundee Centre for Health and Related Research, School of Nursing and Health SciencesUniversity of DundeeDundeeUK
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26
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Gutacker N, Bloor K, Bojke C, Archer J, Walshe K. Does regulation increase the rate at which doctors leave practice? Analysis of routine hospital data in the English NHS following the introduction of medical revalidation. BMC Med 2019; 17:33. [PMID: 30744639 PMCID: PMC6371486 DOI: 10.1186/s12916-019-1270-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Accepted: 01/22/2019] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND In 2012, the UK introduced medical revalidation, whereby to retain their licence all doctors are required to show periodically that they are up to date and fit to practise medicine. Early reports suggested that some doctors found the process overly onerous and chose to leave practice. This study investigates the effect of medical revalidation on the rate at which consultants (senior hospital doctors) leave NHS practice, and assesses any differences between the performance of consultants who left or remained in practice before and after the introduction of revalidation. METHODS We used a retrospective cohort of administrative data from the Hospital Episode Statistics database on all consultants who were working in English NHS hospitals between April 2008 and March 2009 (n = 19,334), followed to March 2015. Proportional hazard models were used to identify the effect of medical revalidation on the time to exit from the NHS workforce, as implied by ceasing NHS clinical activity. The main exposure variable was consultants' time-varying revalidation status, which differentiates between periods when consultants were (a) not subject to revalidation-before the policy was introduced, (b) awaiting a revalidation recommendation and (c) had received a positive recommendation to be revalidated. Difference-in-differences analysis was used to compare the performance of those who left practice with those who remained in practice before and after the introduction of revalidation, as proxied by case-mix-adjusted 30-day mortality rates. RESULTS After 2012, consultants who had not yet revalidated were at an increased hazard of ceasing NHS clinical practice (HR 2.33, 95% CI 2.12 to 2.57) compared with pre-policy levels. This higher risk remained after a positive recommendation (HR 1.85, 95% CI 1.65 to 2.06) but was statistically significantly reduced (p < 0.001). We found no statistically significant differences in mortality rates between those consultants who ceased practice and those who remained, after adjustment for multiple testing. CONCLUSION Revalidation appears to have led to greater numbers of doctors ceasing clinical practice, over and above other contemporaneous influences. Those ceasing clinical practice do not appear to have provided lower quality care, as approximated by mortality rates, when compared with those remaining in practice.
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Affiliation(s)
- Nils Gutacker
- Centre for Health Economics, University of York, York, UK.
| | - Karen Bloor
- Department of Health Sciences, University of York, York, UK
| | - Chris Bojke
- Leeds Institute of Health Sciences, Faculty of Medicine and Health, University of Leeds, Leeds, UK
| | - Julian Archer
- Collaboration for the Advancement of Medical Education Research Assessment, University of Plymouth, Plymouth, UK
| | - Kieran Walshe
- Alliance Manchester Business School, University of Manchester, Manchester, UK
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Ride J, Kasteridis P, Gutacker N, Kronenberg C, Doran T, Mason A, Rice N, Gravelle H, Goddard M, Kendrick T, Siddiqi N, Gilbody S, Dare CRJ, Aylott L, Williams R, Jacobs R. Do care plans and annual reviews of physical health influence unplanned hospital utilisation for people with serious mental illness? Analysis of linked longitudinal primary and secondary healthcare records in England. BMJ Open 2018; 8:e023135. [PMID: 30498040 PMCID: PMC6278786 DOI: 10.1136/bmjopen-2018-023135] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
OBJECTIVE To investigate whether two primary care activities that are framed as indicators of primary care quality (comprehensive care plans and annual reviews of physical health) influence unplanned utilisation of hospital services for people with serious mental illness (SMI). DESIGN, SETTING, PARTICIPANTS Retrospective observational cohort study using linked primary care and hospital records (Hospital Episode Statistics) for 5158 patients diagnosed with SMI between April 2006 and March 2014, who attended 213 primary care practices in England that contribute to the Clinical Practice Research Datalink GOLD database. OUTCOMES AND ANALYSIS Cox survival models were used to estimate the associations between two primary care quality indicators (care plans and annual reviews of physical health) and the hazards of three types of unplanned hospital utilisation: presentation to accident and emergency departments (A&E), admission for SMI and admission for ambulatory care sensitive conditions (ACSC). RESULTS Risk of A&E presentation was 13% lower (HR 0.87, 95% CI 0.77 to 0.98) and risk of admission to hospital for ACSC was 23% lower (HR 0.77, 95% CI 0.60 to 0.99) for patients with a care plan documented in the previous year compared with those without a care plan. Risk of A&E presentation was 19% lower for those who had a care plan documented earlier but not updated in the previous year (HR: 0.81, 95% CI 0.67 to 0.97) compared with those without a care plan. Risks of hospital admission for SMI were not associated with care plans, and none of the outcomes were associated with annual reviews. CONCLUSIONS Care plans documented in primary care for people with SMI are associated with reduced risk of A&E attendance and reduced risk of unplanned admission to hospital for physical health problems, but not with risk of admission for mental health problems. Annual reviews of physical health are not associated with risk of unplanned hospital utilisation.
