Abstract
BACKGROUND: Electronic medical record (EMR) systems in primary care present an opportunity to address frailty, a significant health concern for older adults. Researchers in the UK used Read codes to develop a 36-factor electronic frailty index (eFI), which produces frailty scores for patients in primary care settings. AIM: We aimed to translate the 36-factor eFI to a Canadian context. METHODS: We used manual and automatic mapping to develop a coding set based on standardized terminologies used in Canada to reflect the 36 factors of the eFI. Manual mapping was completed independently by two coders, followed by group consensus among the research team. Automatic mapping was completed using Apelon TermWorks. We then used EMR data from the British Columbia Canadian Primary Care Sentinel Surveillance Network. We searched structured data fields related to diagnoses and reasons for patient visits to develop a list of free text terms associated with any of the 36 factors. RESULTS AND CONCLUSIONS: A total of 3768 terms were identified; 3021 were codes. A total of 747 free text terms were identified from 527,521 reviewed data entries. Of the 36 frailty factors, 24 were captured mostly by codes; 7 mostly by free text; and 4 approximately equally by codes and free text. Three key findings emerged from this study: (1) It is difficult to capture frailty using only standardized terminologies currently used in Canada and a combination of standardized codes and free text terms better captures the complexity of frailty; (2) EMRs in primary care can be better optimized; (3) Output from this study allows for the development of a frailty screening algorithm that could be implemented in primary care settings to improve individual and system level outcomes related to frailty.