1. Detection Algorithms for Gastrointestinal Perforation Cases in the Medical Information Database Network (MID-NET®) in Japan.
- Author
-
Tanigawa, Masatoshi, Kohama, Mei, Hirata, Kaori, Izukura, Rieko, Kandabashi, Tadashi, Kataoka, Yoko, Nakashima, Naoki, Kimura, Michio, Uyama, Yoshiaki, and Yokoi, Hideto
- Subjects
PHARMACOLOGY ,MEDICAL information storage & retrieval systems ,INTESTINAL perforation ,DATA analysis ,DRUG side effects ,HOSPITAL care ,COMPUTED tomography ,FISHER exact test ,DESCRIPTIVE statistics ,ANTI-infective agents ,ELECTRONIC health records ,MEDICAL records ,ACQUISITION of data ,STATISTICS ,MEDICAL coding ,CONFIDENCE intervals ,DATA analysis software ,ALGORITHMS ,NOSOLOGY ,SENSITIVITY & specificity (Statistics) - Abstract
Background: The Medical Information Database Network (MID-NET
® ) in Japan is a vast repository providing an essential pharmacovigilance tool. Gastrointestinal perforation (GIP) is a critical adverse drug event, yet no well-established GIP identification algorithm exists in MID-NET® . Methods: This study evaluated 12 identification algorithms by combining ICD-10 codes with GIP therapeutic procedures. Two sites contributed 200 inpatients with GIP-suggestive ICD-10 codes (100 inpatients each), while a third site contributed 165 inpatients with GIP-suggestive ICD-10 codes and antimicrobial prescriptions. The positive predictive values (PPVs) of the algorithms were determined, and the relative sensitivity (rSn) among the 165 inpatients at the third institution was evaluated. Results: A trade-off between PPV and rSn was observed. For instance, ICD-10 code-based definitions yielded PPVs of 59.5%, whereas ICD-10 codes with CT scan and antimicrobial information gave PPVs of 56.0% and an rSn of 97.0%, and ICD-10 codes with CT scan and antimicrobial information as well as three types of operation codes produced PPVs of 84.2% and an rSn of 24.2%. The same algorithms produced statistically significant differences in PPVs among the three institutions. Combining diagnostic and procedure codes improved the PPVs. The algorithm combining ICD-10 codes with CT scan and antimicrobial information and 80 different operation codes offered the optimal balance (PPV: 61.6%, rSn: 92.4%). Conclusion: This study developed valuable GIP identification algorithms for MID-NET® , revealing the trade-offs between accuracy and sensitivity. The algorithm with the most reasonable balance was determined. These findings enhance pharmacovigilance efforts and facilitate further research to optimize adverse event detection algorithms. [ABSTRACT FROM AUTHOR]- Published
- 2024
- Full Text
- View/download PDF