ITERATIVE MODELING AND EVALUATION OF THE CLINICAL AND ECONOMIC OUTCOMES OF PAC

PAC 临床和经济结果的迭代建模和评估

• 批准号: 6102654
• 负责人: CURTIS P LANGLOTZ
• 金额: $ 21.3万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-01-01 至 1999-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6102654
• 关键词: clinical research; computer system design /evaluation; health care cost /financing; health care facility information system; human data; mathematical model; model design /development; radiology

The aims of this project are to measure, estimate, and model the effect of a series of specific interventions involving the implementation of a Picture Archiving and Communication System (PACS) on the health outcomes of patients and on the finances of a radiology practice, clinical unit, and medical center. The three principal components of our approach are (1) develop a financial model from estimated and actual expenses before and after each intervention, (2) derive multivariate models that estimate the independent effects of PACS interventions on health outcome surrogates, and (3) construct a cost effectiveness model that integrates incremental costs and health outcomes associated with each intervention in a single metric. First, we will estimate the cost of equipment, supplies, and personnel from actual expense information (prior to PACS interventions), and from actual and projected needs of the radiology department (after PACS interventions). These data will be used to develop an incremental direct-cost model of PACS from the perspective of a health system. Next, we will measure readily available surrogate variables that are likely to correlate highly with the health outcomes of patients: the rate of inpatient admission, the length of inpatient stay (for admitted patients), the need for and cost of subsequent health care. Multivariate analysis will be used to detect whether the outcome surrogates are influenced by the interventions, and by other factors known to influence these variables (e.g., case mix). Our hypothesis is that, after controlling for the underlying clinical and demographic differences among patients, patients imaged after a PACS intervention compared to those imaged before the intervention, will have shorter lengths of stay, shorter ED visits, shorter exam performance times, and decreased costs of care. Finally, cost-effectiveness metrics will be computed as cost per diagnostic value, cost per increment of process improvement, and as cost per health outcome surrogate. We will perform sensitivity analyses of the combined model to test the robustness of the model, to assess the applicability of the model to other health care facilities, to reveal the variables on which the conclusions depend, and to suggest implementation strategies that may improve operational efficiency and cost-effectiveness.

本项目的目的是测量、估计和模拟 一系列具体干预措施， 一个关于健康的图像存储和通信系统（PACS） 病人的结果和放射学实践的财务状况， 临床单位和医疗中心。 的三个主要组成部分 我们的方法是（1）从估计和实际情况中建立一个财务模型 每次干预前后的费用，（2）得出多变量 评估PACS干预措施对以下方面的独立影响的模型 健康结果替代物，以及（3）构建成本效益模型 将增量成本和健康结果与 每个干预都是一个指标。 首先，我们将估算设备、供应品和人员的成本 从实际费用信息（PACS干预之前），以及从 放射科的实际和预计需求（PACS后 干预）。 这些数据将用于开发一个增量 PACS的直接成本模型从卫生系统的角度。 接下来，我们将测量现成的替代变量， 可能与患者的健康结果高度相关： 住院率、住院时间（入院 患者），后续医疗保健的需求和成本。 多变量分析将用于检测结果是否 代理人受到干预措施和其他因素的影响 已知会影响这些变量（例如，病例组合）。我们的假设是 在控制了潜在的临床和人口统计学因素后， 患者之间的差异，PACS干预后成像的患者 与干预前的成像相比， 住院时间更长，艾德访视时间更短，检查时间更短，以及 降低护理成本。 最后，成本效益指标将是 按每诊断值成本、每过程增量成本计算 改善，并作为每个健康结果替代成本。 我们将执行 敏感性分析的组合模型，以测试的鲁棒性， 模型，以评估该模型对其他医疗保健的适用性 工具，以揭示结论所依赖的变量，以及 提出实施战略， 效率和成本效益。