Summary
This study quantifies agreement between electronic health records and self-reported surveys for medical history in a large US cohort (All of Us Research Program). The findings demonstrate variable concordance across disease categories, with cancer conditions showing highest agreement (0.45) and infectious disease lowest (0.12), suggesting that survey data can meaningfully supplement EHR documentation for conditions typically underdocumented in clinical records.
UK applicability
The methodological approach is applicable to UK clinical research contexts, though specific findings reflect US EHR systems and may not directly transfer. UK researchers could adapt this framework to assess agreement between NHS records and patient-reported data, particularly to identify documentation gaps in primary or secondary care.
Key measures
Positive agreement scores between EHR and survey data by disease category; percentage of participants with completed surveys and EHR data; agreement by condition type (hearing/vision, infectious disease, cancer, etc.)
Outcomes reported
The study compared medical history data collected through self-reported surveys and electronic health records (EHRs) across over 150 conditions in 314,994 participants from the All of Us Research Program. Agreement scores were calculated for each condition category to identify data quality and complementarity between the two sources.
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