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Capturing the human impact of living with multiple long-term conditions in routine electronic health records - lost in translation?

Simon D S Fraser Orcid Logo, Emilia Holland Orcid Logo, Lynn Laidlaw Orcid Logo, Nick A Francis Orcid Logo, Sara Macdonald, Frances S Mair Orcid Logo, Nisreen A Alwan, Michael Boniface Orcid Logo, Rebecca B Hoyle Orcid Logo, Nic Fair, Jakub J Dylag, Mozhdeh Shiranirad, Roberta Chiovoloni, Sebastian Stannard Orcid Logo, Robin Poole Orcid Logo, Ashley Akbari Orcid Logo, Mark Ashworth, Alex Dregan

Journal of Multimorbidity and Comorbidity, Volume: 15

Swansea University Authors: Roberta Chiovoloni, Ashley Akbari Orcid Logo

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DOI (Published version): 10.1177/26335565251329869

Abstract

Background: Living with multiple long-term conditions (MLTCs) involves ‘work’. A recent qualitative synthesis identified eight patient-centred work themes: ‘learning and adapting’, ‘accumulation and complexity’, ‘investigation and monitoring’, ‘health service and administration’ and ‘symptom’, ‘emot...

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Published in: Journal of Multimorbidity and Comorbidity
ISSN: 2633-5565 2633-5565
Published: SAGE Publications 2025
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URI: https://cronfa.swan.ac.uk/Record/cronfa69276
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fullrecord <?xml version="1.0"?><rfc1807><datestamp>2025-04-11T12:28:59.0203669</datestamp><bib-version>v2</bib-version><id>69276</id><entry>2025-04-11</entry><title>Capturing the human impact of living with multiple long-term conditions in routine electronic health records - lost in translation?</title><swanseaauthors><author><sid>08502855f683911aeb83edd02904be23</sid><firstname>Roberta</firstname><surname>Chiovoloni</surname><name>Roberta Chiovoloni</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>2025-04-11</date><deptcode>MEDS</deptcode><abstract>Background: Living with multiple long-term conditions (MLTCs) involves &#x2018;work&#x2019;. A recent qualitative synthesis identified eight patient-centred work themes: &#x2018;learning and adapting&#x2019;, &#x2018;accumulation and complexity&#x2019;, &#x2018;investigation and monitoring&#x2019;, &#x2018;health service and administration&#x2019; and &#x2018;symptom&#x2019;, &#x2018;emotional&#x2019;, &#x2018;medication&#x2019; and &#x2018;financial&#x2019; work. These themes may be underrepresented in electronic health records (EHRs). This study aimed to evaluate the representation of these themes and their constituent concepts in EHR data in a general population and among individuals with history of a mental health condition. Methods: Using the OpenCodelists builder from OpenSAFELY, clinical code lists corresponding to work concepts were developed using Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) and validated by two clinicians. Additional concepts were engineered within the Clinical Practice Research Datalink (CPRD) and the Secure Anonymised Information Linkage (SAIL) Databank. We analysed trends in recording rates over 20 years across a SAIL general population cohort (n=5,180,602) and a CPRD cohort comprising individuals with a mental health diagnosis (n=3,616,776) and matched controls (n=4,457,225). Results: 55 code lists and seven engineered concepts were developed across the themes. The proportion of patients with codes related to &#x2018;investigation and monitoring&#x2019; exceeded 40%, while &#x2018;accumulation and complexity&#x2019; and &#x2018;financial work&#x2019; were poorly represented (&lt;2% and &lt;1% of the study population respectively). Recording was generally higher among individuals with a mental health diagnosis history. Conclusion: While EHR data captures some aspects of MLTC work, patient-centred concepts are under-represented. Future research should explore reasons behind variability in coding practices, and innovative methods for enriching structured records with patient-centred data.</abstract><type>Journal Article</type><journal>Journal of Multimorbidity and Comorbidity</journal><volume>15</volume><journalNumber/><paginationStart/><paginationEnd/><publisher>SAGE Publications</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>2633-5565</issnPrint><issnElectronic>2633-5565</issnElectronic><keywords>multimorbidity, long-term conditions, electronic health records, clinical coding, lived experience</keywords><publishedDay>31</publishedDay><publishedMonth>12</publishedMonth><publishedYear>2025</publishedYear><publishedDate>2025-12-31</publishedDate><doi>10.1177/26335565251329869</doi><url/><notes/><college>COLLEGE NANME</college><department>Medical School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MEDS</DepartmentCode><institution>Swansea University</institution><apcterm>Another institution paid the OA fee</apcterm><funders>This study is independent research funded by the National Institute for Health and Care Research (NIHR) Artificial Intelligence for Multiple Long-Term Conditions (AIM) &#x2018;Multidisciplinary Ecosystem to study Lifecourse Determinants and Prevention of Early-onset Burdensome Multimorbidity (MELD-B)&#x2019;, (reference number NIHR203988). The MELD-B study also received some funding from the NIHR Applied Research Collaboration Wessex.