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Assessing the accuracy of using diagnostic codes from administrative data to infer antidepressant treatment
Jenna Wong1,2, Michal Abrahamowicz1, David L Buckeridge1
1Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Canada.
Purpose:
To assess the accuracy of using diagnostic codes from administrative data to infer treatment indications for antidepressants prescribed in primary care.
Methods:
Validation study of administrative diagnostic codes for 13 plausible indications for antidepressants compared with physician-documented treatment indications from an indication-based electronic prescribing system in Quebec, Canada. The analysis included all antidepressant prescriptions written by primary care physicians between January 1, 2003 and December 31, 2012 using the electronic prescribing system. Patient prescribed antidepressants were linked to physician claims and hospitalization data to obtain all diagnoses recorded in the past year.
Results:
Diagnostic codes had poor sensitivity for all treatment indications, ranging from a high of only 31.2% (95% CI, 26.8%-35.9%) for anxiety/stress disorders to as low as 1.3% (95% CI, 0.0%-5.2%) for sexual dysfunction. Sensitivity was notably worse among older patients and patients with more chronic comorbidities. Physician claims data were a better source of diagnostic codes for antidepressant treatment indications than hospitalization data.
Conclusions:
Administrative diagnostic codes are poor proxies for antidepressant treatment indications. Future work should determine whether the use of other variables in administrative data besides diagnostic codes can improve the ability to predict antidepressant treatment indications.
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