Development of algorithms for identifying patients with Crohn's disease in the Japanese health insurance claims database.

BACKGROUND

Real-world big data studies using health insurance claims databases require extraction algorithms to accurately identify target population and outcome. However, no algorithm for Crohn's disease (CD) has yet been validated. In this study we aim to develop an algorithm for identifying CD using the claims data of the insurance system.

METHODS

A single-center retrospective study to develop a CD extraction algorithm from insurance claims data was conducted. Patients visiting the Kitasato University Kitasato Institute Hospital between January 2015-February 2019 were enrolled, and data were extracted according to inclusion criteria combining the Tenth Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) diagnosis codes with or without prescription or surgical codes. Hundred cases that met each inclusion criterion were randomly sampled and positive predictive values (PPVs) were calculated according to the diagnosis in the medical chart. Of all cases, 20% were reviewed in duplicate, and the inter-observer agreement (Kappa) was also calculated.

RESULTS

From the 82,898 enrolled, 255 cases were extracted by diagnosis code alone, 197 by the combination of diagnosis and prescription codes, and 197 by the combination of diagnosis codes and prescription or surgical codes. The PPV for confirmed CD cases was 83% by diagnosis codes alone, but improved to 97% by combining with prescription codes. The inter-observer agreement was 0.9903.

CONCLUSIONS

Single ICD-code alone was insufficient to define CD; however, the algorithm that combined diagnosis codes with prescription codes indicated a sufficiently high PPV and will enable outcome-based research on CD using the Japanese claims database.

Déclaration de conflit d'intérêts

HM has received research grants from Japan Foundation for Applied Enzymology. TK has served as a speaker, a consultant or an advisory board member for Abbvie, Alfresa Pharma, Janssen Pharma, Takeda, Mitsubishi Tanabe Pharma, Pfizer, Mochida, and received research grants from Nippon Kayaku, EA Pharma, Otsuka Holdings, JIMRO, Abbie, Zeria. FT has received research grants from Mitsubishi Tanabe Pharma. TN are employees of JMDC Co. Ltd., holds shares in JMDC Co. Ltd. TaH has served as a speaker, a consultant or an advisory board member for Mitsubishi Tanabe Pharma, AbbVie GK, EA Pharma, Kyorin Pharma, JIMRO, Janssen Pharmaceutical, Mochida Pharmaceutical, Takeda Pharmaceutical, and received research grants from Alfresa Pharma, EA Pharma, Mitsubishi Tanabe Pharma, AbbVie GK, JIMRO, Zeria Pharmaceutical, Daiichi-Sankyo, Kyorin Pharmaceutical, Nippon Kayaku, Astellas Pharma, Takeda Pharmaceutical, Pfizer, Mochida Pharmaceutical. ToH has served as a speaker, a consultant or an advisory board member for Aspen Japan, Abbvie GK, Ferring, Gilead Sciences, Janssen, JIMRO, Mitsubishi Tanabe Pharma, Mochida Pharmaceutical, Nippon Kayaku, Pfizer, Takeda Pharmaceutical, Zeria, and received research grants from Abbvie, EA Pharma, JIMRO, Otsuka Holdings, Zeria, and received scholarship grants from Zeria. This does not alter our adherence to PLOS ONE policies on sharing data and materials.