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Affiliation(s)
- Jemimah Ride
- Centre for Health Economics, University of York, York, UK
| | | | - Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | - Christoph Kronenberg
- CINCH, University Duisburg-Essen, Essen, Germany
- Leibniz Science Campus Ruhr, Essen, Germany
- RWI – Leibniz-Institute for Economic Research, Essen, Germany
| | - Tim Doran
- Department of Health Sciences, The University of York, York, UK
| | - Anne Mason
- Centre for Health Economics, University of York, York, UK
| | - Nigel Rice
- Centre for Health Economics, University of York, York, UK
| | - Hugh Gravelle
- Centre for Health Economics, University of York, York, UK
| | - Maria Goddard
- Centre for Health Economics, University of York, York, UK
| | - Tony Kendrick
- Primary Care and Population Sciences, University of Southampton, Southampton, UK
| | - Najma Siddiqi
- Department of Health Sciences, The University of York, York, UK
| | - Simon Gilbody
- Department of Health Sciences, The University of York, York, UK
| | | | | | | | - Rowena Jacobs
- Centre for Health Economics, University of York, York, UK
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Affiliation(s)
- Nils Gutacker
- 1 Senior Research Fellow, Centre for Health Economics, University of York, UK
| | - Andrew Street
- 2 Professor in Health Economics, Department of Health Policy, London School of Economics and Political Science, UK
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Morton K, Voss S, Adamson J, Baxter H, Bloor K, Brandling J, Cowlishaw S, Doran T, Gibson A, Gutacker N, Liu D, Purdy S, Roy P, Salisbury C, Scantlebury A, Vaittinen A, Watson R, Benger JR. General practitioners and emergency departments (GPED)-efficient models of care: a mixed-methods study protocol. BMJ Open 2018; 8:e024012. [PMID: 30287675 PMCID: PMC6194458 DOI: 10.1136/bmjopen-2018-024012] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
INTRODUCTION Pressure continues to grow on emergency departments in the UK and throughout the world, with declining performance and adverse effects on patient outcome, safety and experience. One proposed solution is to locate general practitioners to work in or alongside the emergency department (GPED). Several GPED models have been introduced, however, evidence of effectiveness is weak. This study aims to evaluate the impact of GPED on patient care, the primary care and acute hospital team and the wider urgent care system. METHODS AND ANALYSIS The study will be divided into three work packages (WPs). WP-A; Mapping and Taxonomy: mapping, description and classification of current models of GPED in all emergency departments in England and interviews with key informants to examine the hypotheses that underpin GPED. WP-B; Quantitative Analysis of National Data: measurement of the effectiveness, costs and consequences of the GPED models identified in WP-A, compared with a no-GPED model, using retrospective analysis of Hospital Episode Statistics Data. WP-C; Case Studies: detailed case studies of different GPED models using a mixture of qualitative and quantitative methods including: non-participant observation of clinical care, semistructured interviews with staff, patients and carers; workforce surveys with emergency department staff and analysis of available local routinely collected hospital data. Prospective case study sites will be identified by completing telephone interviews with sites awarded capital funding by the UK government to implement GPED initiatives. The study has a strong patient and public involvement group that has contributed to study design and materials, and which will be closely involved in data interpretation and dissemination. ETHICS AND DISSEMINATION The study has been approved by the National Health Service East Midlands-Leicester South Research Ethics Committee: 17/EM/0312. The results of the study will be disseminated through peer-reviewed journals, conferences and a planned programme of knowledge mobilisation. TRIAL REGISTRATION NUMBER ISRCTN51780222.
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Affiliation(s)
- Katherine Morton
- Faculty of Health and Life Sciences, University of the West of England, Bristol, UK
| | - Sarah Voss
- Faculty of Health and Life Sciences, University of the West of England, Bristol, UK
| | - Joy Adamson
- Institute of Health and Society, Newcastle University, Newcastle upon Tyne, UK
| | - Helen Baxter
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Karen Bloor
- Department of Health Sciences, University of York, York, UK
| | - Janet Brandling
- Faculty of Health and Life Sciences, University of the West of England, Bristol, UK
| | - Sean Cowlishaw
- Department of Psychiatry, University of Melbourne, Melbourne, Victoria, Australia
| | - Tim Doran
- Department of Health Sciences, University of York, York, UK
| | - Andrew Gibson
- Faculty of Health and Life Sciences, University of the West of England, Bristol, UK
| | - Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | - Dan Liu
- Centre for Health Economics, University of York, York, UK
| | - Sarah Purdy
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Paul Roy
- Bristol NHS Clinical Commissioning Group, Bristol, UK
| | | | | | - Anu Vaittinen
- Institute of Health and Society, Newcastle University, Newcastle upon Tyne, UK
| | - Rose Watson
- Institute of Health and Society, Newcastle University, Newcastle upon Tyne, UK
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O'Hara JK, Grasic K, Gutacker N, Street A, Foy R, Thompson C, Wright J, Lawton R. Identifying positive deviants in healthcare quality and safety: a mixed methods study. J R Soc Med 2018; 111:276-291. [PMID: 29749286 DOI: 10.1177/0141076818772230] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Objective Solutions to quality and safety problems exist within healthcare organisations, but to maximise the learning from these positive deviants, we first need to identify them. This study explores using routinely collected, publicly available data in England to identify positively deviant services in one region of the country. Design A mixed methods study undertaken July 2014 to February 2015, employing expert discussion, consensus and statistical modelling to identify indicators of quality and safety, establish a set of criteria to inform decisions about which indicators were robust and useful measures, and whether these could be used to identify positive deviants. Setting Yorkshire and Humber, England. Participants None - analysis based on routinely collected, administrative English hospital data. Main outcome measures We identified 49 indicators of quality and safety from acute care settings across eight data sources. Twenty-six indicators did not allow comparison of quality at the sub-hospital level. Of the 23 remaining indicators, 12 met all criteria and were possible candidates for identifying positive deviants. Results Four indicators (readmission and patient reported outcomes for hip and knee surgery) offered indicators of the same service. These were selected by an expert group as the basis for statistical modelling, which supported identification of one service in Yorkshire and Humber showing a 50% positive deviation from the national average. Conclusion Relatively few indicators of quality and safety relate to a service level, making meaningful comparisons and local improvement based on the measures difficult. It was possible, however, to identify a set of indicators that provided robust measurement of the quality and safety of services providing hip and knee surgery.
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Affiliation(s)
- Jane K O'Hara
- 1 Leeds Institute of Medical Education, University of Leeds, Leeds LS2 9NL, UK.,2 Yorkshire & Quality Research Group, Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford BD9 6RJ, UK
| | - Katja Grasic
- 3 Centre for Health Economics, University of York, York YO10 5DD, UK
| | - Nils Gutacker
- 3 Centre for Health Economics, University of York, York YO10 5DD, UK
| | - Andrew Street
- 4 Department of Health Policy, London School of Economics and Political Science, London WC2A 2AE, UK
| | - Robbie Foy
- 5 Leeds Institute of Health Sciences, University of Leeds, Leeds LS2 9NL, UK
| | - Carl Thompson
- 6 School of Healthcare, University of Leeds, Leeds LS2 9JT, UK
| | - John Wright
- 2 Yorkshire & Quality Research Group, Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford BD9 6RJ, UK
| | - Rebecca Lawton
- 2 Yorkshire & Quality Research Group, Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford BD9 6RJ, UK.,7 School of Psychology, University of Leeds, Leeds LS2 9JT, UK
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Gutacker N, Bloor K, Bojke C, Walshe K. Should interventions to reduce variation in care quality target doctors or hospitals? Health Policy 2018; 122:660-666. [PMID: 29703654 PMCID: PMC6022214 DOI: 10.1016/j.healthpol.2018.04.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2017] [Revised: 10/16/2017] [Accepted: 04/06/2018] [Indexed: 11/29/2022]
Abstract
Performance management initiatives are increasingly targeting individual doctors as well as hospitals. Less than 25% of variation in clinical outcomes is attributable to providers. More variation in clinical outcomes is associated with doctors than with hospitals. Performance estimates for individual doctors are unreliable due to small samples.
