Implementing emergency admission risk prediction in general practice: a qualitative study

Evans, Bridie; Dale, Jeremy; Davies, Jan; Hutchings, Hayley; Kingston, Mark; Porter, Alison; Russell, Ian; Williams, Victoria; Snooks, Helen

doi:10.3399/bjgp.2021.0146

Journal article 662 views 41 downloads

Implementing emergency admission risk prediction in general practice: a qualitative study

Bridie Evans

, Jeremy Dale, Jan Davies, Hayley Hutchings

, Mark Kingston

, Alison Porter

, Ian Russell, Victoria Williams, Helen Snooks

British Journal of General Practice, Volume: 72, Issue: 715, Pages: e138 - e147

Swansea University Authors: Bridie Evans , Hayley Hutchings , Mark Kingston , Alison Porter , Ian Russell, Victoria Williams, Helen Snooks

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DOI (Published version): 10.3399/bjgp.2021.0146

Abstract

Using computer software in general practice to predict patient risk of emergency hospital admission has been widely advocated, despite limited evidence about effects. In a trial evaluating the introduction of a Predictive Risk Stratification Model (PRISM), statistically significant increases in emer...

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Published in:	British Journal of General Practice
ISSN:	0960-1643 1478-5242
Published:	Royal College of General Practitioners 2022
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa58918
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first_indexed	2021-12-06T13:37:41Z
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Use was inhibited by the model not being integrated with practice systems. Most participants doubted any large-scale impact, but did cite examples of the impact on individual patient care and reported increased awareness of patients at high risk of emergency admission to hospital. Qualitative results suggest mixed views of predictive risk stratification in general practice and raised awareness of highest-risk patients potentially affecting rates of unplanned hospital attendance and admissions. To inform future policy, decision makers need more information about implementation and effects of emergency admission risk stratification tools in primary and community settings. 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spelling	2022-10-27T11:44:24.4469860 v2 58918 2021-12-06 Implementing emergency admission risk prediction in general practice: a qualitative study 6098eddc58e31ac2f3e070cb839faa6a 0000-0003-0293-0888 Bridie Evans Bridie Evans true false bdf5d5f154d339dd92bb25884b7c3652 0000-0003-4155-1741 Hayley Hutchings Hayley Hutchings true false 3442763d6ff0467963e0792d2b5404fa 0000-0003-2242-4210 Mark Kingston Mark Kingston true false fcc861ec479a79f7fb9befb13192238b 0000-0002-3408-7007 Alison Porter Alison Porter true false 3cd60bd6beba30c90df45bf55b585649 Ian Russell Ian Russell true false e9bb438bfaaf693c0376c20c9e4529d2 Victoria Williams Victoria Williams true false ab23c5e0111b88427a155a1f495861d9 0000-0003-0173-8843 Helen Snooks Helen Snooks true false 2021-12-06 HDAT Using computer software in general practice to predict patient risk of emergency hospital admission has been widely advocated, despite limited evidence about effects. In a trial evaluating the introduction of a Predictive Risk Stratification Model (PRISM), statistically significant increases in emergency hospital admissions and use of other NHS services were reported without evidence of benefits to patients or the NHS. To explore GPs' and practice managers' experiences of incorporating PRISM into routine practice. Semi-structured interviews were carried out with GPs and practice managers in 18 practices in rural, urban, and suburban areas of south Wales. Interviews (30-90 min) were conducted at 3-6 months after gaining PRISM access, and ∼18 months later. Data were analysed thematically using Normalisation Process Theory. Responders ( = 22) reported that the decision to use PRISM was based mainly on fulfilling Quality and Outcomes Framework incentives. Most applied it to <0.5% practice patients over a few weeks. Using PRISM entailed undertaking technical tasks, sharing information in practice meetings, and making small-scale changes to patient care. Use was inhibited by the model not being integrated with practice systems. Most participants doubted any large-scale impact, but did cite examples of the impact on individual patient care and reported increased awareness of patients at high risk of emergency admission to hospital. Qualitative results suggest mixed views of predictive risk stratification in general practice and raised awareness of highest-risk patients potentially affecting rates of unplanned hospital attendance and admissions. To inform future policy, decision makers need more information about implementation and effects of emergency admission risk stratification tools in primary and community settings. [Abstract copyright: © The Authors.] Journal Article British Journal of General Practice 72 715 e138 e147 Royal College of General Practitioners 0960-1643 1478-5242 qualitative research; emergency service, hospital; general practice; health risk appraisal; health service evaluation; chronic disease 27 1 2022 2022-01-27 10.3399/bjgp.2021.0146 COLLEGE NANME Health Data Science COLLEGE CODE HDAT Swansea University National Institute for Health Research (NIHR) Health Services and Delivery Research Programme (grant number: 09/1801/1054). 