BACKGROUND: Large health care organizations may use administrative data to target primary care patients with depression for quality improvement (QI) activities. However, little is known about the patients who would be identified by these data or the types of QI activities they might need. We describe the clinical characteristics and outcomes of patients identified through administrative data in 2 family practice clinics. METHODS: Patients with depression aged 18 to 65 years were identified through review of encounter/administrative data during a 16-month period. Patients agreeing to participate (N=103) were interviewed with the Primary Care Evaluation of Mental Disorders questionnaire and completed the Depression Outcomes Modules (with an embedded Medical Outcomes Short Form-36 [SF-36]), Symptom Check List-25 (SCL-25), and Alcohol use Disorders Identification Test. Follow-up assessments were completed by 83 patients at a median of 7 months. RESULTS: A large majority of identified patients (85%) met full criteria for a Diagnostic and Statistical Manual of Mental Disorders depressive disorder; those not meeting criteria usually had high levels of symptoms on the SCL-25. Seventy-seven percent of the patients reported recurrent episodes of depressed mood, and 60% reported chronic depression. Although most improved at follow-up, they continued to have substantial functional deficits on the SF-36, and 60% still had high levels of depressive symptoms. CONCLUSIONS: QI programs that use administrative data to identify primary care patients with depression will select a cohort with relatively severe, recurrent depressive disorders. Most of these patients will receive standard treatments without QI interventions and will continue to be symptomatic. QI programs targeting this population may need to offer intensive alternatives rather than monitor standard care.
BACKGROUND: Large health care organizations may use administrative data to target primary care patients with depression for quality improvement (QI) activities. However, little is known about the patients who would be identified by these data or the types of QI activities they might need. We describe the clinical characteristics and outcomes of patients identified through administrative data in 2 family practice clinics. METHODS:Patients with depression aged 18 to 65 years were identified through review of encounter/administrative data during a 16-month period. Patients agreeing to participate (N=103) were interviewed with the Primary Care Evaluation of Mental Disorders questionnaire and completed the Depression Outcomes Modules (with an embedded Medical Outcomes Short Form-36 [SF-36]), Symptom Check List-25 (SCL-25), and Alcohol use Disorders Identification Test. Follow-up assessments were completed by 83 patients at a median of 7 months. RESULTS: A large majority of identified patients (85%) met full criteria for a Diagnostic and Statistical Manual of Mental Disorders depressive disorder; those not meeting criteria usually had high levels of symptoms on the SCL-25. Seventy-seven percent of the patients reported recurrent episodes of depressed mood, and 60% reported chronic depression. Although most improved at follow-up, they continued to have substantial functional deficits on the SF-36, and 60% still had high levels of depressive symptoms. CONCLUSIONS: QI programs that use administrative data to identify primary care patients with depression will select a cohort with relatively severe, recurrent depressive disorders. Most of these patients will receive standard treatments without QI interventions and will continue to be symptomatic. QI programs targeting this population may need to offer intensive alternatives rather than monitor standard care.
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