Interventions to reduce variation in care quality are increasingly targeted at both individual doctors and the organisations in which they work. Concerns remain about the scope and consequences for such performance management, the relative contribution of individuals and organisations to observed variation, and whether performance can be measured reliably. This study explores these issues in the context of the English National Health Service by analysing comprehensive administrative data for all patients treated for four clinical conditions (acute myocardial infarction, hip fracture, pneumonia, ischemic stroke) and two surgical procedures (coronary artery bypass, hip replacement) during April 2010–February 2013. Performance indicators are defined as 30-day mortality, 28-day emergency readmission and inpatient length of stay. Three-level hierarchical generalised linear mixed models are estimated to attribute variation in case-mix adjusted indicators to individual doctors and hospital organisations. Except for length of stay after hip replacement, no more than 11% of variation in case-mix adjusted performance indicators can be attributed to doctors and organisations with the rest reflecting random chance and unobserved patient factors. Doctor variation exceeds hospital variation by a factor of 1.2 or more. However, identifying poor performance amongst doctors is hampered by insufficient numbers of cases per doctor to reliably estimate their individual performances. Policy makers and regulators should therefore be cautious when targeting individual doctors in performance improvement initiatives.
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Affiliation(s)
- Nils Gutacker
- Centre for Health Economics, University of York, Heslington, York, YO10 5DD, United Kingdom.
| | - Karen Bloor
- Department of Health Sciences, University of York, United Kingdom.
| | - Chris Bojke
- Centre for Health Economics, University of York, United Kingdom.
| | - Kieran Walshe
- Alliance Manchester Business School, University of Manchester, United Kingdom.
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Gutacker N, Street A. Multidimensional performance assessment of public sector organisations using dominance criteria. Health Econ 2018; 27:e13-e27. [PMID: 28833902 PMCID: PMC5900921 DOI: 10.1002/hec.3554] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2016] [Revised: 04/05/2017] [Accepted: 06/12/2017] [Indexed: 05/21/2023]
Abstract
Public sector organisations pursue multiple objectives and serve a number of stakeholders. But stakeholders are rarely explicit about the valuations they attach to different objectives, nor are these valuations likely to be identical. This complicates the assessment of their performance because no single set of weights can be chosen legitimately to aggregate outputs into unidimensional composite scores. We propose the use of dominance criteria in a multidimensional performance assessment framework to identify best practice and poor performance under relatively weak assumptions about stakeholders' preferences. We use as an example providers of hip replacement surgery in the English National Health Service and estimate multivariate multilevel models to study their performance in terms of length of stay, readmission rates, post-operative patient-reported health status and waiting time. We find substantial correlation between objectives and demonstrate that ignoring the correlation can lead to incorrect assessments of performance.
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Moscelli G, Siciliani L, Gutacker N, Cookson R. Socioeconomic inequality of access to healthcare: Does choice explain the gradient? J Health Econ 2018; 57:290-314. [PMID: 28935158 DOI: 10.1016/j.jhealeco.2017.06.005] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Revised: 04/29/2017] [Accepted: 06/11/2017] [Indexed: 06/07/2023]
Abstract
Equity of access is a key policy objective in publicly-funded healthcare systems. However, observed inequalities of access by socioeconomic status may result from differences in patients' choices. Using data on non-emergency coronary revascularisation procedures in the English National Health Service, we found substantive differences in waiting times within public hospitals between patients with different socioeconomic status: up to 35% difference, or 43 days, between the most and least deprived population quintile groups. Using selection models with differential distances as identification variables, we estimated that only up to 12% of these waiting time inequalities can be attributed to patients' choices of hospital and type of treatment (heart bypass versus stent). Residual inequality, after allowing for choice, was economically significant: patients in the least deprived quintile group benefited from shorter waiting times and the associated health benefits were worth up to £850 per person.
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Affiliation(s)
| | - Luigi Siciliani
- Centre for Health Economics, University of York, United Kingdom; Department of Economics and Related Studies, University of York, United Kingdom
| | - Nils Gutacker
- Centre for Health Economics, University of York, United Kingdom
| | - Richard Cookson
- Centre for Health Economics, University of York, United Kingdom
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Velikova G, Valderas JM, Potter C, Batchelder L, A’Court C, Baker M, Bostock J, Coulter A, Fitzpatrick R, Forder J, Fox D, Geneen L, Gibbons E, Jenkinson C, Jones K, Kelly L, Peters M, Mulhern B, Labeit A, Rowen D, Meadows K, Elliott J, Brazier J, Knowles E, Keetharuth A, Brazier J, Connell J, Carlton J, Buck LT, Ricketts T, Barkham M, Goswami P, Salek S, Ionova T, Oliva E, Fielding AK, Karakantza M, Al-Ismail S, Collins GP, McConnell S, Langton C, Jennings DM, Else R, Kell J, Ward H, Day S, Lumley E, Phillips P, Duncan R, Buckley-Woods H, Aber A, Jones G, Michaels J, Porter I, Gangannagaripalli J, Davey A, Ricci-Cabello I, Haywood K, Hansen ST, Valderas J, Roberts D, Gumber A, Podmore B, Hutchings A, van der Meulen J, Aggarwal A, Konan S, Price A, Jackson W, Bottomley N, Philiips M, Knightley-Day T, Beard D, Gibbons E, Fitzpatrick R, Greenhalgh J, Gooding K, Gibbons E, Valderas C, Wright J, Dalkin S, Meads D, Black N, Fawkes C, Froud R, Carnes D, Price A, Cook J, Dakin H, Smith J, Kang S, Beard D, Griffiths C, Guest E, Harcourt D, Murphy M, Hollinghurst S, Salisbury C, Carlton J, Elliott J, Rowen D, Gao A, Price A, Beard D, Lemanska A, Chen T, Dearnaley DP, Jena R, Sydes M, Faithfull S, Ades AE, Kounali D, Lu G, Rombach I, Gray A, Jenkinson C, Rivero-Arias O, Holch P, Holmes M, Rodgers Z, Dickinson S, Clayton B, Davidson S, Routledge J, Glennon J, Henry AM, Franks K, Velikova