Unlocking EMR Data to Track Physical Function Across the Continuum of Care

IntroductionPhysical function (PF) is a critical contributor to quality of life and healthcare value, especially for older adults at risk for functional decline following hospitalization. Tracking PF is essential for monitoring recovery, preventing adverse events, and improving care transitions. Despite the potential of electronic health records (EHRs) to enable tracking of PF, it is rarely tracked systematically. We present a case study on the extraction of PF data from EHRs for patients transitioning from hospital to homecare in a large health system, highlighting challenges and offering recommendations. MethodsAn expert consensus group identified data elements important to the measurement of PF. We then assessed the feasibility of extracting those elements from a single healthcare system. Working with Johns Hopkins Health System (JHHS) informatics and homecare leaders, we determined which elements were captured in the EHR and which were not feasible to extract within our resource constraints. We then requested a refined data list for adult patients during the project period. After validation, data were securely transferred to University of Utah Health (UUH). ResultsData from 21,702 patients were included. Of 27 desired elements, 17 were successfully extracted. Elements were marked present if documented at least once during admission, or missing if absent. Administrative data had low missingness, while missingness for assessments of cognition and mobility performance in hospital were over 65% and assessments of PF capacity in home health were missing in over 80% of patients. However, 81.7% of those receiving home health rehabilitation had the expected mobility measure. Overall, 73% of patients had at least 75% of the extracted data elements. ConclusionsTo track PF effectively, begin with clear definitions, a targeted cohort, and relevant data elements. Collaboration with EHR, clinical, and billing experts is essential, as is upfront assessment of data availability and alignment with project resources.