Emergency admission predictive risk stratification models: assessment of implementation consequences (PRISMATIC 2): protocol for a mixed methods study.

Kingston, Mark; Snooks, Helen; Watkins, Alan; Burton, Christopher; Dale, Jeremy; Davies, Jan; Dearden, Alex; Evans, Bridie; Gomes, Barbara; Jones, Jenna; Kumar, Rashmi; Porter, Alison; Sewell, Berni; Wallace, Emma

doi:10.3399/BJGPO.2024.0182

Journal article 6 views

Emergency admission predictive risk stratification models: assessment of implementation consequences (PRISMATIC 2): protocol for a mixed methods study.

Mark Kingston

, Helen Snooks

, Alan Watkins

, Christopher Burton, Jeremy Dale, Jan Davies, Alex Dearden, Bridie Evans

, Barbara Gomes, Jenna Jones, Rashmi Kumar, Alison Porter

, Berni Sewell, Emma Wallace

BJGP Open, Start page: BJGPO.2024.0182

Swansea University Authors: Mark Kingston , Helen Snooks , Alan Watkins , Alex Dearden, Bridie Evans , Barbara Gomes, Jenna Jones, Alison Porter , Berni Sewell

PDF | Accepted Manuscript

© 2024 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License (CC BY 4.0).
Download (411.11KB)

Check full text

DOI (Published version): 10.3399/BJGPO.2024.0182

Abstract

Emergency admissions are costly, increasingly numerous, and associated with adverse patient outcomes. Policy responses have included the widespread introduction of emergency admission risk stratification (EARS) tools in primary care. These tools generate scores that predict patients' risk of em...

Full description

Published in:	BJGP Open
ISSN:	2398-3795
Published:	2024
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa67870
Tags:	Add Tag No Tags, Be the first to tag this record!

