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- W2995016142 abstract "The increasing reliance on real-world evidence (RWE) is a challenge when considering health economic (HE) evaluations in precision oncology due to each patient’s variability in genetic characteristics and treatment history. The objective of this study was to assess the capabilities of US-based retrospective data assets to inform HE modeling studies in precision oncology. A comparative landscape assessment (CLA) was conducted using US-based RWE data assets including Pharmetrics Plus (PMTX+), Ambulatory Electronic Medical Record (AEMR), Oncology EMR (OEMR), Prescription Claims (Rx), Professional Fee Claims Data (Dx) and Charge Data Master (CDM). Precision oncology focuses on individual patient’s treatment by mutation and stratification in relation to disease susceptibility, diagnosis, prognosis, and treatment response. To assess data availability in this area, the CLA included core HE modeling inputs: epidemiology, patient and disease characteristics, treatment patterns, costs (e.g., treatment, resource use, disease management), and adverse events (AEs). HE modeling inputs in precision oncology requires patient data with detailed health records including information on mutations or other genetic alterations. Information related to patient clinical characteristics (etiology, genetics, performance scores, companion diagnostics use) can be rare and unstructured, so studies require novel approaches using high-quality linked databases. Epidemiology, patient/disease characteristics, resource use, AEs (PMTX+, EMRs, CDM, Dx), treatment patterns (PMTX+, Rx) and control cohorts information (EMRs) are reported in various data assets, however information on genotypes are not consistently reported in the US. Observational data needed for HE models in precision oncology may not be satisfied with a unique RWE data source, but commonly requires linkage of databases. Understanding both the research question and available data assets to rapidly query a data set and identify patients should guide the choice of observational data to use in HE modeling. The possibility of enriching retrospective databases using patient/provider surveys should also be considered." @default.
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- W2995016142 date "2019-11-01" @default.
- W2995016142 modified "2023-10-18" @default.
- W2995016142 title "PCN527 US HEALTHCARE DATABASES FOR HEALTH ECONOMIC MODELING IN PRECISION MEDICINE: AN ONCOLOGY-BASED COMPARATIVE LANDSCAPE ASSESSMENT" @default.
- W2995016142 doi "https://doi.org/10.1016/j.jval.2019.09.718" @default.
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