G, Maguire R, McCann L, Young T, Armes J, Harris J, Miaskowski C, Kotronoulas G, Miller M, Ream E, Patiraki E, Geiger A, Berg GV, Flowerday A, Donnan P, McCrone P, Apostolidis K, Fox P, Furlong E, Kearney N, Gibbons C, Fischer F, Gibbons C, Coste J, Martinez JV, Rose M, Leplege A, Shingler S, Aldhouse N, Al-Zubeidi T, Trigg A, Kitchen H, Davey A, Porter I, Green C, Valderas JM, Coast J, Smith S, Hendriks J, Black N, Shah K, Rivero-Arias O, Ramos-Goni JM, Kreimeier S, Herdman M, Devlin N, Finch AP, Brazier JE, Mukuria C, Zamora B, Parkin D, Feng Y, Bateman A, Herdman M, Devlin N, Patton T, Gutacker N, Shah K. Proceedings of Patient Reported Outcome Measure's (PROMs) Conference Oxford 2017: Advances in Patient Reported Outcomes Research : Oxford, UK. 8th June 2017. Health Qual Life Outcomes 2017; 15:185. [PMID: 29035171 PMCID: PMC5667589 DOI: 10.1186/s12955-017-0757-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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Al Quait A, Doherty P, Gutacker N, Mills J. In the modern era of percutaneous coronary intervention: Is cardiac rehabilitation engagement purely a patient or a service level decision? Eur J Prev Cardiol 2017. [PMID: 28633533 PMCID: PMC5574495 DOI: 10.1177/2047487317717064] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Aims Despite the proven benefits of cardiac rehabilitation (CR), utilization rates remain below recommendation in the percutaneous coronary intervention cohort in most European countries. Although extensive research has been carried out on CR uptake, no previous study has investigated the factors that lead patients to attend the initial CR baseline assessment (CR engagement). This paper attempts to provide new insights into CR engagement in the growing percutaneous coronary intervention population. Methods and results In total, we analysed data on 59,807 patients who underwent percutaneous coronary intervention during 2013 to 2016 (mean age 65 years; 25% female). Twenty factors were hypothesized to have a direct impact on CR engagement and they were grouped into four main categories; namely socio-demographic factors, cardiac risk factors, medical status and service-level factors. A binary logistic regression model was constructed to examine the association between CR engagement and tested factors. All but one of the proposed factors had a statistically significant impact on CR engagement. Results showed that CR engagement decreases by 1.2% per year of age (odds ratio 0.98) and is approximately 7% lower (odds ratio 0.93) in female patients, while patients are 4.4 times more likely to engage if they receive a confirmed joining date (odds ratio 4.4). The final model achieved 86.6% sensitivity and 49.0% specificity with an area under the receiver operating characteristic curve of 0.755. Conclusion The present results highlight the important factors of the likelihood of CR engagement. This implies that future strategies should focus on factors that are associated with CR engagement.
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Affiliation(s)
- Abdulrahman Al Quait
- 1 Department of Health Sciences, Faculty of Science, University of York, UK.,2 King Fahad Medical City, Riyadh, Saudi Arabia
| | - Patrick Doherty
- 1 Department of Health Sciences, Faculty of Science, University of York, UK
| | - Nils Gutacker
- 3 Centre for Health Economics, Faculty of Science, University of York, UK
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Gutacker N, Street A. Use of large-scale HRQoL datasets to generate individualised predictions and inform patients about the likely benefit of surgery. Qual Life Res 2017; 26:2497-2505. [PMID: 28567601 PMCID: PMC5548850 DOI: 10.1007/s11136-017-1599-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/20/2017] [Indexed: 01/18/2023]
Abstract
Purpose The English NHS has mandated the routine collection of health-related quality of life (HRQoL) data before and after surgery, giving prospective patient information about the likely benefit of surgery. Yet, the information is difficult to access and interpret because it is not presented in a lay-friendly format and does not reflect patients’ individual circumstances. We set out a methodology to generate personalised information to help patients make informed decisions. Methods We used anonymised, pre- and postoperative EuroQol-5D-3L (EQ-5D) data for over 490,000 English NHS patients who underwent primary hip or knee replacement surgery or groin hernia repair between April 2009 and March 2016. We estimated linear regression models to relate changes in EQ-5D utility scores to patients’ own assessment of the success of surgery, and calculated from that minimally important differences for health improvements/deteriorations. Classification tree analysis was used to develop algorithms that sort patients into homogeneous groups that best predict postoperative EQ-5D utility scores. Results Patients were classified into between 55 (hip replacement) to 60 (hernia repair) homogeneous groups. The classifications explained between 14 and 27% of variation in postoperative EQ-5D utility score. Conclusions Patients are heterogeneous in their expected benefit from surgery, and decision aids should reflect this. Large administrative datasets on HRQoL can be used to generate the required individualised predictions to inform patients.
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Affiliation(s)
- Nils Gutacker
- Centre for Health Economics, University of York, Heslington, YO10 5DD, UK.
| | - Andrew Street
- Centre for Health Economics, University of York, Heslington, YO10 5DD, UK
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Gutacker N, Siciliani L, Moscelli G, Gravelle H. Choice of hospital: Which type of quality matters? J Health Econ 2016; 50:230-246. [PMID: 27590088 PMCID: PMC5138156 DOI: 10.1016/j.jhealeco.2016.08.001] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2015] [Revised: 06/27/2016] [Accepted: 08/16/2016] [Indexed: 05/25/2023]
Abstract
The implications of hospital quality competition depend on what type of quality affects choice of hospital. Previous studies of quality and choice of hospitals have used crude measures of quality such as mortality and readmission rates rather than measures of the health gain from specific treatments. We estimate multinomial logit models of hospital choice by patients undergoing hip replacement surgery in the English NHS to test whether hospital demand responds to quality as measured by detailed patient reports of health before and after hip replacement. We find that a one standard deviation increase in average health gain increases demand by up to 10%. The more traditional measures of hospital quality are less important in determining hospital choice.
