Related Experiment Video
Updated: Feb 12, 2026
Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
Published on: November 10, 2023
Multicentre development and validation of data-driven claims-based algorithms for identifying dermatomyositis and
Ken-Ei Sada1, Yoshia Miyawaki2, Ryo Yanai3
1Department of Clinical Epidemiology, Kochi Medical School, Nankoku, Japan.
Objective:
To develop and validate data-driven algorithms for identifying patients with dermatomyositis and polymyositis using Japanese administrative claims data.
Methods:
This multicentre retrospective, cross-sectional study included outpatients from six university hospitals between November and December 2023. Administrative claims data covering 1 year were linked with chart-confirmed diagnoses. Twenty-six candidate variables, including diagnosis codes, laboratory tests, prescriptions, and administrative billing items, were evaluated. Three feature-selection methods were applied to identify relevant predictors. Decision tree analysis was used to construct simplified rule-based algorithms, which were validated in independent internal and external cohorts.
Results:
Among 8199 training, 3512 testing, and 1827 external validation patients, 576 (7.0%), 244 (6.9%), and 136 (4.2%) carried diagnosis codes for dermatomyositis/polymyositis, of whom 352, 150, and 98 were confirmed as true cases, respectively. The performance of diagnosis codes alone yielded positive predictive values of 0.602 in the testing set and 0.713 in the external validation set. Anti-double-stranded DNA antibody testing, intractable disease management fees, and diagnosis codes for Sjögren's syndrome were identified as key discriminative variables. The optimal algorithm demonstrated a sensitivity of 0.878, a specificity of 0.984, a positive predictive value of 0.761, and an F1-score of 0.815 in the external validation cohort, providing superior accuracy compared to the use of International Classification of Diseases-10 codes alone.
Conclusions:
International Classification of Diseases-10 codes alone were insufficient for the accurate identification of dermatomyositis/polymyositis in Japanese claims data. Integrating laboratory tests and administrative information substantially improved the positive predictive value, providing a practical and generalizable framework for claims-based research in Japan.
Related Concept Videos
01:15Data Validation
Key parameters for method validation include:
01:03Data Validation
Nursing assessment guides are generally based on holistic models rather than medical...
01:11Testing a Claim about Mean: Known Population SD
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...
01:29Reliability and Validity
01:10In Vitro Drug Release Testing: Overview, Development and Validation
01:24Testing a Claim about Population Proportion
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...