Performance evaluation of case definitions of type 1 diabetes for health insurance claims data in Japan

Tasuku Okui, Chinatsu Nojiri, Shinichiro Kimura, Kentaro Abe, Sayaka Maeno, Masae Minami, Yasutaka Maeda, Naoko Tajima, Tomoyuki Kawamura, Naoki Nakashima

Research output: Contribution to journalArticlepeer-review

Abstract

Background: No case definition of Type 1 diabetes (T1D) for the claims data has been proposed in Japan yet. This study aimed to evaluate the performance of candidate case definitions for T1D using Electronic health care records (EHR) and claims data in a University Hospital in Japan. Methods: The EHR and claims data for all the visiting patients in a University Hospital were used. As the candidate case definitions for claims data, we constructed 11 definitions by combinations of International Statistical Classification of Diseases and Related Health Problems, Tenth Revision. (ICD 10) code of T1D, the claims code of insulin needles for T1D patients, basal insulin, and syringe pump for continuous subcutaneous insulin infusion (CSII). We constructed a predictive model for T1D patients using disease names, medical practices, and medications as explanatory variables. The predictive model was applied to patients of test group (validation data), and performances of candidate case definitions were evaluated. Results: As a result of performance evaluation, the sensitivity of the confirmed disease name of T1D was 32.9 (95% CI: 28.4, 37.2), and positive predictive value (PPV) was 33.3 (95% CI: 38.0, 38.4). By using the case definition of both the confirmed diagnosis of T1D and either of the claims code of the two insulin treatment methods (i.e., syringe pump for CSII and insulin needles), PPV improved to 90.2 (95% CI: 85.2, 94.4). Conclusions: We have established a case definition with high PPV, and the case definition can be used for precisely detecting T1D patients from claims data in Japan.

Original languageEnglish
Article number52
JournalBMC Medical Informatics and Decision Making
Volume21
Issue number1
DOIs
Publication statusPublished - Dec 2021

All Science Journal Classification (ASJC) codes

  • Health Policy
  • Health Informatics

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