</funders><projectreference/><lastEdited>2025-04-11T12:28:59.0203669</lastEdited><Created>2025-04-11T12:17:14.0052667</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>Simon D S</firstname><surname>Fraser</surname><orcid>0000-0002-4172-4406</orcid><order>1</order></author><author><firstname>Emilia</firstname><surname>Holland</surname><orcid>0000-0001-5722-3836</orcid><order>2</order></author><author><firstname>Lynn</firstname><surname>Laidlaw</surname><orcid>0000-0001-6688-6658</orcid><order>3</order></author><author><firstname>Nick A</firstname><surname>Francis</surname><orcid>0000-0001-8939-7312</orcid><order>4</order></author><author><firstname>Sara</firstname><surname>Macdonald</surname><order>5</order></author><author><firstname>Frances S</firstname><surname>Mair</surname><orcid>0000-0001-9780-1135</orcid><order>6</order></author><author><firstname>Nisreen A</firstname><surname>Alwan</surname><order>7</order></author><author><firstname>Michael</firstname><surname>Boniface</surname><orcid>0000-0002-9281-6095</orcid><order>8</order></author><author><firstname>Rebecca B</firstname><surname>Hoyle</surname><orcid>0000-0002-1645-1071</orcid><order>9</order></author><author><firstname>Nic</firstname><surname>Fair</surname><order>10</order></author><author><firstname>Jakub J</firstname><surname>Dylag</surname><order>11</order></author><author><firstname>Mozhdeh</firstname><surname>Shiranirad</surname><order>12</order></author><author><firstname>Roberta</firstname><surname>Chiovoloni</surname><order>13</order></author><author><firstname>Sebastian</firstname><surname>Stannard</surname><orcid>0000-0002-6139-1020</orcid><order>14</order></author><author><firstname>Robin</firstname><surname>Poole</surname><orcid>0000-0002-3113-5202</orcid><order>15</order></author><author><firstname>Ashley</firstname><surname>Akbari</surname><orcid>0000-0003-0814-0801</orcid><order>16</order></author><author><firstname>Mark</firstname><surname>Ashworth</surname><order>17</order></author><author><firstname>Alex</firstname><surname>Dregan</surname><order>18</order></author></authors><documents><document><filename>69276__34016__aacbb52c3d8f443d81957235662e3e6f.pdf</filename><originalFilename>69276.VOR.pdf</originalFilename><uploaded>2025-04-11T12:24:16.2585318</uploaded><type>Output</type><contentLength>1267379</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>&#xA9; The Author(s) 2025. 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spelling 2025-04-11T12:28:59.0203669 v2 69276 2025-04-11 Capturing the human impact of living with multiple long-term conditions in routine electronic health records - lost in translation? 08502855f683911aeb83edd02904be23 Roberta Chiovoloni Roberta Chiovoloni true false aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false 2025-04-11 MEDS Background: Living with multiple long-term conditions (MLTCs) involves ‘work’. A recent qualitative synthesis identified eight patient-centred work themes: ‘learning and adapting’, ‘accumulation and complexity’, ‘investigation and monitoring’, ‘health service and administration’ and ‘symptom’, ‘emotional’, ‘medication’ and ‘financial’ work. These themes may be underrepresented in electronic health records (EHRs). This study aimed to evaluate the representation of these themes and their constituent concepts in EHR data in a general population and among individuals with history of a mental health condition. Methods: Using the OpenCodelists builder from OpenSAFELY, clinical code lists corresponding to work concepts were developed using Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) and validated by two clinicians. Additional concepts were engineered within the Clinical Practice Research Datalink (CPRD) and the Secure Anonymised Information Linkage (SAIL) Databank. We analysed trends in recording rates over 20 years across a SAIL general population cohort (n=5,180,602) and a CPRD cohort comprising individuals with a mental health diagnosis (n=3,616,776) and matched controls (n=4,457,225). Results: 55 code lists and seven engineered concepts were developed across the themes. The proportion of patients with codes related to ‘investigation and monitoring’ exceeded 40%, while ‘accumulation and complexity’ and ‘financial work’ were poorly represented (<2% and <1% of the study population respectively). Recording was generally higher among individuals with a mental health diagnosis history. Conclusion: While EHR data captures some aspects of MLTC work, patient-centred concepts are under-represented. Future research should explore reasons behind variability in coding practices, and innovative methods for enriching structured records with patient-centred data. Journal Article Journal of Multimorbidity and Comorbidity 15 SAGE Publications 2633-5565 2633-5565 multimorbidity, long-term conditions, electronic health records, clinical coding, lived experience 31 12 2025 2025-12-31 10.1177/26335565251329869 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University Another institution paid the OA fee This study is independent research funded by the National Institute for Health and Care Research (NIHR) Artificial Intelligence for Multiple Long-Term Conditions (AIM) ‘Multidisciplinary Ecosystem to study Lifecourse Determinants and Prevention of Early-onset Burdensome Multimorbidity (MELD-B)’, (reference number NIHR203988). The MELD-B study also received some funding from the NIHR Applied Research Collaboration Wessex. 