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Affiliation(s)
- Nils Gutacker
- Centre for Health Economics, University of York, York, United Kingdom.
| | - Luigi Siciliani
- Department of Economics and Related Studies, University of York, York, United Kingdom
| | - Giuseppe Moscelli
- Centre for Health Economics, University of York, York, United Kingdom
| | - Hugh Gravelle
- Centre for Health Economics, University of York, York, United Kingdom
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Croudace T, Brazier J, Gutacker N, Street A, Robotham D, Waterman S, Rose D, Satkunanathan S, Wykes T, Nasr N, Enderby P, Carlton J, Rowen D, Elliott J, Brazier J, Stevens K, Basarir H, Labeit A, Murphy M, Hollinghurst S, Salisbury C, Marley D, Wilson J, Barrat A, Roy B, Rombach I, Burke Ó, Jenkinson C, Gray A, Rivero-Arias O, Porter I, Gangannagaripalli J, Bramwell C, Valderas JM, Holch P, Davidson S, Routledge J, Henry A, Franks K, Gilbert A, Absolom K, Velikova G, Porter I, Valderas JM, Boehnke JR, Trigg A, Howells R, Singh J, Pokhrel S, Longworth L, Potter C, Hunter C, Kelly L, Gibbons E, Forder J, Coulter A, Fitzpatrick R, Peters M. Proceedings of Patient Reported Outcome Measure’s (PROMs) Conference Sheffield 2016: advances in patient reported outcomes research. Health Qual Life Outcomes 2016. [PMCID: PMC5073844 DOI: 10.1186/s12955-016-0540-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
S1 Using computerized adaptive testing Tim Croudace S2 Well-being: what is it, how does it compare to health and what are the implications of using it to inform health policy John Brazier O1 “Am I going to get better?”—Using PROMs to inform patients about the likely benefit of surgery Nils Gutacker, Andrew Street O2 Identifying Patient Reported Outcome Measures for an electronic Personal Health Record Dan Robotham, Samantha Waterman, Diana Rose, Safarina Satkunanathan, Til Wykes O3 Examining the change process over time qualitatively: transformative learning and response shift Nasrin Nasr, Pamela Enderby O4 Developing a PROM to evaluate self-management in diabetes (HASMID): giving patients a voice Jill Carlton, Donna Rowen, Jackie Elliott, John Brazier, Katherine Stevens, Hasan Basarir, Alex Labeit O5 Development of the Primary Care Outcomes Questionnaire (PCOQ) Mairead Murphy, Sandra Hollinghurst, Chris Salisbury O6 Developing the PKEX score- a multimodal assessment tool for patients with shoulder problems Dominic Marley, James Wilson, Amy Barrat, Bibhas Roy O7 Applying multiple imputation to multi-item patient reported outcome measures: advantages and disadvantages of imputing at the item, sub-scale or score level Ines Rombach, Órlaith Burke, Crispin Jenkinson, Alastair Gray, Oliver Rivero-Arias O8 Integrating Patient Reported Outcome Measures (PROMs) into routine primary care for patients with multimorbidity: a feasibility study Ian Porter, Jaheeda Gangannagaripalli, Charlotte Bramwell, Jose M. Valderas O9 eRAPID: electronic self-report and management of adverse-events for pelvic radiotherapy (RT) patients Patricia Holch, Susan Davidson, Jacki Routledge, Ann Henry, Kevin Franks, Alex Gilbert, Kate Absolom & Galina Velikova O10 Patient reported outcomes (PROMs) based recommendation in clinical guidance for the management of chronic conditions in the United Kingdom Ian Porter, Jose M.Valderas O11 Cross-sectional and longitudinal parameter shifts in epidemiological data: measurement invariance and response shifts in cohort and survey data describing the UK’s Quality of Life Jan R. Boehnke O12 Patient-reported outcomes within health technology decision making: current status and implications for future policy Andrew Trigg, Ruth Howells O13 Can social care needs and well-being be explained by the EQ-5D? Analysis of Health Survey for England dataset Jeshika Singh, Subhash Pokhrel, Louise Longworth O14 Where patients and policy meet: exploring individual-level use of the Long-Term Conditions Questionnaire (LTCQ) Caroline Potter, Cheryl Hunter, Laura Kelly, Elizabeth Gibbons, Julian Forder, Angela Coulter, Ray Fitzpatrick, Michele Peters
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Moscelli G, Siciliani L, Gutacker N, Gravelle H. Location, quality and choice of hospital: Evidence from England 2002-2013. Reg Sci Urban Econ 2016; 60:112-124. [PMID: 27766000 PMCID: PMC5063539 DOI: 10.1016/j.regsciurbeco.2016.07.001] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2015] [Revised: 06/30/2016] [Accepted: 07/03/2016] [Indexed: 05/16/2023]
Abstract
We investigate (a) how patient choice of hospital for elective hip replacement is influenced by distance, quality and waiting times, (b) differences in choices between patients in urban and rural locations, (c) the relationship between hospitals' elasticities of demand to quality and the number of local rivals, and how these changed after relaxation of constraints on hospital choice in England in 2006. Using a data set on over 500,000 elective hip replacement patients over the period 2002 to 2013 we find that patients became more likely to travel to a provider with higher quality or lower waiting times, the proportion of patients bypassing their nearest provider increased from 25% to almost 50%, and hospital elasticity of demand with respect to own quality increased. By 2013 average hospital demand elasticity with respect to readmission rates and waiting times were - 0.2 and - 0.04. Providers facing more rivals had demand that was more elastic with respect to quality and waiting times. Patients from rural areas have smaller disutility from distance.
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Affiliation(s)
- Giuseppe Moscelli
- Economics of Social and Health Care Research Unit, Centre for Health Economics, University of York, York YO10 5DD, United Kingdom
| | - Luigi Siciliani
- Department of Economics and Related Studies, University of York, York YO10 5DD, United Kingdom
| | - Nils Gutacker
- Economics of Social and Health Care Research Unit, Centre for Health Economics, University of York, York YO10 5DD, United Kingdom
| | - Hugh Gravelle
- Economics of Social and Health Care Research Unit, Centre for Health Economics, University of York, York YO10 5DD, United Kingdom
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Gutacker N, Bloor K, Cookson R, Gale CP, Maynard A, Pagano D, Pomar J, Bernal-Delgado E. Hospital Surgical Volumes and Mortality after Coronary Artery Bypass Grafting: Using International Comparisons to Determine a Safe Threshold. Health Serv Res 2016; 52:863-878. [PMID: 27198068 DOI: 10.1111/1475-6773.12508] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
OBJECTIVE To estimate a safe minimum hospital volume for hospitals performing coronary artery bypass graft (CABG) surgery. DATA SOURCE Hospital data on all publicly funded CABG in five European countries, 2007-2009 (106,149 patients). DESIGN Hierarchical logistic regression models to estimate the relationship between hospital volume and mortality, allowing for case mix. Segmented regression analysis to estimate a threshold. FINDINGS The 30-day in-hospital mortality rate was 3.0 percent overall, 5.2 percent (95 percent CI: 4.0-6.4) in low-volume hospitals, and 2.1 percent (95 percent CI: 1.8-2.3) in high-volume hospitals. There is a significant curvilinear relationship between volume and mortality, flatter above 415 cases per hospital per year. CONCLUSIONS There is a clear relationship between hospital CABG volume and mortality in Europe, implying a "safe" threshold volume of 415 cases per year.
