ArticleJournal of multimorbidity and comorbidity
Capturing the human impact of living with multiple long-term conditions in routine electronic health records - lost in translation?
Article in Journal of multimorbidity and comorbidity. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
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', '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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.