Estimation of the Prevalence of Chronic Kidney Disease in People with Diabetes by Combining Information from Multiple Routine Data Collections
利用奥地利社保机构的医疗索赔数据，通过高维回归模型整合分散的疾病类型和分期信息，估计了全国糖尿病患者中慢性肾病的分期患病率，并与已有研究验证了结果的一致性。
Abstract Health care claims databases maintained by social insurance institutions provide rich and sometimes easily accessible data sources for epidemiological research. Interpreting the registered claims, for example, drug prescriptions, as proxies for the condition of interest, for example, diabetes, they allow for nationwide prevalence estimation. We illustrate a more subtle use of health care claims data in estimating the stage-specific prevalence of chronic kidney disease in the Austrian population with diabetes. The main difficulty was that information on the type of disease (chronic or acute) and information on the stage of disease were only available for small, almost disjoint subsets of the health care claims data. Using high-dimensional regression models, we could combine the information and provide nationwide estimates of the stage-specific prevalence of diabetic chronic kidney disease. Validating our estimates by comparing to other studies, we found the level of agreement satisfying.