2022-10-27T11:44:24.4469860 2021-12-06T13:33:25.6497675 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Bridie Evans 0000-0003-0293-0888 1 Jeremy Dale 2 Jan Davies 3 Hayley Hutchings 0000-0003-4155-1741 4 Mark Kingston 0000-0003-2242-4210 5 Alison Porter 0000-0002-3408-7007 6 Ian Russell 7 Victoria Williams 8 Helen Snooks 0000-0003-0173-8843 9 58918__22360__b2a6938333404c198bd445728091fd34.pdf 58918.pdf 2022-02-11T15:30:13.9615391 Output 130301 application/pdf Version of Record true ©The Authors. This article is Open Access: CC BY 4.0 licence true eng http://creativecommons.org/licences/by/4.0/
title	Implementing emergency admission risk prediction in general practice: a qualitative study
spellingShingle	Implementing emergency admission risk prediction in general practice: a qualitative study Bridie Evans Hayley Hutchings Mark Kingston Alison Porter Ian Russell Victoria Williams Helen Snooks
title_short	Implementing emergency admission risk prediction in general practice: a qualitative study
title_full	Implementing emergency admission risk prediction in general practice: a qualitative study
title_fullStr	Implementing emergency admission risk prediction in general practice: a qualitative study
title_full_unstemmed	Implementing emergency admission risk prediction in general practice: a qualitative study
title_sort	Implementing emergency admission risk prediction in general practice: a qualitative study
author_id_str_mv	6098eddc58e31ac2f3e070cb839faa6a bdf5d5f154d339dd92bb25884b7c3652 3442763d6ff0467963e0792d2b5404fa fcc861ec479a79f7fb9befb13192238b 3cd60bd6beba30c90df45bf55b585649 e9bb438bfaaf693c0376c20c9e4529d2 ab23c5e0111b88427a155a1f495861d9
author_id_fullname_str_mv	6098eddc58e31ac2f3e070cb839faa6a_*_Bridie Evans bdf5d5f154d339dd92bb25884b7c3652__Hayley Hutchings 3442763d6ff0467963e0792d2b5404fa__Mark Kingston fcc861ec479a79f7fb9befb13192238b__Alison Porter 3cd60bd6beba30c90df45bf55b585649__Ian Russell e9bb438bfaaf693c0376c20c9e4529d2__Victoria Williams ab23c5e0111b88427a155a1f495861d9_**_Helen Snooks
author	Bridie Evans Hayley Hutchings Mark Kingston Alison Porter Ian Russell Victoria Williams Helen Snooks
author2	Bridie Evans Jeremy Dale Jan Davies Hayley Hutchings Mark Kingston Alison Porter Ian Russell Victoria Williams Helen Snooks
format	Journal article
container_title	British Journal of General Practice
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publisher	Royal College of General Practitioners
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description	Using computer software in general practice to predict patient risk of emergency hospital admission has been widely advocated, despite limited evidence about effects. In a trial evaluating the introduction of a Predictive Risk Stratification Model (PRISM), statistically significant increases in emergency hospital admissions and use of other NHS services were reported without evidence of benefits to patients or the NHS. To explore GPs' and practice managers' experiences of incorporating PRISM into routine practice. Semi-structured interviews were carried out with GPs and practice managers in 18 practices in rural, urban, and suburban areas of south Wales. Interviews (30-90 min) were conducted at 3-6 months after gaining PRISM access, and ∼18 months later. Data were analysed thematically using Normalisation Process Theory. Responders ( = 22) reported that the decision to use PRISM was based mainly on fulfilling Quality and Outcomes Framework incentives. Most applied it to <0.5% practice patients over a few weeks. Using PRISM entailed undertaking technical tasks, sharing information in practice meetings, and making small-scale changes to patient care. Use was inhibited by the model not being integrated with practice systems. Most participants doubted any large-scale impact, but did cite examples of the impact on individual patient care and reported increased awareness of patients at high risk of emergency admission to hospital. Qualitative results suggest mixed views of predictive risk stratification in general practice and raised awareness of highest-risk patients potentially affecting rates of unplanned hospital attendance and admissions. To inform future policy, decision makers need more information about implementation and effects of emergency admission risk stratification tools in primary and community settings. [Abstract copyright: © The Authors.]
published_date	2022-01-27T04:15:49Z
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Implementing emergency admission risk prediction in general practice: a qualitative study

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