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Identifying cases of spinal cord injury or disease in a primary care electronic medical record database
John Shepherd1, Karen Tu2,3,4,5, Jacqueline Young6
1Rehabilitation Sciences Institute, University of Toronto, Toronto, Ontario, Canada.
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.
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