Using electronic health records to understand multimorbidity in older people: a scoping review
Using electronic health records to understand multimorbidity in older people: a scoping review
Background: the increasing availability of electronic health records (EHR), encompassing routinely collected general practice, hospital, and linked national census data, presents significant opportunities to enhance our understanding of multimorbidity at scale. However, the utility and clinical impact of EHR in advancing multimorbidity research, particularly concerning older adults who are disproportionately affected, remain unclear.
Aim: this study aims to synthesise the literature on the use of EHR to investigate multimorbidity in individuals aged >65 years.
Method: we conducted a scoping review, performing literature searches across Medline, Embase, CINAHL, and the Cochrane Central Register of Controlled Trials. Studies published from the inception of these databases until September 2024 were included if they investigated multimorbidity using EHR in individuals aged >65 years. Data were extracted and synthesised narratively.
Results: 620 studies were identified, with 46 meeting the inclusion criteria. All studies originated from high-income countries, primarily the USA and Spain. Research focused on areas such as healthcare utilisation and costs, predictive modelling based on patient disease profiles, specific clustering models, relationships between multimorbidity and particular disease categories, aetiology, polypharmacy, and the accuracy of EHR. Reporting on data completeness, sociodemographic characteristics, and inclusion of ethnic and social diversity within EHR datasets was notably limited.
Conclusion: the use of EHR to elucidate multimorbidity is expanding and holds substantial promise. However, enhanced reporting of data completeness and sociodemographic characteristics is essential to facilitate the effective translation of findings into real-world populations. Neglecting these aspects risks exacerbating inequality gaps for individuals > 65 years with multimorbidity.
Smith, Lucy
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Simpson, Glenn
802b50d9-aa00-4cca-9eaf-238385f8481c
Singh, Neil
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Wells, Lucy
d8e7370d-e936-4c77-b4ff-070274270294
Dambha-Miller, Hajira
58961db5-31aa-460e-9394-08590c4b7ba1
22 May 2025
Smith, Lucy
835f8b9b-b6e0-4f5f-b6b4-a48c7913b463
Simpson, Glenn
802b50d9-aa00-4cca-9eaf-238385f8481c
Singh, Neil
6341983a-716e-4aad-b655-8450e0c9d1da
Wells, Lucy
d8e7370d-e936-4c77-b4ff-070274270294
Dambha-Miller, Hajira
58961db5-31aa-460e-9394-08590c4b7ba1
Smith, Lucy, Simpson, Glenn, Singh, Neil, Wells, Lucy and Dambha-Miller, Hajira
(2025)
Using electronic health records to understand multimorbidity in older people: a scoping review.
The British journal of general practice : the journal of the Royal College of General Practitioners, 75 (Suppl. 1).
(doi:10.3399/bjgp25X741933).
Record type:
Meeting abstract
Abstract
Background: the increasing availability of electronic health records (EHR), encompassing routinely collected general practice, hospital, and linked national census data, presents significant opportunities to enhance our understanding of multimorbidity at scale. However, the utility and clinical impact of EHR in advancing multimorbidity research, particularly concerning older adults who are disproportionately affected, remain unclear.
Aim: this study aims to synthesise the literature on the use of EHR to investigate multimorbidity in individuals aged >65 years.
Method: we conducted a scoping review, performing literature searches across Medline, Embase, CINAHL, and the Cochrane Central Register of Controlled Trials. Studies published from the inception of these databases until September 2024 were included if they investigated multimorbidity using EHR in individuals aged >65 years. Data were extracted and synthesised narratively.
Results: 620 studies were identified, with 46 meeting the inclusion criteria. All studies originated from high-income countries, primarily the USA and Spain. Research focused on areas such as healthcare utilisation and costs, predictive modelling based on patient disease profiles, specific clustering models, relationships between multimorbidity and particular disease categories, aetiology, polypharmacy, and the accuracy of EHR. Reporting on data completeness, sociodemographic characteristics, and inclusion of ethnic and social diversity within EHR datasets was notably limited.
Conclusion: the use of EHR to elucidate multimorbidity is expanding and holds substantial promise. However, enhanced reporting of data completeness and sociodemographic characteristics is essential to facilitate the effective translation of findings into real-world populations. Neglecting these aspects risks exacerbating inequality gaps for individuals > 65 years with multimorbidity.
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Published date: 22 May 2025
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Local EPrints ID: 503166
URI: http://eprints.soton.ac.uk/id/eprint/503166
ISSN: 0960-1643
PURE UUID: be79e0f6-d372-4964-8e85-d6bab1803c2f
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Date deposited: 23 Jul 2025 16:32
Last modified: 24 Jul 2025 01:59
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Author:
Lucy Smith
Author:
Neil Singh
Author:
Lucy Wells
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