Inflammatory bowel diseases · 2023
Development and Validation of Claims-Based Definitions to Identify Incident and Prevalent Inflammatory Bowel Disease in Administrative Healthcare Databases.
ОбзорСтатьяПоддержка службы здравоохранения СШАПоддержка NIH: внешняя программаНазвание и аннотация: Перевод пока не подготовлен
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Dawwas Ghadeer K, Weiss Alexandra, Constant Brad D, Parlett Lauren E, Haynes Kevin, Yang Jeff Yufeng, Brensinger Colleen, Wu Qufei, Pate Virginia, Jonsson Funk Michele, Schaubel Douglas E, Hurtado-Lorenzo Andres, David Kappelman Michael, Lewis James D
Аннотация
BACKGROUND: To facilitate inflammatory bowel disease (IBD) research in the United States, we developed and validated claims-based definitions to identify incident and prevalent IBD diagnoses using administrative healthcare claims data among multiple payers.
METHODS: We used data from Medicare, Medicaid, and the HealthCore Integrated Research Database (Anthem commercial and Medicare Advantage claims). The gold standard for validation was review of medical records. We evaluated 1 incidence and 4 prevalence algorithms based on a combination of International Classification of Diseases codes, National Drug Codes, and Current Procedural Terminology codes. The claims-based incident diagnosis date needed to be within ±90 days of that recorded in the medical record to be valid.
RESULTS: We reviewed 111 charts of patients with a potentially incident diagnosis. The positive predictive value (PPV) of the claims algorithm was 91% (95% confidence interval [CI], 81%-97%). We reviewed 332 charts to validate prevalent case definition algorithms. The PPV was 94% (95% CI, 86%-98%) for ≥2 IBD diagnoses and presence of prescriptions for IBD medications, 92% (95% CI, 85%-97%) for ≥2 diagnoses without any medications, 78% (95% CI, 67%-87%) for a single diagnosis and presence of an IBD medication, and 35% (95% CI, 25%-46%) for 1 physician diagnosis and no IBD medications.
CONCLUSIONS: Through a combination of diagnosis, procedural, and medication codes in insurance claims data, we were able to identify incident and prevalent IBD cases with high accuracy. These algorithms can be useful for the ascertainment of IBD cases in future studies.
METHODS: We used data from Medicare, Medicaid, and the HealthCore Integrated Research Database (Anthem commercial and Medicare Advantage claims). The gold standard for validation was review of medical records. We evaluated 1 incidence and 4 prevalence algorithms based on a combination of International Classification of Diseases codes, National Drug Codes, and Current Procedural Terminology codes. The claims-based incident diagnosis date needed to be within ±90 days of that recorded in the medical record to be valid.
RESULTS: We reviewed 111 charts of patients with a potentially incident diagnosis. The positive predictive value (PPV) of the claims algorithm was 91% (95% confidence interval [CI], 81%-97%). We reviewed 332 charts to validate prevalent case definition algorithms. The PPV was 94% (95% CI, 86%-98%) for ≥2 IBD diagnoses and presence of prescriptions for IBD medications, 92% (95% CI, 85%-97%) for ≥2 diagnoses without any medications, 78% (95% CI, 67%-87%) for a single diagnosis and presence of an IBD medication, and 35% (95% CI, 25%-46%) for 1 physician diagnosis and no IBD medications.
CONCLUSIONS: Through a combination of diagnosis, procedural, and medication codes in insurance claims data, we were able to identify incident and prevalent IBD cases with high accuracy. These algorithms can be useful for the ascertainment of IBD cases in future studies.