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

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.