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Affiliation(s)
- Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | - Karen Bloor
- Department of Health Sciences, University of York, York, UK
| | | | - Chris P Gale
- Division of Epidemiology and Biostatistics, University of Leeds, UK
| | - Alan Maynard
- Department of Health Sciences, University of York, York, UK
| | - Domenico Pagano
- Department of Cardiothoracic Surgery, University Hospital Birmingham Queen Elizabeth, Edgbaston, UK
| | - José Pomar
- Department of Cardiovascular Surgery, Hospital Clinic de Barcelona, Barcelona, Spain
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Abstract
A number of OECD countries have introduced waiting time prioritisation policies which give explicit priority to severely ill patients with high marginal disutility of waiting. There is however little empirical evidence on how patients are actually prioritised. We exploit a unique opportunity to investigate this issue using a large national dataset with accurate measures of severity on nearly 400,000 patients. We link data from a national patient-reported outcome measures survey to administrative data on all patients waiting for a publicly funded hip and knee replacement in England during the years 2009-14. We find that patients suffering the most severe pain and immobility have shorter waits than those suffering the least, by about 24% for hip replacement and 11% for knee replacement, and that the association is approximately linear. These differentials are more closely associated with pain than immobility, and are larger in hospitals with longer average waiting times. These result suggests that doctors prioritise patients according to severity even when no formal prioritisation policy is in place and average waiting times are short.
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Affiliation(s)
- Nils Gutacker
- Centre for Health Economics, University of York, UK.
| | - Luigi Siciliani
- Department of Economics and Related Studies, University of York, UK
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Gomes M, Gutacker N, Bojke C, Street A. Addressing Missing Data in Patient-Reported Outcome Measures (PROMS): Implications for the Use of PROMS for Comparing Provider Performance. Health Econ 2016; 25:515-28. [PMID: 25740592 PMCID: PMC4973682 DOI: 10.1002/hec.3173] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2014] [Revised: 11/27/2014] [Accepted: 02/10/2015] [Indexed: 05/03/2023]
Abstract
Patient-reported outcome measures (PROMs) are now routinely collected in the English National Health Service and used to compare and reward hospital performance within a high-powered pay-for-performance scheme. However, PROMs are prone to missing data. For example, hospitals often fail to administer the pre-operative questionnaire at hospital admission, or patients may refuse to participate or fail to return their post-operative questionnaire. A key concern with missing PROMs is that the individuals with complete information tend to be an unrepresentative sample of patients within each provider and inferences based on the complete cases will be misleading. This study proposes a strategy for addressing missing data in the English PROM survey using multiple imputation techniques and investigates its impact on assessing provider performance. We find that inferences about relative provider performance are sensitive to the assumptions made about the reasons for the missing data.
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Affiliation(s)
- Manuel Gomes
- Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK
| | - Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | - Chris Bojke
- Centre for Health Economics, University of York, York, UK
| | - Andrew Street
- Centre for Health Economics, University of York, York, UK
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Hall M, Laut K, Dondo TB, Alabas OA, Brogan RA, Gutacker N, Cookson R, Norman P, Timmis A, de Belder M, Ludman PF, Gale CP. Patient and hospital determinants of primary percutaneous coronary intervention in England, 2003-2013. Heart 2016; 102:313-319. [PMID: 26732182 PMCID: PMC4752647 DOI: 10.1136/heartjnl-2015-308616] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
OBJECTIVE Primary percutaneous coronary intervention (PPCI) for ST-elevation myocardial infarction (STEMI) is insufficiently implemented in many countries. We investigated patient and hospital characteristics associated with PPCI utilisation. METHODS Whole country registry data (MINAP, Myocardial Ischaemia National Audit Project) comprising PPCI-capable National Health Service trusts in England (84 hospital trusts; 92 350 hospitalisations; 90 489 patients), 2003-2013. Multilevel Poisson regression modelled the relationship between incidence rate ratios (IRR) of PPCI and patient and trust-level factors. RESULTS Overall, standardised rates of PPCI increased from 0.01% to 86.3% (2003-2013). While, on average, there was a yearly increase in PPCI utilisation of 30% (adjusted IRR 1.30, 95% CI 1.23 to 1.36), it varied substantially between trusts. PPCI rates were lower for patients with previous myocardial infarction (0.95, 0.93 to 0.98), heart failure (0.86, 0.81 to 0.92), angina (0.96, 0.94 to 0.98), diabetes (0.97, 0.95 to 0.99), chronic renal failure (0.89, 0.85 to 0.90), cerebrovascular disease (0.96, 0.93 to 0.99), age >80 years (0.87, 0.85 to 0.90), and travel distances >30 km (0.95, 0.93 to 0.98). PPCI rates were higher for patients with previous percutaneous coronary intervention (1.09, 1.05 to 1.12) and among trusts with >5 interventional cardiologists (1.30, 1.25 to 1.34), more visiting interventional cardiologists (1-5: 1.31, 1.26 to 1.36; ≥6: 1.42, 1.35 to 1.49), and a 24 h, 7-days-a-week PPCI service (2.69, 2.58 to 2.81). Half of the unexplained variation in PPCI rates was due to between-trust differences. CONCLUSIONS Following an 8 year implementation phase, PPCI utilisation rates stabilised at 85%. However, older and sicker patients were less likely to receive PPCI and there remained between-trust variation in PPCI rates not attributable to differences in staffing levels. Compliance with clinical pathways for STEMI is needed to ensure more equitable quality of care.
