Validation Study of Algorithms to Identify Malignant Tumors and Serious Infections in a Japanese Administrative Healthcare Database.

ABSTRACT:

Background

This retrospective observational study validated case-finding algorithms for malignant tumors and serious infections in a Japanese administrative healthcare database.

Methods

Random samples of possible cases of each disease (January 2015-January 2018) from two hospitals participating in the Medical Data Vision Co., Ltd. (MDV) database were identified using combinations of ICD-10 diagnostic codes and other procedural/billing codes. For each disease, two physicians identified true cases among the random samples of possible cases by medical record review; a third physician made the final decision in cases where the two physicians disagreed. The accuracy of case-finding algorithms was assessed using positive predictive value (PPV) and sensitivity.

Results

There

SUBMITTER: Nishikawa A 

PROVIDER: S-EPMC10760479 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature