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Measuring multimorbidity in research: Delphi consensus study
BMJ Medicine, Volume: 1, Issue: 1, Start page: e000247
Swansea University Authors:
Ashley Akbari , Ronan Lyons
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DOI (Published version): 10.1136/bmjmed-2022-000247
Abstract
Objective To develop international consensus on the definition and measurement of multimorbidity in research.Design Delphi consensus study.Setting International consensus; data collected in three online rounds from participants between 30 November 2020 and 18 May 2021.Participants Professionals inte...
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<?xml version="1.0"?><rfc1807><datestamp>2022-09-09T16:12:35.8209642</datestamp><bib-version>v2</bib-version><id>60877</id><entry>2022-08-23</entry><title>Measuring multimorbidity in research: Delphi consensus study</title><swanseaauthors><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><author><sid>83efcf2a9dfcf8b55586999d3d152ac6</sid><ORCID>0000-0001-5225-000X</ORCID><firstname>Ronan</firstname><surname>Lyons</surname><name>Ronan Lyons</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2022-08-23</date><deptcode>HDAT</deptcode><abstract>Objective To develop international consensus on the definition and measurement of multimorbidity in research.Design Delphi consensus study.Setting International consensus; data collected in three online rounds from participants between 30 November 2020 and 18 May 2021.Participants Professionals interested in multimorbidity and people with long term conditions were recruited to professional and public panels.Results 150 professional and 25 public participants completed the first survey round. Response rates for rounds 2/3 were 83%/92% for professionals and 88%/93% in the public panel, respectively. Across both panels, the consensus was that multimorbidity should be defined as two or more long term conditions. Complex multimorbidity was perceived to be a useful concept, but the panels were unable to agree on how to define it. Both panels agreed that conditions should be included in a multimorbidity measure if they were one or more of the following: currently active; permanent in their effects; requiring current treatment, care, or therapy; requiring surveillance; or relapsing-remitting conditions requiring ongoing care. Consensus was reached for 24 conditions to always include in multimorbidity measures, and 35 conditions to usually include unless a good reason not to existed. Simple counts were preferred for estimating prevalence and examining clustering or trajectories, and weighted measures were preferred for risk adjustment and outcome prediction.Conclusions Previous multimorbidity research is limited by inconsistent definitions and approaches to measuring multimorbidity. This Delphi study identifies professional and public panel consensus guidance to facilitate consistency of definition and measurement, and to improve study comparability and reproducibility.</abstract><type>Journal Article</type><journal>BMJ Medicine</journal><volume>1</volume><journalNumber>1</journalNumber><paginationStart>e000247</paginationStart><paginationEnd/><publisher>BMJ</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>2754-0413</issnElectronic><keywords/><publishedDay>27</publishedDay><publishedMonth>7</publishedMonth><publishedYear>2022</publishedYear><publishedDate>2022-07-27</publishedDate><doi>10.1136/bmjmed-2022-000247</doi><url/><notes>Data availability statement:Data are available upon reasonable request</notes><college>COLLEGE NANME</college><department>Health Data Science</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>HDAT</DepartmentCode><institution>Swansea University</institution><apcterm/><funders>This study was funded by Health Data Research UK. . SS is part funded by the NIHR Applied Research Collaboration West Midlands, NIHR Health Protection Research Unit Gastrointestinal Infections, and NIHR HPRU Genomics and Enabling data.</funders><projectreference/><lastEdited>2022-09-09T16:12:35.8209642</lastEdited><Created>2022-08-23T18:59:14.2062850</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>Iris S S</firstname><surname>Ho</surname><order>1</order></author><author><firstname>Amaya</firstname><surname>Azcoaga-Lorenzo</surname><orcid>0000-0003-3307-878x</orcid><order>2</order></author><author><firstname>Ashley</firstname><surname>Akbari</surname><orcid>0000-0003-0814-0801</orcid><order>3</order></author><author><firstname>Jim</firstname><surname>Davies</surname><order>4</order></author><author><firstname>Kamlesh</firstname><surname>Khunti</surname><orcid>0000-0003-2343-7099</orcid><order>5</order></author><author><firstname>Umesh T</firstname><surname>Kadam</surname><order>6</order></author><author><firstname>Ronan</firstname><surname>Lyons</surname><orcid>0000-0001-5225-000X</orcid><order>7</order></author><author><firstname>Colin</firstname><surname>McCowan</surname><order>8</order></author><author><firstname>Stewart W</firstname><surname>Mercer</surname><orcid>0000-0002-1703-3664</orcid><order>9</order></author><author><firstname>Krishnarajah</firstname><surname>Nirantharakumar</surname><order>10</order></author><author><firstname>Sophie</firstname><surname>Staniszewska</surname><order>11</order></author><author><firstname>Bruce</firstname><surname>Guthrie</surname><orcid>0000-0003-4191-4880</orcid><order>12</order></author></authors><documents><document><filename>60877__25107__3700915cf20e418aae714e5639722449.pdf</filename><originalFilename>60877_VoR.pdf</originalFilename><uploaded>2022-09-09T16:11:09.7189687</uploaded><type>Output</type><contentLength>1745901</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>https://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807> |
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2022-09-09T16:12:35.8209642 v2 60877 2022-08-23 Measuring multimorbidity in research: Delphi consensus study aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false 83efcf2a9dfcf8b55586999d3d152ac6 0000-0001-5225-000X Ronan Lyons Ronan Lyons true false 2022-08-23 HDAT Objective To develop international consensus on the definition and measurement of multimorbidity in research.Design Delphi consensus study.Setting International consensus; data collected in three online rounds from participants between 30 November 2020 and 18 May 2021.Participants Professionals interested in multimorbidity and people with long term conditions were recruited to professional and public panels.Results 150 professional and 25 public participants completed the first survey round. Response rates for rounds 2/3 were 83%/92% for professionals and 88%/93% in the public panel, respectively. Across both panels, the consensus was that multimorbidity should be defined as two or more long term conditions. Complex multimorbidity was perceived to be a useful concept, but the panels were unable to agree on how to define it. Both panels agreed that conditions should be included in a multimorbidity measure if they were one or more of the following: currently active; permanent in their effects; requiring current treatment, care, or therapy; requiring surveillance; or relapsing-remitting conditions requiring ongoing care. Consensus was reached for 24 conditions to always include in multimorbidity measures, and 35 conditions to usually include unless a good reason not to existed. Simple counts were preferred for estimating prevalence and examining clustering or trajectories, and weighted measures were preferred for risk adjustment and outcome prediction.Conclusions Previous multimorbidity research is limited by inconsistent definitions and approaches to measuring multimorbidity. This Delphi study identifies professional and public panel consensus guidance to facilitate consistency of definition and measurement, and to improve study comparability and reproducibility. Journal Article BMJ Medicine 1 1 e000247 BMJ 2754-0413 27 7 2022 2022-07-27 10.1136/bmjmed-2022-000247 Data availability statement:Data are available upon reasonable request COLLEGE NANME Health Data Science COLLEGE CODE HDAT Swansea University This study was funded by Health Data Research UK. . SS is part funded by the NIHR Applied Research Collaboration West Midlands, NIHR Health Protection Research Unit Gastrointestinal Infections, and NIHR HPRU Genomics and Enabling data. 2022-09-09T16:12:35.8209642 2022-08-23T18:59:14.2062850 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Iris S S Ho 1 Amaya Azcoaga-Lorenzo 0000-0003-3307-878x 2 Ashley Akbari 0000-0003-0814-0801 3 Jim Davies 4 Kamlesh Khunti 0000-0003-2343-7099 5 Umesh T Kadam 6 Ronan Lyons 0000-0001-5225-000X 7 Colin McCowan 8 Stewart W Mercer 0000-0002-1703-3664 9 Krishnarajah Nirantharakumar 10 Sophie Staniszewska 11 Bruce Guthrie 0000-0003-4191-4880 12 60877__25107__3700915cf20e418aae714e5639722449.pdf 60877_VoR.pdf 2022-09-09T16:11:09.7189687 Output 1745901 application/pdf Version of Record true This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license true eng https://creativecommons.org/licenses/by/4.0/ |
title |
Measuring multimorbidity in research: Delphi consensus study |
spellingShingle |
Measuring multimorbidity in research: Delphi consensus study Ashley Akbari Ronan Lyons |
title_short |
Measuring multimorbidity in research: Delphi consensus study |
title_full |
Measuring multimorbidity in research: Delphi consensus study |
title_fullStr |
Measuring multimorbidity in research: Delphi consensus study |
title_full_unstemmed |
Measuring multimorbidity in research: Delphi consensus study |
title_sort |
Measuring multimorbidity in research: Delphi consensus study |
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aa1b025ec0243f708bb5eb0a93d6fb52 83efcf2a9dfcf8b55586999d3d152ac6 |
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aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari 83efcf2a9dfcf8b55586999d3d152ac6_***_Ronan Lyons |
author |
Ashley Akbari Ronan Lyons |
author2 |
Iris S S Ho Amaya Azcoaga-Lorenzo Ashley Akbari Jim Davies Kamlesh Khunti Umesh T Kadam Ronan Lyons Colin McCowan Stewart W Mercer Krishnarajah Nirantharakumar Sophie Staniszewska Bruce Guthrie |
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BMJ Medicine |
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e000247 |
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Swansea University |
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2754-0413 |
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10.1136/bmjmed-2022-000247 |
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BMJ |
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Faculty of Medicine, Health and Life Sciences |
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Faculty of Medicine, Health and Life Sciences |
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Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine |
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description |
Objective To develop international consensus on the definition and measurement of multimorbidity in research.Design Delphi consensus study.Setting International consensus; data collected in three online rounds from participants between 30 November 2020 and 18 May 2021.Participants Professionals interested in multimorbidity and people with long term conditions were recruited to professional and public panels.Results 150 professional and 25 public participants completed the first survey round. Response rates for rounds 2/3 were 83%/92% for professionals and 88%/93% in the public panel, respectively. Across both panels, the consensus was that multimorbidity should be defined as two or more long term conditions. Complex multimorbidity was perceived to be a useful concept, but the panels were unable to agree on how to define it. Both panels agreed that conditions should be included in a multimorbidity measure if they were one or more of the following: currently active; permanent in their effects; requiring current treatment, care, or therapy; requiring surveillance; or relapsing-remitting conditions requiring ongoing care. Consensus was reached for 24 conditions to always include in multimorbidity measures, and 35 conditions to usually include unless a good reason not to existed. Simple counts were preferred for estimating prevalence and examining clustering or trajectories, and weighted measures were preferred for risk adjustment and outcome prediction.Conclusions Previous multimorbidity research is limited by inconsistent definitions and approaches to measuring multimorbidity. This Delphi study identifies professional and public panel consensus guidance to facilitate consistency of definition and measurement, and to improve study comparability and reproducibility. |
published_date |
2022-07-27T04:19:21Z |
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11.021648 |