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Affiliation(s)
- M Hall
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - K Laut
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - T B Dondo
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - O A Alabas
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - R A Brogan
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK York Teaching Hospital NHS Foundation Trust, York, UK
| | - N Gutacker
- Centre for Health Economics, University of York, York, UK
| | - R Cookson
- Centre for Health Economics, University of York, York, UK
| | - P Norman
- School of Geography, University of Leeds, Leeds, UK
| | - A Timmis
- NIHR Biomedical Research Unit at Barts Health, Queen Mary University, London, UK
| | - M de Belder
- The James Cook University Hospital, South Tees Hospitals NHS Foundation Trust, Middlesbrough, UK
| | - P F Ludman
- Queen Elizabeth Hospital, Birmingham, UK
| | - C P Gale
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK York Teaching Hospital NHS Foundation Trust, York, UK
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Jacobs R, Gutacker N, Mason A, Goddard M, Gravelle H, Kendrick T, Gilbody S. Determinants of hospital length of stay for people with serious mental illness in England and implications for payment systems: a regression analysis. BMC Health Serv Res 2015; 15:439. [PMID: 26424408 PMCID: PMC4590310 DOI: 10.1186/s12913-015-1107-6] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2015] [Accepted: 09/23/2015] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Serious mental illness (SMI), which encompasses a set of chronic conditions such as schizophrenia, bipolar disorder and other psychoses, accounts for 3.4 m (7 %) total bed days in the English NHS. The introduction of prospective payment to reimburse hospitals makes an understanding of the key drivers of length of stay (LOS) imperative. Existing evidence, based on mainly small scale and cross-sectional studies, is mixed. Our study is the first to use large-scale national routine data to track English hospitals' LOS for patients with a main diagnosis of SMI over time to examine the patient and local area factors influencing LOS and quantify the provider level effects to draw out the implications for payment systems. METHODS We analysed variation in LOS for all SMI admissions to English hospitals from 2006 to 2010 using Hospital Episodes Statistics (HES). We considered patients with a LOS of up to 180 days and estimated Poisson regression models with hospital fixed effects, separately for admissions with one of three main diagnoses: schizophrenia; psychotic and schizoaffective disorder; and bipolar affective disorder. We analysed the independent contribution of potential determinants of LOS including clinical and socioeconomic characteristics of the patient, access to and quality of primary care, and local area characteristics. We examined the degree of unexplained variation in provider LOS. RESULTS Most risk factors did not have a differential effect on LOS for different diagnostic sub-groups, however we did find some heterogeneity in the effects. Shorter LOS in the pooled model was associated with co-morbid substance or alcohol misuse (4 days), and personality disorder (8 days). Longer LOS was associated with older age (up to 19 days), black ethnicity (4 days), and formal detention (16 days). Gender was not a significant predictor. Patients who self-discharged had shorter LOS (20 days). No association was found between higher primary care quality and LOS. We found large differences between providers in unexplained variation in LOS. CONCLUSIONS By identifying key determinants of LOS our results contribute to a better understanding of the implications of case-mix to ensure prospective payment systems reflect accurately the resource use within sub-groups of patients with SMI.
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Affiliation(s)
- Rowena Jacobs
- Centre for Health Economics, University of York, Heslington, York, UK.
| | - Nils Gutacker
- Centre for Health Economics, University of York, Heslington, York, UK.
| | - Anne Mason
- Centre for Health Economics, University of York, Heslington, York, UK.
| | - Maria Goddard
- Centre for Health Economics, University of York, Heslington, York, UK.
| | - Hugh Gravelle
- Centre for Health Economics, University of York, Heslington, York, UK.
| | - Tony Kendrick
- Primary Care and Population Sciences, University of Southampton, Southampton, UK.
| | - Simon Gilbody
- Department of Health Sciences, University of York, Heslington, York, UK.
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Gutacker N, Bloor K, Cookson R, Garcia-Armesto S, Bernal-Delgado E. Comparing hospital performance within and across countries: an illustrative study of coronary artery bypass graft surgery in England and Spain. Eur J Public Health 2015; 25 Suppl 1:28-34. [PMID: 25690127 DOI: 10.1093/eurpub/cku228] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVE To assess the feasibility, strengths and weaknesses of using administrative data to compare hospital performance across countries, using mortality after coronary artery bypass graft (CABG) surgery as an illustrative example. METHODS Country specific and pooled models using individual-level data and logistic regression methods assess individual hospital performance using funnel plots accounting for multiple testing. Outcomes are adjusted for age, sex, comorbidities and indicators of patient severity. Data includes patients from all publicly funded hospitals delivering CABG surgery in England and Spain. Inpatient hospital-level standardized mortality rates within 30 days of CABG surgery are calculated for 83 999 CABG patients between 2007 and 2009. RESULTS Unadjusted national mortality rates are 5% in Spain and 2.3% in England. Country-specific models identified similar patterns of excess mortality 'alerts' and 'alarms' in hospitals in Spain or England. Pooling data from both countries identifies larger numbers of alerts and alarms in Spanish hospitals, and risk-adjustment increased the already large national mortality difference. This was reduced but not eliminated by accounting for lower volume in Spanish hospitals. CONCLUSION Cross-national comparisons potentially add value by providing international performance benchmarks. Hospital-level analysis across countries can illuminate differences in hospital performance, which might not be identified using country-specific data or incomplete registry data, and can test hypotheses that may explain national differences. Difficulties of making data comparable between countries, however, compound the usual within-country measurement problems.
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Affiliation(s)
- Nils Gutacker
- 1 Centre for Health Economics, University of York, England, UK
| | - Karen Bloor
- 2 Department of Health Sciences, University of York, England, UK
| | - Richard Cookson
- 1 Centre for Health Economics, University of York, England, UK
| | - Sandra Garcia-Armesto
- 3 Institute for Health Sciences in Aragon, IIS Aragon, Zaragoza, Spain 4 Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Spain
| | - Enrique Bernal-Delgado
- 3 Institute for Health Sciences in Aragon, IIS Aragon, Zaragoza, Spain 4 Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Spain
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Gutacker N, Mason AR, Kendrick T, Goddard M, Gravelle H, Gilbody S, Aylott L, Wainwright J, Jacobs R. Does the quality and outcomes framework reduce psychiatric admissions in people with serious mental illness? A regression analysis. BMJ Open 2015; 5:e007342. [PMID: 25897027 PMCID: PMC4410123 DOI: 10.1136/bmjopen-2014-007342] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND The Quality and Outcomes Framework (QOF) incentivises general practices in England to provide proactive care for people with serious mental illness (SMI) including schizophrenia, bipolar disorder and other psychoses. Better proactive primary care may reduce the risk of psychiatric admissions to hospital, but this has never been tested empirically. METHODS The QOF data set included 8234 general practices in England from 2006/2007 to 2010/2011. Rates of hospital admissions with primary diagnoses of SMI or bipolar disorder were estimated from national routine hospital data and aggregated to practice level. Poisson regression was used to analyse associations. RESULTS Practices with higher achievement on the annual review for SMI patients (MH9), or that performed better on either of the two lithium indicators for bipolar patients (MH4 or MH5), had more psychiatric admissions. An additional 1% in achievement rates for MH9 was associated with an average increase in the annual practice admission rate of 0.19% (95% CI 0.10% to 0.28%) or 0.007 patients (95% CI 0.003 to 0.01). CONCLUSIONS The positive association was contrary to expectation, but there are several possible explanations: better quality primary care may identify unmet need for secondary care; higher QOF achievement may not prevent the need for secondary care; individuals may receive their QOF checks postdischarge rather than prior to admission; individuals with more severe SMI may be more likely to be registered with practices with better QOF performance; and QOF may be a poor measure of the quality of care for people with SMI.
