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The Value of Routinely Collected Data in Evaluating Home Assessment and Modification Interventions to Prevent Falls in Older People: Systematic Literature Review

Helen Daniels Orcid Logo, Joe Hollinghurst, Rich Fry Orcid Logo, Andrew Clegg, Sarah Hillcoat-Nallétamby, Silviya Nikolova, Sarah Rodgers Orcid Logo, Neil Williams, Ashley Akbari Orcid Logo

JMIR Aging, Volume: 4, Issue: 2, Start page: e24728

Swansea University Authors: Helen Daniels Orcid Logo, Joe Hollinghurst, Rich Fry Orcid Logo, Sarah Rodgers Orcid Logo, Ashley Akbari Orcid Logo

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DOI (Published version): 10.2196/24728

Abstract

Background: Falls in older people commonly occur at home. Home assessment and modification (HAM) interventions can be effective in reducing falls; however, there are some concerns over the validity of evaluation findings. Routinely collected data could improve the quality of HAM evaluations and stre...

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Published in: JMIR Aging
ISSN: 2561-7605
Published: JMIR Publications Inc. 2021
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fullrecord <?xml version="1.0"?><rfc1807><datestamp>2022-07-18T14:51:06.8101200</datestamp><bib-version>v2</bib-version><id>56585</id><entry>2021-03-28</entry><title>The Value of Routinely Collected Data in Evaluating Home Assessment and Modification Interventions to Prevent Falls in Older People: Systematic Literature Review</title><swanseaauthors><author><sid>a054902cb884be2476d0f097f0016294</sid><ORCID>0000-0001-8899-0333</ORCID><firstname>Helen</firstname><surname>Daniels</surname><name>Helen Daniels</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>d7c51b69270b644a11b904629fe56ab0</sid><firstname>Joe</firstname><surname>Hollinghurst</surname><name>Joe Hollinghurst</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>d499b898d447b62c81b2c122598870e0</sid><ORCID>0000-0002-7968-6679</ORCID><firstname>Rich</firstname><surname>Fry</surname><name>Rich Fry</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>e81e94dea293640575619d15baf34a35</sid><ORCID>0000-0002-4483-0845</ORCID><firstname>Sarah</firstname><surname>Rodgers</surname><name>Sarah Rodgers</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>aa1b025ec0243f708bb5eb0a93d6fb52</sid><ORCID>0000-0003-0814-0801</ORCID><firstname>Ashley</firstname><surname>Akbari</surname><name>Ashley Akbari</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2021-03-28</date><deptcode>HDAT</deptcode><abstract>Background: Falls in older people commonly occur at home. Home assessment and modification (HAM) interventions can be effective in reducing falls; however, there are some concerns over the validity of evaluation findings. Routinely collected data could improve the quality of HAM evaluations and strengthen their evidence base.Objective: The aim of this study is to conduct a systematic review of the evidence of the use of routinely collected data in the evaluations of HAM interventions.Methods: We searched the following databases from inception until January 31, 2020: PubMed, Ovid, CINAHL, OpenGrey, CENTRAL, LILACS, and Web of Knowledge. Eligible studies were those evaluating HAMs designed to reduce falls involving participants aged 60 years or more. We included study protocols and full reports. Bias was assessed using the Risk Of Bias In Non-Randomized Studies of Interventions (ROBINS-I) tool.Results: A total of 7 eligible studies were identified in 8 papers. Government organizations provided the majority of data across studies, with health care providers and third-sector organizations also providing data. Studies used a range of demographic, clinical and health, and administrative data. The purpose of using routinely collected data spanned recruiting and creating a sample, stratification, generating independent variables or covariates, and measuring key study-related outcomes. Nonhome-based modification interventions (eg, in nursing homes) using routinely collected data were not included in this study. We included two protocols, which meant that the results of those studies were not available. MeSH headings were excluded from the PubMed search because of a reduction in specificity. This means that some studies that met the inclusion criteria may not have been identified.Conclusions: Routine data can be used successfully in many aspects of HAM evaluations and can reduce biases and improve other important design considerations. However, the use of these data in these studies is currently not widespread. There are a number of governance barriers to be overcome to allow these types of linkage and to ensure that the use of routinely collected data in evaluations of HAM interventions is exploited to its full potential.</abstract><type>Journal Article</type><journal>JMIR Aging</journal><volume>4</volume><journalNumber>2</journalNumber><paginationStart>e24728</paginationStart><paginationEnd/><publisher>JMIR Publications Inc.