Impact and sustainability of centralising acute stroke services in English metropolitan areas: retrospective analysis of hospital episode statistics and stroke national audit data

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Abstract

Objectives

To investigate whether further centralisation of acute stroke services in Greater Manchester in 2015 was associated with changes in outcomes and whether the effects of centralisation of acute stroke services in London in 2010 were sustained.

Design

Retrospective analyses of patient level data from the Hospital Episode Statistics (HES) database linked to mortality data from the Office for National Statistics, and the Sentinel Stroke National Audit Programme (SSNAP).

Setting

Acute stroke services in Greater Manchester and London, England.

Participants

509 182 stroke patients in HES living in urban areas admitted between January 2008 and March 2016; 218 120 stroke patients in SSNAP between April 2013 and March 2016.

Interventions

Hub and spoke models for acute stroke care.

Main outcome measures

Mortality at 90 days after hospital admission; length of acute hospital stay; treatment in a hyperacute stroke unit; 19 evidence based clinical interventions.

Results

In Greater Manchester, borderline evidence suggested that risk adjusted mortality at 90 days declined overall; a significant decline in mortality was seen among patients treated at a hyperacute stroke unit (difference-in-differences −1.8% (95% confidence interval −3.4 to −0.2)), indicating 69 fewer deaths per year. A significant decline was seen in risk adjusted length of acute hospital stay overall (−1.5 (−2.5 to −0.4) days; P<0.01), indicating 6750 fewer bed days a year. The number of patients treated in a hyperacute stroke unit increased from 39% in 2010-12 to 86% in 2015/16. In London, the 90 day mortality rate was sustained (P>0.05), length of hospital stay declined (P<0.01), and more than 90% of patients were treated in a hyperacute stroke unit. Achievement of evidence based clinical interventions generally remained constant or improved in both areas.

Conclusions

Centralised models of acute stroke care, in which all stroke patients receive hyperacute care, can reduce mortality and length of acute hospital stay and improve provision of evidence based clinical interventions. Effects can be sustained over time.

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Most cited references 46

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Global burden of stroke and risk factors in 188 countries, during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

Valery L. Feigin, Gregory Roth, Mohsen Naghavi … (2016)

The contribution of modifiable risk factors to the increasing global and regional burden of stroke is unclear, but knowledge about this contribution is crucial for informing stroke prevention strategies. We used data from the Global Burden of Disease Study 2013 (GBD 2013) to estimate the population-attributable fraction (PAF) of stroke-related disability-adjusted life-years (DALYs) associated with potentially modifiable environmental, occupational, behavioural, physiological, and metabolic risk factors in different age and sex groups worldwide and in high-income countries and low-income and middle-income countries, from 1990 to 2013.

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Organised inpatient (stroke unit) care for stroke.

(2013)

Organised stroke unit care is provided by multidisciplinary teams that exclusively manage stroke patients in a ward dedicated to stroke patients, with a mobile stroke team or within a generic disability service (mixed rehabilitation ward). To assess the effect of stroke unit care compared with alternative forms of care for people following a stroke. We searched the trials registers of the Cochrane Stroke Group (January 2013) and the Cochrane Effective Practice and Organisation of Care (EPOC) Group (January 2013), MEDLINE (2008 to September 2012), EMBASE (2008 to September 2012) and CINAHL (1982 to September 2012). In an effort to identify further published, unpublished and ongoing trials, we searched 17 trial registers (January 2013), performed citation tracking of included studies, checked reference lists of relevant articles and contacted trialists. Randomised controlled clinical trials comparing organised inpatient stroke unit care with an alternative service. After formal risk of bias assessment, we have now excluded previously included quasi-randomised trials. Two review authors initially assessed eligibility and trial quality. We checked descriptive details and trial data with the co-ordinators of the original trials. We included 28 trials, involving 5855 participants, comparing stroke unit care with an alternative service. More-organised care was consistently associated with improved outcomes. Twenty-one trials (3994 participants) compared stroke unit care with care provided in general wards. Stroke unit care showed reductions in the odds of death recorded at final (median one year) follow-up (odds ratio (OR) 0.87, 95% confidence interval (CI) 0.69 to 0.94; P = 0.005), the odds of death or institutionalised care (OR 0.78, 95% CI 0.68 to 0.89; P = 0.0003) and the odds of death or dependency (OR 0.79, 95% CI 0.68 to 0.90; P = 0.0007). Sensitivity analyses indicated that the observed benefits remained when the analysis was restricted to securely randomised trials that used unequivocally blinded outcome assessment with a fixed period of follow-up. Outcomes were independent of patient age, sex, initial stroke severity or stroke type, and appeared to be better in stroke units based in a discrete ward. There was no indication that organised stroke unit care resulted in a longer hospital stay. Stroke patients who receive organised inpatient care in a stroke unit are more likely to be alive, independent, and living at home one year after the stroke. The benefits were most apparent in units based in a discrete ward. We observed no systematic increase in the length of inpatient stay.

