Artikel ; Online: Association between claims-based setting of diagnosis and treatment initiation among Medicare patients with hepatitis C.
2024
Abstract: Objective: To develop a claims-based algorithm to determine the setting of a disease diagnosis.: Data sources and study setting: Medicare enrollment and claims data from 2014 to 2019.: Study design: We developed a claims-based algorithm using ... ...
Abstract | Objective: To develop a claims-based algorithm to determine the setting of a disease diagnosis. Data sources and study setting: Medicare enrollment and claims data from 2014 to 2019. Study design: We developed a claims-based algorithm using facility indicators, revenue center codes, and place of service codes to identify settings where HCV diagnosis first appeared. When the first appearance was in a laboratory, we attempted to associate HCV diagnoses with subsequent clinical visits. Face validity was assessed by examining association of claims-based diagnostic settings with treatment initiation. Data collection/extraction methods: Patients newly diagnosed with HCV and continuously enrolled in traditional Medicare Parts A, B, and D (12 months before and 6 months after index diagnosis) were included. Principal findings: Among 104,454 patients aged 18-64 and 66,726 aged ≥65, 70.1% and 69%, respectively, were diagnosed in outpatient settings, and 20.2% and 22.7%, respectively in laboratory or unknown settings. Logistic regression revealed significantly lower odds of treatment initiation after diagnosis in emergency departments/urgent cares, hospitals, laboratories, or unclassified settings, than in outpatient visits. Conclusions: The algorithm identified the setting of HCV diagnosis in most cases, and found significant associations with treatment initiation, suggesting an approach that can be adapted for future claims-based studies. |
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Sprache | Englisch |
Erscheinungsdatum | 2024-05-21 |
Erscheinungsland | United States |
Dokumenttyp | Journal Article |
ZDB-ID | 410435-3 |
ISSN | 1475-6773 ; 0017-9124 |
ISSN (online) | 1475-6773 |
ISSN | 0017-9124 |
DOI | 10.1111/1475-6773.14330 |
Datenquelle | MEDical Literature Analysis and Retrieval System OnLINE |
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