</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>2561-7605</issnElectronic><keywords>falls; aged; routinely collected data; evaluation research; systematic review</keywords><publishedDay>23</publishedDay><publishedMonth>4</publishedMonth><publishedYear>2021</publishedYear><publishedDate>2021-04-23</publishedDate><doi>10.2196/24728</doi><url/><notes/><college>COLLEGE NANME</college><department>Health Data Science</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>HDAT</DepartmentCode><institution>Swansea University</institution><apcterm>Other</apcterm><funders>HCRW_SCF-18-1504/HCRW/HCRW_/United Kingdom SR was supported in part by the National Institute for Health Research Applied Research (NIHR) Collaboration North West Coast. AC was supported in part by the NIHR Collaboration Yorkshire and Humber and Health Data Research UK, an initiative funded by the UK Research and Innovation Councils, National Institute for Health Research and the UK devolved administrations, and leading medical research charities. The views expressed here are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care. The funder has no input in the study. This work was supported by Health and Care Research Wales (Project SCF-18-1504), the Dunhill Medical Trust (Project BEHA\41), and Health Data Research UK (HDR-9006), which received funding from HDR UK Ltd funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation, and the Wellcome Trust. This research was also supported by the Administrative Data Research (ADR) Wales program of work. The ADR Wales program of work is aligned with the priority themes identified in the Welsh Government&#x2019;s national strategy: Prosperity for All. ADR Wales brings together data science experts at Swansea University Medical School; staff from the Wales Institute of Social and Economic Research, Data and Methods at Cardiff University; and specialist teams within the Welsh Government to develop new evidence that supports Prosperity for All by using the SAIL Databank at Swansea University, to link and analyze anonymized data. ADR Wales is part of the Economic and Social Research Council (part of the UK Research and Innovation) funded by ADR UK (Grant ES/S007393/1). This work was also supported by the Wales School for Social Care Research, which was funded by Health and Care Research. The data used in this study are available from the SAIL Databank at Swansea University, Swansea, United Kingdom. All proposals to use SAIL data are subject to review by an independent IGRP. Before any data can be accessed, approval must be provided by the IGRP. The IGRP gives careful consideration to each project to ensure the proper and appropriate use of SAIL data. When access has been approved, it is gained through a privacy-protecting safe haven and remote access system, referred to as the SAIL Gateway. SAIL has established an application process to be followed by anyone who would like to access data via SAIL</funders><lastEdited>2022-07-18T14:51:06.8101200</lastEdited><Created>2021-03-28T12:00:00.7890483</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Medicine</level></path><authors><author><firstname>Helen</firstname><surname>Daniels</surname><orcid>0000-0001-8899-0333</orcid><order>1</order></author><author><firstname>Joe</firstname><surname>Hollinghurst</surname><order>2</order></author><author><firstname>Rich</firstname><surname>Fry</surname><orcid>0000-0002-7968-6679</orcid><order>3</order></author><author><firstname>Andrew</firstname><surname>Clegg</surname><order>4</order></author><author><firstname>Sarah</firstname><surname>Hillcoat-Nall&#xE9;tamby</surname><order>5</order></author><author><firstname>Silviya</firstname><surname>Nikolova</surname><order>6</order></author><author><firstname>Sarah</firstname><surname>Rodgers</surname><orcid>0000-0002-4483-0845</orcid><order>7</order></author><author><firstname>Neil</firstname><surname>Williams</surname><order>8</order></author><author><firstname>Ashley</firstname><surname>Akbari</surname><orcid>0000-0003-0814-0801</orcid><order>9</order></author></authors><documents><document><filename>56585__20167__b1d4dc54fc6e4c888a985e4b13da47e3.pdf</filename><originalFilename>56585.pdf</originalFilename><uploaded>2021-06-15T16:16:30.7480023</uploaded><type>Output</type><contentLength>531839</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>This is an open-access article distributed under the terms of the Creative Commons Attribution License</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>https://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling 2022-07-18T14:51:06.8101200 v2 56585 2021-03-28 The Value of Routinely Collected Data in Evaluating Home Assessment and Modification Interventions to Prevent Falls in Older People: Systematic Literature Review a054902cb884be2476d0f097f0016294 0000-0001-8899-0333 Helen Daniels Helen Daniels true false d7c51b69270b644a11b904629fe56ab0 Joe Hollinghurst Joe Hollinghurst true false d499b898d447b62c81b2c122598870e0 0000-0002-7968-6679 Rich Fry Rich Fry true false e81e94dea293640575619d15baf34a35 0000-0002-4483-0845 Sarah Rodgers Sarah Rodgers true false aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false 2021-03-28 