first_indexed	2024-10-01T13:34:54Z
last_indexed	2024-10-01T13:34:54Z
id	cronfa67870
recordtype	SURis
fullrecord	<?xml version="1.0" encoding="utf-8"?><rfc1807 xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"><bib-version>v2</bib-version><id>67870</id><entry>2024-10-01</entry><title>Emergency admission predictive risk stratification models: assessment of implementation consequences (PRISMATIC 2): protocol for a mixed methods study.</title><swanseaauthors><author><sid>3442763d6ff0467963e0792d2b5404fa</sid><ORCID>0000-0003-2242-4210</ORCID><firstname>Mark</firstname><surname>Kingston</surname><name>Mark Kingston</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>ab23c5e0111b88427a155a1f495861d9</sid><ORCID>0000-0003-0173-8843</ORCID><firstname>Helen</firstname><surname>Snooks</surname><name>Helen Snooks</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>81fc05c9333d9df41b041157437bcc2f</sid><ORCID>0000-0003-3804-1943</ORCID><firstname>Alan</firstname><surname>Watkins</surname><name>Alan Watkins</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>4386276ca8a14b9b73fbcb9e69ea1527</sid><firstname>Alex</firstname><surname>Dearden</surname><name>Alex Dearden</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>6098eddc58e31ac2f3e070cb839faa6a</sid><ORCID>0000-0003-0293-0888</ORCID><firstname>Bridie</firstname><surname>Evans</surname><name>Bridie Evans</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>1a8104f9603508df48d75cf75395c93f</sid><firstname>Barbara</firstname><surname>Gomes</surname><name>Barbara Gomes</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>e662b6c5aba239a9cd0f115d16df0a82</sid><ORCID/><firstname>Jenna</firstname><surname>Jones</surname><name>Jenna Jones</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>fcc861ec479a79f7fb9befb13192238b</sid><ORCID>0000-0002-3408-7007</ORCID><firstname>Alison</firstname><surname>Porter</surname><name>Alison Porter</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>f6a4af2cfa4275d2a8ebba292fa14421</sid><firstname>Berni</firstname><surname>Sewell</surname><name>Berni Sewell</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2024-10-01</date><deptcode>MEDS</deptcode><abstract>Emergency admissions are costly, increasingly numerous, and associated with adverse patient outcomes. Policy responses have included the widespread introduction of emergency admission risk stratification (EARS) tools in primary care. These tools generate scores that predict patients' risk of emergency hospital admission and can be used to support targeted approaches to improve care and reduce admissions. However, the impact of EARS is poorly understood and there may be unintended consequences. To assess effects, mechanisms, costs, and patient and healthcare professionals' views related to the introduction of EARS tools in England. Quasi-experimental mixed methods design using anonymised routine data and qualitative methods. We will apply multiple interrupted time series analysis to data, aggregated at former Clinical Commissioning Group level, to look at changes in emergency admission and other healthcare use following EARS introduction across England. We will investigate GP decision-making at practice level using linked general practice and secondary care data to compare case-mix, demographics, indicators of condition severity and frailty associated with emergency admissions before and after EARS introduction. We will undertake interviews ( ~48) with GPs and healthcare staff to understand how patient care may have changed. We will conduct focus groups ( =2) and interviews ( ~16) with patients to explore how they perceive that communication of individual risk scores might affect their experiences and health seeking behaviours. Findings will provide policymakers, healthcare professionals, and patients, with a better understanding of the effects, costs and stakeholder perspectives related to the introduction of EARS tools. [Abstract copyright: Copyright © 2024, The Authors.]</abstract><type>Journal Article</type><journal>BJGP Open</journal><volume/><journalNumber/><paginationStart>BJGPO.2024.0182</paginationStart><paginationEnd/><publisher/><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>2398-3795</issnElectronic><keywords>Primary health care, health services research, emergency health services, risk stratification, clinical prediction rule, chronic disease</keywords><publishedDay>16</publishedDay><publishedMonth>9</publishedMonth><publishedYear>2024</publishedYear><publishedDate>2024-09-16</publishedDate><doi>10.3399/BJGPO.2024.0182</doi><url/><notes/><college>COLLEGE NANME</college><department>Medical School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MEDS</DepartmentCode><institution>Swansea University</institution><apcterm/><funders>This study is funded by the NIHR HS&DR programme, project number 150717. The views expressed are those of the author and not necessarily those of the NIHR or the Department of Health and Social Care. The funding application was supported by infrastructure funding from PRIME Centre Wales http://www.primecentre.wales/.