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Routine Data Analyses to Compare Outpatient Depression Treatment Regimens
Robin Siegel1, Thomas Ostermann1, Reinhard Schuster2
1Department for Psychology and Psychotherapy, Witten/Herdecke University, Alfred-Herrhausen-Straße 50, 58448 Witten, Germany.
Studies in Health Technology and Informatics
|September 9, 2017
Summary
Healthcare data quality is crucial for policy. This study analyzed outpatient depression diagnoses, finding general physicians often diagnose unspecified episodes, unlike mental health specialists.
Area of Science:
- Health Services Research
- Health Informatics
- Psychiatry
Background:
- Routine data analyses are vital for health policy.
- Healthcare databases vary in quality, completeness, and accessibility.
- Understanding data structure is key for accurate health policy decisions.
Purpose of the Study:
- To describe the quality of a large outpatient healthcare database.
- To detail the data extraction process.
- To analyze provider-type and disease severity in depressive disorder treatment.
Main Methods:
- Database quality assessment.
- Calculation of depression diagnosis rates (ICD-10 F32/33) in outpatient care.
- Analysis of diagnosis rates by provider-type using Cramers V for effect size.
Main Results:
- The 2015 database contained 2,383,672 cases.
- General/somatic physicians diagnosed and treated most depressive patients.
- A relationship exists between depression severity and provider-type; general physicians diagnose more unspecified depressive episodes.
Conclusions:
- Outpatient healthcare databases require rigorous quality assessment for reliable health policy.
- Provider-type influences depression diagnosis patterns, with general physicians more likely to diagnose unspecified episodes.
- Further research into data quality and diagnostic practices is warranted.
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