2025-04-11T12:28:59.0203669 2025-04-11T12:17:14.0052667 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Health Data Science Simon D S Fraser 0000-0002-4172-4406 1 Emilia Holland 0000-0001-5722-3836 2 Lynn Laidlaw 0000-0001-6688-6658 3 Nick A Francis 0000-0001-8939-7312 4 Sara Macdonald 5 Frances S Mair 0000-0001-9780-1135 6 Nisreen A Alwan 7 Michael Boniface 0000-0002-9281-6095 8 Rebecca B Hoyle 0000-0002-1645-1071 9 Nic Fair 10 Jakub J Dylag 11 Mozhdeh Shiranirad 12 Roberta Chiovoloni 13 Sebastian Stannard 0000-0002-6139-1020 14 Robin Poole 0000-0002-3113-5202 15 Ashley Akbari 0000-0003-0814-0801 16 Mark Ashworth 17 Alex Dregan 18 69276__34016__aacbb52c3d8f443d81957235662e3e6f.pdf 69276.VOR.pdf 2025-04-11T12:24:16.2585318 Output 1267379 application/pdf Version of Record true © The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (CC BY 4.0). true eng https://creativecommons.org/licenses/by/4.0/
title Capturing the human impact of living with multiple long-term conditions in routine electronic health records - lost in translation?
spellingShingle Capturing the human impact of living with multiple long-term conditions in routine electronic health records - lost in translation?
Roberta Chiovoloni
Ashley Akbari
title_short Capturing the human impact of living with multiple long-term conditions in routine electronic health records - lost in translation?
title_full Capturing the human impact of living with multiple long-term conditions in routine electronic health records - lost in translation?
title_fullStr Capturing the human impact of living with multiple long-term conditions in routine electronic health records - lost in translation?
title_full_unstemmed Capturing the human impact of living with multiple long-term conditions in routine electronic health records - lost in translation?
title_sort Capturing the human impact of living with multiple long-term conditions in routine electronic health records - lost in translation?
author_id_str_mv 08502855f683911aeb83edd02904be23
aa1b025ec0243f708bb5eb0a93d6fb52
author_id_fullname_str_mv 08502855f683911aeb83edd02904be23_***_Roberta Chiovoloni
aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari
author Roberta Chiovoloni
Ashley Akbari
author2 Simon D S Fraser
Emilia Holland
Lynn Laidlaw
Nick A Francis
Sara Macdonald
Frances S Mair
Nisreen A Alwan
Michael Boniface
Rebecca B Hoyle
Nic Fair
Jakub J Dylag
Mozhdeh Shiranirad
Roberta Chiovoloni
Sebastian Stannard
Robin Poole
Ashley Akbari
Mark Ashworth
Alex Dregan
format Journal article
container_title Journal of Multimorbidity and Comorbidity
container_volume 15
publishDate 2025
institution Swansea University
issn 2633-5565
2633-5565
doi_str_mv 10.1177/26335565251329869
publisher SAGE Publications
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 Background: Living with multiple long-term conditions (MLTCs) involves ‘work’. A recent qualitative synthesis identified eight patient-centred work themes: ‘learning and adapting’, ‘accumulation and complexity’, ‘investigation and monitoring’, ‘health service and administration’ and ‘symptom’, ‘emotional’, ‘medication’ and ‘financial’ work. These themes may be underrepresented in electronic health records (EHRs). This study aimed to evaluate the representation of these themes and their constituent concepts in EHR data in a general population and among individuals with history of a mental health condition. Methods: Using the OpenCodelists builder from OpenSAFELY, clinical code lists corresponding to work concepts were developed using Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) and validated by two clinicians. Additional concepts were engineered within the Clinical Practice Research Datalink (CPRD) and the Secure Anonymised Information Linkage (SAIL) Databank. We analysed trends in recording rates over 20 years across a SAIL general population cohort (n=5,180,602) and a CPRD cohort comprising individuals with a mental health diagnosis (n=3,616,776) and matched controls (n=4,457,225). Results: 55 code lists and seven engineered concepts were developed across the themes. The proportion of patients with codes related to ‘investigation and monitoring’ exceeded 40%, while ‘accumulation and complexity’ and ‘financial work’ were poorly represented (<2% and <1% of the study population respectively). Recording was generally higher among individuals with a mental health diagnosis history. Conclusion: While EHR data captures some aspects of MLTC work, patient-centred concepts are under-represented. Future research should explore reasons behind variability in coding practices, and innovative methods for enriching structured records with patient-centred data.
published_date 2025-12-31T17:53:39Z
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score 11.08899

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