Abstract
Background: Frailty is a state of increased vulnerability from physical, social, and cognitive factors resulting in greater risk of negative health outcomes. There is potential for better frailty assessment in primary care by using electronic medical record (EMR) data. Aim. To adapt the validated UK 36-item electronic frailty index (eFI) to a Canadian context. Methods. The eFI calculates frailty scores using EMR data. Clinical terminology mapping was required to translate the clinical codes that reflect frailty in the UK eFI to Canadian primary care terminologies (ICD, LOINC, ATC). Manual and automatic mapping was used to develop a superset of codes. We used data from the BC Canadian Primary Care Sentinel Surveillance Network to develop a list of free text terms by searching free text fields related to diagnoses and reasons for patient visits within a sample of patients (65 years) EMRs from July 207 to June 2022.
Results: A total of 3768 terms were identified for the frailty factors (302 codes and 747 free text terms). 69% of the factors were captured mostly by codes; 20% mostly by free text; and % were captured approximately equally.
Conclusion & Implications: It is difficult to capture frailty using only standardized terminologies used in Canada. A combination of standardized codes and free text better captures the complexity of frailty. This study allows for the development of a frailty screening algorithm and subsequently a frailty screening tool that can be implemented in primary care frailty screening, resulting in improved patient and system level outcomes.Funding sources: Canadian Institutes of Health Research, Canadian Nurses Foundation.