</funders><projectreference/><lastEdited>2024-10-01T14:59:41.2914245</lastEdited><Created>2024-10-01T13:56:33.3847080</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Health Data Science</level></path><authors><author><firstname>Mark</firstname><surname>Kingston</surname><orcid>0000-0003-2242-4210</orcid><order>1</order></author><author><firstname>Helen</firstname><surname>Snooks</surname><orcid>0000-0003-0173-8843</orcid><order>2</order></author><author><firstname>Alan</firstname><surname>Watkins</surname><orcid>0000-0003-3804-1943</orcid><order>3</order></author><author><firstname>Christopher</firstname><surname>Burton</surname><order>4</order></author><author><firstname>Jeremy</firstname><surname>Dale</surname><order>5</order></author><author><firstname>Jan</firstname><surname>Davies</surname><order>6</order></author><author><firstname>Alex</firstname><surname>Dearden</surname><order>7</order></author><author><firstname>Bridie</firstname><surname>Evans</surname><orcid>0000-0003-0293-0888</orcid><order>8</order></author><author><firstname>Barbara</firstname><surname>Gomes</surname><order>9</order></author><author><firstname>Jenna</firstname><surname>Jones</surname><orcid/><order>10</order></author><author><firstname>Rashmi</firstname><surname>Kumar</surname><order>11</order></author><author><firstname>Alison</firstname><surname>Porter</surname><orcid>0000-0002-3408-7007</orcid><order>12</order></author><author><firstname>Berni</firstname><surname>Sewell</surname><order>13</order></author><author><firstname>Emma</firstname><surname>Wallace</surname><orcid>0000-0002-9315-2956</orcid><order>14</order></author></authors><documents><document><filename>67870__31494__4ee72cfb6b404890880e2263f7b6a586.pdf</filename><originalFilename>67870.AAM.pdf</originalFilename><uploaded>2024-10-01T14:20:57.8897840</uploaded><type>Output</type><contentLength>420974</contentLength><contentType>application/pdf</contentType><version>Accepted Manuscript</version><cronfaStatus>true</cronfaStatus><documentNotes>© 2024 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License (CC BY 4.0).</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>http://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling	v2 67870 2024-10-01 Emergency admission predictive risk stratification models: assessment of implementation consequences (PRISMATIC 2): protocol for a mixed methods study. 3442763d6ff0467963e0792d2b5404fa 0000-0003-2242-4210 Mark Kingston Mark Kingston true false ab23c5e0111b88427a155a1f495861d9 0000-0003-0173-8843 Helen Snooks Helen Snooks true false 81fc05c9333d9df41b041157437bcc2f 0000-0003-3804-1943 Alan Watkins Alan Watkins true false 4386276ca8a14b9b73fbcb9e69ea1527 Alex Dearden Alex Dearden true false 6098eddc58e31ac2f3e070cb839faa6a 0000-0003-0293-0888 Bridie Evans Bridie Evans true false 1a8104f9603508df48d75cf75395c93f Barbara Gomes Barbara Gomes true false e662b6c5aba239a9cd0f115d16df0a82 Jenna Jones Jenna Jones true false fcc861ec479a79f7fb9befb13192238b 0000-0002-3408-7007 Alison Porter Alison Porter true false f6a4af2cfa4275d2a8ebba292fa14421 Berni Sewell Berni Sewell true false 2024-10-01 MEDS Emergency admissions are costly, increasingly numerous, and associated with adverse patient outcomes. Policy responses have included the widespread introduction of emergency admission risk stratification (EARS) tools in primary care. These tools generate scores that predict patients' risk of emergency hospital admission and can be used to support targeted approaches to improve care and reduce admissions. However, the impact of EARS is poorly understood and there may be unintended consequences. To assess effects, mechanisms, costs, and patient and healthcare professionals' views related to the introduction of EARS tools in England. Quasi-experimental mixed methods design using anonymised routine data and qualitative methods. We will apply multiple interrupted time series analysis to data, aggregated at former Clinical Commissioning Group level, to look at changes in emergency admission and other healthcare use following EARS introduction across England. We will investigate GP decision-making at practice level using linked general practice and secondary care data to compare case-mix, demographics, indicators of condition severity and frailty associated with emergency admissions before and after EARS introduction. We will undertake interviews ( ~48) with GPs and healthcare staff to understand how patient care may have changed. We will conduct focus groups ( =2) and interviews ( ~16) with patients to explore how they perceive that communication of individual risk scores might affect their experiences and health seeking behaviours. Findings will provide policymakers, healthcare professionals, and patients, with a better understanding of the effects, costs and stakeholder perspectives related to the introduction of EARS tools. [Abstract copyright: Copyright © 2024, The Authors.] Journal Article BJGP Open BJGPO.2024.0182 2398-3795 Primary health care, health services research, emergency health services, risk stratification, clinical prediction rule, chronic disease 16 9 2024 2024-09-16 10.3399/BJGPO.2024.0182 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University This study is funded by the NIHR HS&DR programme, project number 150717. The views expressed are those of the author and not necessarily those of the NIHR or the Department of Health and Social Care. The funding application was supported by infrastructure funding from PRIME Centre Wales http://www.primecentre.wales/. 2024-10-01T14:59:41.2914245 2024-10-01T13:56:33.3847080 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Health Data Science Mark Kingston 0000-0003-2242-4210 1 Helen Snooks 0000-0003-0173-8843 2 Alan Watkins 0000-0003-3804-1943 3 Christopher Burton 4 Jeremy Dale 5 Jan Davies 6 Alex Dearden 7 Bridie Evans 0000-0003-0293-0888 8 Barbara Gomes 9 Jenna Jones 10 Rashmi Kumar 11 Alison Porter 0000-0002-3408-7007 12 Berni Sewell 13 Emma Wallace 0000-0002-9315-2956 14 67870__31494__4ee72cfb6b404890880e2263f7b6a586.pdf 67870.AAM.pdf 2024-10-01T14:20:57.8897840 Output 420974 application/pdf Accepted Manuscript true © 2024 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License (CC BY 4.0). true eng http://creativecommons.org/licenses/by/4.0/
