Section of Cancer Economics and Policy, Department of Health Services Research, The University of Texas M. D. Anderson Cancer Center, Houston, TX.
Division of Biostatistics, Washington University School of Medicine in St. Louis, MO.
Semin Radiat Oncol. 2019 Oct;29(4):348-353. doi: 10.1016/j.semradonc.2019.05.009.
Administrative claims data are big data generated from healthcare encounters. Claims data contain information on insurance payment as well as clinical diagnoses and procedure codes to ascertain medical conditions and treatments, making them valuable sources for economic evaluation research. This paper offers an introductory overview of the use of claims data for oncology-related cost-of-illness, cost comparison, and cost-effectiveness analyses. We reviewed analytical methods commonly employed in these analyses, such as the phase of care approach and net costing method for cost-of-illness studies, propensity score matching methods for cost comparison studies, and net benefit regression models for cost-effectiveness studies. We used published studies to explain each method and to discuss methodological challenges of conducting economic studies using claims data.
行政索赔数据是从医疗保健中产生的大数据。索赔数据包含有关保险支付以及临床诊断和程序代码的信息，以确定医疗状况和治疗方法，这使得它们成为经济评估研究的有价值的来源。本文对索赔数据在癌症相关疾病成本、成本比较和成本效益分析中的应用进行了介绍性概述。我们审查了这些分析中常用的分析方法，如疾病成本研究中的治疗阶段方法和净成本法、成本比较研究中的倾向评分匹配方法以及成本效益研究中的净效益回归模型。我们使用已发表的研究来解释每种方法，并讨论使用索赔数据进行经济研究的方法学挑战。