HDAT Background: Falls in older people commonly occur at home. Home assessment and modification (HAM) interventions can be effective in reducing falls; however, there are some concerns over the validity of evaluation findings. Routinely collected data could improve the quality of HAM evaluations and strengthen their evidence base.Objective: The aim of this study is to conduct a systematic review of the evidence of the use of routinely collected data in the evaluations of HAM interventions.Methods: We searched the following databases from inception until January 31, 2020: PubMed, Ovid, CINAHL, OpenGrey, CENTRAL, LILACS, and Web of Knowledge. Eligible studies were those evaluating HAMs designed to reduce falls involving participants aged 60 years or more. We included study protocols and full reports. Bias was assessed using the Risk Of Bias In Non-Randomized Studies of Interventions (ROBINS-I) tool.Results: A total of 7 eligible studies were identified in 8 papers. Government organizations provided the majority of data across studies, with health care providers and third-sector organizations also providing data. Studies used a range of demographic, clinical and health, and administrative data. The purpose of using routinely collected data spanned recruiting and creating a sample, stratification, generating independent variables or covariates, and measuring key study-related outcomes. Nonhome-based modification interventions (eg, in nursing homes) using routinely collected data were not included in this study. We included two protocols, which meant that the results of those studies were not available. MeSH headings were excluded from the PubMed search because of a reduction in specificity. This means that some studies that met the inclusion criteria may not have been identified.Conclusions: Routine data can be used successfully in many aspects of HAM evaluations and can reduce biases and improve other important design considerations. However, the use of these data in these studies is currently not widespread. There are a number of governance barriers to be overcome to allow these types of linkage and to ensure that the use of routinely collected data in evaluations of HAM interventions is exploited to its full potential. Journal Article JMIR Aging 4 2 e24728 JMIR Publications Inc. 2561-7605 falls; aged; routinely collected data; evaluation research; systematic review 23 4 2021 2021-04-23 10.2196/24728 COLLEGE NANME Health Data Science COLLEGE CODE HDAT Swansea University Other HCRW_SCF-18-1504/HCRW/HCRW_/United Kingdom SR was supported in part by the National Institute for Health Research Applied Research (NIHR) Collaboration North West Coast. AC was supported in part by the NIHR Collaboration Yorkshire and Humber and Health Data Research UK, an initiative funded by the UK Research and Innovation Councils, National Institute for Health Research and the UK devolved administrations, and leading medical research charities. The views expressed here are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care. The funder has no input in the study. This work was supported by Health and Care Research Wales (Project SCF-18-1504), the Dunhill Medical Trust (Project BEHA\41), and Health Data Research UK (HDR-9006), which received funding from HDR UK Ltd funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation, and the Wellcome Trust. This research was also supported by the Administrative Data Research (ADR) Wales program of work. The ADR Wales program of work is aligned with the priority themes identified in the Welsh Government’s national strategy: Prosperity for All. ADR Wales brings together data science experts at Swansea University Medical School; staff from the Wales Institute of Social and Economic Research, Data and Methods at Cardiff University; and specialist teams within the Welsh Government to develop new evidence that supports Prosperity for All by using the SAIL Databank at Swansea University, to link and analyze anonymized data. ADR Wales is part of the Economic and Social Research Council (part of the UK Research and Innovation) funded by ADR UK (Grant ES/S007393/1). This work was also supported by the Wales School for Social Care Research, which was funded by Health and Care Research. The data used in this study are available from the SAIL Databank at Swansea University, Swansea, United Kingdom. All proposals to use SAIL data are subject to review by an independent IGRP. Before any data can be accessed, approval must be provided by the IGRP. The IGRP gives careful consideration to each project to ensure the proper and appropriate use of SAIL data. When access has been approved, it is gained through a privacy-protecting safe haven and remote access system, referred to as the SAIL Gateway. SAIL has established an application process to be followed by anyone who would like to access data via SAIL 2022-07-18T14:51:06.8101200 2021-03-28T12:00:00.7890483 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Helen Daniels 0000-0001-8899-0333 1 Joe Hollinghurst 2 Rich Fry 0000-0002-7968-6679 3 Andrew Clegg 4 Sarah Hillcoat-Nallétamby 5 Silviya Nikolova 6 Sarah Rodgers 0000-0002-4483-0845 7 Neil Williams 8 Ashley Akbari 0000-0003-0814-0801 9 56585__20167__b1d4dc54fc6e4c888a985e4b13da47e3.pdf 56585.pdf 2021-06-15T16:16:30.7480023 Output 531839 application/pdf Version of Record true This is an open-access article distributed under the terms of the Creative Commons Attribution License true eng https://creativecommons.org/licenses/by/4.0/
