[Internal confirmation of diagnoses in routine statutory health insurance data: concept with examples and case...

Over the course of the last few decades, statutory health insurance data have become increasingly important for health services research. Of particular interest in this context are diagnoses. Since all health insurance data are originally collected for billing purposes, secondary analyses should examine the completeness, plausibility, and validity of the information provided. While an external validation through, for example, a comparison with the physician's records or a second independent medical examination can be seen as a gold standard, this is often not feasible. For this reason, internal validation approaches are recommended for studies based upon diagnoses drawn from routine data. For such approaches, no established standards are currently available. The aim of this contribution is to introduce a generic internal validation concept for chronic diseases. Data employed in the present contribution stem from the health insuree sample of the AOK health insurance fund Hesse. Criteria for assessing the validity of diagnoses (e.g., repetitions, codes assigned by various physicians, prescriptions) are presented for three chronic diseases - heart failure, dementia, and tuberculosis. Building upon these criteria, algorithms for the definition of epidemiologically certain cases are developed and prevalence estimates formed on the basis of these algorithms are compared with other data sources (registers and surveys). Internal confirmation of the diagnoses of heart failure and dementia was possible in 97% and 80% of cases, respectively. The difference between the two diagnoses is due to the low rate of treatment with specific pharmaceuticals in the case of dementia. Prevalence estimates are comparable with those based on other sources. Inpatient discharge diagnoses of tuberculosis were internally confirmed in 100% and outpatient diagnoses in 40% of cases. For this reason, outpatient diagnoses were not considered for the case definition of tuberculosis. A comparison with tuberculosis surveillance data reveals a somewhat higher incidence in the insuree sample. In selecting and weighting criteria as well as employing a case definition, the research aim of the respective investigation must be taken into account. The adopted procedure is to be presented in a transparent manner.