Identifying cases of spinal cord injury or disease in a primary care electronic medical record database

Abstract

Objective: To identify cases of spinal cord injury or disease (SCI/D) in an Ontario database of primary care electronic medical records (EMR). Design: A reference standard of cases of chronic SCI/D was established via manual review of EMRs; this reference standard was used to evaluate potential case identification algorithms for use in the same database. Setting: Electronic Medical Records Primary Care (EMRPC) Database, Ontario, Canada. Participants: A sample of 48,000 adult patients was randomly selected from 213,887 eligible patients in the EMRPC database. Interventions: N/A. Main Outcome Measure(s): Candidate algorithms were evaluated using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F-score. Results: 126 cases of chronic SCI/D were identified, forming the reference standard. Of these, 57 were cases of traumatic spinal cord injury (TSCI), and 67 were cases of non-traumatic spinal cord injury (NTSCI). The optimal case identification algorithm used free-text keyword searches and a physician billing code, and had 70.6% sensitivity (61.9–78.4), 98.5% specificity (97.3–99.3), 89.9% PPV (82.2–95.0), 94.7% NPV (92.8–96.3), and an F-score of 79.1. Conclusions: Identifying cases of chronic SCI/D from a database of primary care EMRs using free-text entries is feasible, relying on a comprehensive case definition. Identifying a cohort of patients with SCI/D will allow for future study of the epidemiology and health service utilization of these patients.