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Affiliation(s)
- Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | - Anne R Mason
- Centre for Health Economics, University of York, York, UK
| | - Tony Kendrick
- Primary Care and Population Sciences, University of Southampton, Aldermoor Health Centre, Southampton, UK
| | - Maria Goddard
- Centre for Health Economics, University of York, York, UK
| | - Hugh Gravelle
- Centre for Health Economics, University of York, York, UK
| | - Simon Gilbody
- Department of Health Sciences, University of York, York, UK
| | | | | | - Rowena Jacobs
- Centre for Health Economics, University of York, York, UK
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Jacobs R, Gutacker N, Mason A, Goddard M, Gravelle H, Kendrick T, Gilbody S, Aylott L, Wainwright J. Do higher primary care practice performance scores predict lower rates of emergency admissions for persons with serious mental illness? An analysis of secondary panel data. Health Services and Delivery Research 2015. [DOI: 10.3310/hsdr03160] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
BackgroundSerious mental illness (SMI) is a set of chronic enduring conditions including schizophrenia and bipolar disorder. SMIs are associated with poor outcomes, high costs and high levels of disease burden. Primary care plays a central role in the care of people with a SMI in the English NHS. Good-quality primary care has the potential to reduce emergency hospital admissions, but also to increase elective admissions if physical health problems are identified by regular health screening of people with SMIs. Better-quality primary care may reduce length of stay (LOS) by enabling quicker discharge, and it may also reduce NHS expenditure.ObjectivesWe tested whether or not better-quality primary care, as assessed by the SMI quality indicators measured routinely in the Quality and Outcomes Framework (QOF) in English general practice, is associated with lower rates of emergency hospital admissions for people with SMIs, for both mental and physical conditions and with higher rates of elective admissions for physical conditions in people with a SMI. We also tested the impact of SMI QOF indicators on LOS and costs.DataWe linked administrative data from around 8500 general practitioner (GP) practices and from Hospital Episode Statistics for the study period 2006/7 to 2010/11. We identified SMI admissions by a mainInternational Classification of Diseases, 10th revision (ICD-10) diagnosis of F20–F31. We included information on GP practice and patient population characteristics, area deprivation and other potential confounders such as access to care. Analyses were carried out at a GP practice level for admissions, but at a patient level for LOS and cost analyses.MethodsWe ran mixed-effects count data and linear models taking account of the nested structure of the data. All models included year indicators for temporal trends.ResultsContrary to expectation, we found a positive association between QOF achievement and admissions, for emergency admissions for both mental and physical health. An additional 10% in QOF achievement was associated with an increase in the practice emergency SMI admission rate of approximately 1.9%. There was no significant association of QOF achievement with either LOS or cost. All results were robust to sensitivity analyses.ConclusionsPossible explanations for our findings are (1) higher quality of primary care, as measured by QOF may not effectively prevent the need for secondary care; (2) patients may receive their QOF checks post discharge, rather than prior to admission; (3) people with more severe SMIs, at a greater risk of admission, may select into practices that are better organised to provide their care and which have better QOF performance; (4) better-quality primary care may be picking up unmet need for secondary care; and (5) QOF measures may not accurately reflect quality of primary care. Patient-level data on quality of care in general practice is required to determine the reasons for the positive association of QOF quality and admissions. Future research should also aim to identify the non-QOF measures of primary care quality that may reduce unplanned admissions more effectively and could potentially be incentivised.FundingThe National Institute for Health Research Health Services and Delivery Research programme.
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Affiliation(s)
- Rowena Jacobs
- Centre for Health Economics, University of York, York, UK
| | - Nils Gutacker
- Centre for Health Economics, University of York, York, UK
| | - Anne Mason
- Centre for Health Economics, University of York, York, UK
| | - Maria Goddard
- Centre for Health Economics, University of York, York, UK
| | - Hugh Gravelle
- Centre for Health Economics, University of York, York, UK
| | - Tony Kendrick
- Primary Care and Population Sciences, University of Southampton, Southampton, UK
| | - Simon Gilbody
- Department of Health Sciences, University of York, York, UK
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Gutacker N, Street A, Gomes M, Bojke C. Should English healthcare providers be penalised for failing to collect patient-reported outcome measures? A retrospective analysis. J R Soc Med 2015; 108:304-16. [PMID: 25827906 DOI: 10.1177/0141076815576700] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVE The best practice tariff for hip and knee replacement in the English National Health Service (NHS) rewards providers based on improvements in patient-reported outcome measures (PROMs) collected before and after surgery. Providers only receive a bonus if at least 50% of their patients complete the preoperative questionnaire. We determined how many providers failed to meet this threshold prior to the policy introduction and assessed longitudinal stability of participation rates. DESIGN Retrospective observational study using data from Hospital Episode Statistics and the national PROM programme from April 2009 to March 2012. We calculated participation rates based on either (a) all PROM records or (b) only those that could be linked to inpatient records; constructed confidence intervals around rates to account for sampling variation; applied precision weighting to allow for volume; and applied risk adjustment. SETTING NHS hospitals and private providers in England. PARTICIPANTS NHS patients undergoing elective unilateral hip and knee replacement surgery. MAIN OUTCOME MEASURES Number of providers with participation rates statistically significantly below 50%. RESULTS Crude rates identified many providers that failed to achieve the 50% threshold but there were substantially fewer after adjusting for uncertainty and precision. While important, risk adjustment required restricting the analysis to linked data. Year-on-year correlation between provider participation rates was moderate. CONCLUSIONS Participation rates have improved over time and only a small number of providers now fall below the threshold, but administering preoperative questionnaires remains problematic in some providers. We recommend that participation rates are based on linked data and take into account sampling variation.
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Affiliation(s)
- Nils Gutacker
- Centre for Health Economics, University of York, York YO10 5DD, UK
| | - Andrew Street
- Centre for Health Economics, University of York, York YO10 5DD, UK
| | - Manuel Gomes
- Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK
| | - Chris Bojke
- Centre for Health Economics, University of York, York YO10 5DD, UK
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Cookson R, Gutacker N, Garcia-Armesto S, Angulo-Pueyo E, Christiansen T, Bloor K, Bernal-Delgado E. Socioeconomic inequality in hip replacement in four European countries from 2002 to 2009--area-level analysis of hospital data. Eur J Public Health 2015; 25 Suppl 1:21-7. [DOI: 10.1093/eurpub/cku220] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Gutacker N, Bloor K, Cookson R. Comparing the performance of the Charlson/Deyo and Elixhauser comorbidity measures across five European countries and three conditions. Eur J Public Health 2015; 25 Suppl 1:15-20. [DOI: 10.1093/eurpub/cku221] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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