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Multiple regression of cost data: use of generalised linear models.

Julie Barber, Simon Thompson (2004)

Choosing an appropriate method for regression analyses of cost data is problematic because it must focus on population means while taking into account the typically skewed distribution of the data. In this paper we illustrate the use of generalised linear models for regression analysis of cost data. We consider generalised linear models with either an identity link function (providing additive covariate effects) or log link function (providing multiplicative effects), and with gaussian (normal), overdispersed poisson, gamma, or inverse gaussian distributions. These are applied to estimate the treatment effects in two randomised trials adjusted for baseline covariates. Criteria for choosing an appropriate model are presented. In both examples considered, the gaussian model fits poorly and other distributions are to be preferred. When there are variables of prognostic importance in the model, using different distributions can materially affect the estimates obtained; it may also be possible to discriminate between additive and multiplicative covariate effects. Generalised linear models are attractive for the regression of cost data because they provide parametric methods of analysis where a variety of non-normal distributions can be specified and the way covariates act can be altered. Unlike the use of data transformation in ordinary least-squares regression, generalised linear models make inferences about the mean cost directly.

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Author and article information

Contributors

Angus I G Ramsay: Role: senior research associate

Ruth J Boaden: Role: professor of service operations management

Rachael M Hunter: Role: principal research associate

Christopher McKevitt: Role: professor of social sciences and health

Lizz Paley: Role: stroke programme intelligence manager

Catherine Perry: Role: research fellow

Anthony G Rudd: Role: professor of stroke medicine

Simon J Turner: Role: senior lecturer

Pippa J Tyrrell: Role: honorary professor of stroke medicine

Charles D A Wolfe: Role: professor of public health medicine

Naomi J Fulop: Role: professor of health care organisation and management

Stephen Morris:

ORCID: https://orcid.org/0000-0002-5828-3563

Role: professor of health economics

Journal

Journal ID (nlm-ta): BMJ

Journal ID (iso-abbrev): BMJ

Journal ID (publisher-id): BMJ-UK

Journal ID (hwp): bmj

Title: The BMJ

Publisher: BMJ Publishing Group Ltd.

ISSN (Print): 0959-8138

ISSN (Electronic): 1756-1833

Publication date Collection: 2019

Publication date (Electronic): 23 January 2019

Volume: 364

Electronic Location Identifier: l1

Affiliations

[1 ]Department of Applied Health Research, University College London, London WC1E 7HB, UK

[2 ]Alliance Manchester Business School, University of Manchester, Manchester M15 6PB, UK

[3 ]Research Department of Primary Care and Population Health, University College London, London NW3 2PF, UK

[4 ]Department of Population Health Sciences, School of Population Heath and Environmental Sciences, King’s College London, London SE1 1UL, UK

[5 ]Stroke Programme, Royal College of Physicians, London, UK

[6 ]Guy’s and St Thomas’ NHS Foundation Trust, St Thomas' Hospital, London SE1 7EH, UK

[7 ]Health Policy, Politics and Organisation (HiPPO) Research Group, Centre for Primary Care, School of Health Sciences, University of Manchester, Manchester M13 9PL, UK

[8 ]Stroke and Vascular Centre, University of Manchester, Manchester Academic Health Science Centre, Salford Royal Hospitals NHS Foundation Trust, Salford M6 8HD, UK

[9 ]National Institute of Health Research Comprehensive Biomedical Research Centre, Guy’s and St Thomas’ NHS Foundation Trust and King’s College London, Guy’s Hospital, London SE1 9RT, UK

Author notes

Correspondence to: S Morris steve.morris@ 123456ucl.ac.uk

Author information

Stephen Morris https://orcid.org/0000-0002-5828-3563

Article

Publisher ID: mors046272

DOI: 10.1136/bmj.l1

PMC ID: 6334718

PubMed ID: 30674465

SO-VID: 043bce3b-ae97-4045-a785-bb4ebea2de9a

License:

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/.

Impact and sustainability of centralising acute stroke services in English metropolitan areas: retrospective analysis of hospital episode statistics and stroke national audit data

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Abstract

Objectives

Design

Setting

Participants

Interventions

Main outcome measures

Results

Conclusions

Related collections

UCL: UN SDG 03 Good Health and Well-Being

Most cited references 46

Global burden of stroke and risk factors in 188 countries, during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

Organised inpatient (stroke unit) care for stroke.

Multiple regression of cost data: use of generalised linear models.

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