Identification of Adult Patients With Dermatomyositis Using Real‐World Data Sources
Authors' conclusion
We developed and validated multiple DM case identification algorithms across diverse databases, demonstrating their accuracy through multiple evaluation methods.
Study context
- Population
- Adult patients with dermatomyositis (DM) in 11 independent electronic health record or claims databases (over 800 million patients)11 databases · >800 million patients
- Comparison
- Incidence vs prevalence DM case identification algorithms
- Outcome
- Performance of DM case identification algorithms (sensitivity, PPV)
Methodological detailsmulti-database, OMOP Common Data Model, manual chart review, PheValuator and CohortDiagnostics
- Multi-database
- OMOP Common Data Model
- Manual chart review
- PheValuator and CohortDiagnostics
Performance
As reported in the abstract
Algorithm performance (best-performing algorithms)
| Strategy | Sensitivity | PPV |
|---|---|---|
| Incidence algorithm | 42% | 83% |
| Prevalence algorithm | 49% | 84% |
Sensitivity
Incidence algorithm42%
Prevalence algorithm49%
PPV
Incidence algorithm83%
Prevalence algorithm84%
Further findings
Incidence rates by age decile and sex (CohortDiagnostics)
- Aligned with previous epidemiologic data
Original publication
Identification of Adult Patients With Dermatomyositis Using Real‐World Data Sources. Arthritis Care Res (Hoboken). Published 15 November 2025. doi:10.
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