title The Value of Routinely Collected Data in Evaluating Home Assessment and Modification Interventions to Prevent Falls in Older People: Systematic Literature Review
spellingShingle The Value of Routinely Collected Data in Evaluating Home Assessment and Modification Interventions to Prevent Falls in Older People: Systematic Literature Review
Helen Daniels
Joe Hollinghurst
Rich Fry
Sarah Rodgers
Ashley Akbari
title_short The Value of Routinely Collected Data in Evaluating Home Assessment and Modification Interventions to Prevent Falls in Older People: Systematic Literature Review
title_full The Value of Routinely Collected Data in Evaluating Home Assessment and Modification Interventions to Prevent Falls in Older People: Systematic Literature Review
title_fullStr The Value of Routinely Collected Data in Evaluating Home Assessment and Modification Interventions to Prevent Falls in Older People: Systematic Literature Review
title_full_unstemmed The Value of Routinely Collected Data in Evaluating Home Assessment and Modification Interventions to Prevent Falls in Older People: Systematic Literature Review
title_sort The Value of Routinely Collected Data in Evaluating Home Assessment and Modification Interventions to Prevent Falls in Older People: Systematic Literature Review
author_id_str_mv a054902cb884be2476d0f097f0016294
d7c51b69270b644a11b904629fe56ab0
d499b898d447b62c81b2c122598870e0
e81e94dea293640575619d15baf34a35
aa1b025ec0243f708bb5eb0a93d6fb52
author_id_fullname_str_mv a054902cb884be2476d0f097f0016294_***_Helen Daniels
d7c51b69270b644a11b904629fe56ab0_***_Joe Hollinghurst
d499b898d447b62c81b2c122598870e0_***_Rich Fry
e81e94dea293640575619d15baf34a35_***_Sarah Rodgers
aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari
author Helen Daniels
Joe Hollinghurst
Rich Fry
Sarah Rodgers
Ashley Akbari
author2 Helen Daniels
Joe Hollinghurst
Rich Fry
Andrew Clegg
Sarah Hillcoat-Nallétamby
Silviya Nikolova
Sarah Rodgers
Neil Williams
Ashley Akbari
format Journal article
container_title JMIR Aging
container_volume 4
container_issue 2
container_start_page e24728
publishDate 2021
institution Swansea University
issn 2561-7605
doi_str_mv 10.2196/24728
publisher JMIR Publications Inc.
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 - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
document_store_str 1
active_str 0
description Background: Falls in older people commonly occur at home. Home assessment and modification (HAM) interventions can be effective in reducing falls; however, there are some concerns over the validity of evaluation findings. Routinely collected data could improve the quality of HAM evaluations and strengthen their evidence base.Objective: The aim of this study is to conduct a systematic review of the evidence of the use of routinely collected data in the evaluations of HAM interventions.Methods: We searched the following databases from inception until January 31, 2020: PubMed, Ovid, CINAHL, OpenGrey, CENTRAL, LILACS, and Web of Knowledge. Eligible studies were those evaluating HAMs designed to reduce falls involving participants aged 60 years or more. We included study protocols and full reports. Bias was assessed using the Risk Of Bias In Non-Randomized Studies of Interventions (ROBINS-I) tool.Results: A total of 7 eligible studies were identified in 8 papers. Government organizations provided the majority of data across studies, with health care providers and third-sector organizations also providing data. Studies used a range of demographic, clinical and health, and administrative data. The purpose of using routinely collected data spanned recruiting and creating a sample, stratification, generating independent variables or covariates, and measuring key study-related outcomes. Nonhome-based modification interventions (eg, in nursing homes) using routinely collected data were not included in this study. We included two protocols, which meant that the results of those studies were not available. MeSH headings were excluded from the PubMed search because of a reduction in specificity. This means that some studies that met the inclusion criteria may not have been identified.Conclusions: Routine data can be used successfully in many aspects of HAM evaluations and can reduce biases and improve other important design considerations. However, the use of these data in these studies is currently not widespread. There are a number of governance barriers to be overcome to allow these types of linkage and to ensure that the use of routinely collected data in evaluations of HAM interventions is exploited to its full potential.
published_date 2021-04-23T04:11:39Z
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