Abstract
INTRODUCTION: Telemedicine use has risen significantly since the COVID-19 pandemic. Evidence suggests that the quality of care in telemedicine could be as good as in-person care, but this is likely context-dependent. Expert guidelines have declared the appropriate medical conditions, but often without empirical evidence that grapples with the fundamental information limitations facing telemedicine. We draw on the task-technology fit theory and empirical evidence around human communication to examine how the medical and social contexts affect the efficiency and clinical quality of primary care. METHODS AND ANALYSIS: We will use a population-based dataset from the Canadian province of British Columbia (BC) to inform a quasi-experimental study using propensity score matching (PSM). The treatment group will consist of telemedicine visits from April to December 2022. We will use PSM to create a control group of matched, in-person visits in the same period. We will then use cluster-robust linear regression to identify how specific medical conditions and social contexts are associated with higher rates of prescription, follow-up with primary care providers, emergency department visits and acute care admissions. We plan for the study to take place from 1 August 2025 to 1 August 2026. ETHICS AND DISSEMINATION: The Research Ethics BC has granted approval for this study (H21-02244-A006). Our findings will be shared with patients, healthcare providers and policymakers and disseminated through conference presentations and peer-reviewed publications.