title	Emergency admission predictive risk stratification models: assessment of implementation consequences (PRISMATIC 2): protocol for a mixed methods study.
spellingShingle	Emergency admission predictive risk stratification models: assessment of implementation consequences (PRISMATIC 2): protocol for a mixed methods study. Mark Kingston Helen Snooks Alan Watkins Alex Dearden Bridie Evans Barbara Gomes Jenna Jones Alison Porter Berni Sewell
title_short	Emergency admission predictive risk stratification models: assessment of implementation consequences (PRISMATIC 2): protocol for a mixed methods study.
title_full	Emergency admission predictive risk stratification models: assessment of implementation consequences (PRISMATIC 2): protocol for a mixed methods study.
title_fullStr	Emergency admission predictive risk stratification models: assessment of implementation consequences (PRISMATIC 2): protocol for a mixed methods study.
title_full_unstemmed	Emergency admission predictive risk stratification models: assessment of implementation consequences (PRISMATIC 2): protocol for a mixed methods study.
title_sort	Emergency admission predictive risk stratification models: assessment of implementation consequences (PRISMATIC 2): protocol for a mixed methods study.
author_id_str_mv	3442763d6ff0467963e0792d2b5404fa ab23c5e0111b88427a155a1f495861d9 81fc05c9333d9df41b041157437bcc2f 4386276ca8a14b9b73fbcb9e69ea1527 6098eddc58e31ac2f3e070cb839faa6a 1a8104f9603508df48d75cf75395c93f e662b6c5aba239a9cd0f115d16df0a82 fcc861ec479a79f7fb9befb13192238b f6a4af2cfa4275d2a8ebba292fa14421
author_id_fullname_str_mv	3442763d6ff0467963e0792d2b5404fa_*_Mark Kingston ab23c5e0111b88427a155a1f495861d9__Helen Snooks 81fc05c9333d9df41b041157437bcc2f__Alan Watkins 4386276ca8a14b9b73fbcb9e69ea1527__Alex Dearden 6098eddc58e31ac2f3e070cb839faa6a__Bridie Evans 1a8104f9603508df48d75cf75395c93f__Barbara Gomes e662b6c5aba239a9cd0f115d16df0a82__Jenna Jones fcc861ec479a79f7fb9befb13192238b__Alison Porter f6a4af2cfa4275d2a8ebba292fa14421_**_Berni Sewell
author	Mark Kingston Helen Snooks Alan Watkins Alex Dearden Bridie Evans Barbara Gomes Jenna Jones Alison Porter Berni Sewell
author2	Mark Kingston Helen Snooks Alan Watkins Christopher Burton Jeremy Dale Jan Davies Alex Dearden Bridie Evans Barbara Gomes Jenna Jones Rashmi Kumar Alison Porter Berni Sewell Emma Wallace
format	Journal article
container_title	BJGP Open
container_start_page	BJGPO.2024.0182
publishDate	2024
institution	Swansea University
issn	2398-3795
doi_str_mv	10.3399/BJGPO.2024.0182
college_str	Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id	facultyofmedicinehealthandlifesciences
hierarchy_top_title	Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id	facultyofmedicinehealthandlifesciences
hierarchy_parent_title	Faculty of Medicine, Health and Life Sciences
department_str	Swansea University Medical School - Health Data Science{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Health Data Science
document_store_str	1
active_str	0
description	Emergency admissions are costly, increasingly numerous, and associated with adverse patient outcomes. Policy responses have included the widespread introduction of emergency admission risk stratification (EARS) tools in primary care. These tools generate scores that predict patients' risk of emergency hospital admission and can be used to support targeted approaches to improve care and reduce admissions. However, the impact of EARS is poorly understood and there may be unintended consequences. To assess effects, mechanisms, costs, and patient and healthcare professionals' views related to the introduction of EARS tools in England. Quasi-experimental mixed methods design using anonymised routine data and qualitative methods. We will apply multiple interrupted time series analysis to data, aggregated at former Clinical Commissioning Group level, to look at changes in emergency admission and other healthcare use following EARS introduction across England. We will investigate GP decision-making at practice level using linked general practice and secondary care data to compare case-mix, demographics, indicators of condition severity and frailty associated with emergency admissions before and after EARS introduction. We will undertake interviews ( ~48) with GPs and healthcare staff to understand how patient care may have changed. We will conduct focus groups ( =2) and interviews ( ~16) with patients to explore how they perceive that communication of individual risk scores might affect their experiences and health seeking behaviours. Findings will provide policymakers, healthcare professionals, and patients, with a better understanding of the effects, costs and stakeholder perspectives related to the introduction of EARS tools. [Abstract copyright: Copyright © 2024, The Authors.]
published_date	2024-09-16T14:59:40Z
_version_	1811720364417351680
score	11.031067

Emergency admission predictive risk stratification models: assessment of implementation consequences (PRISMATIC 2): protocol for a mixed methods study.

Similar Items