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医学数据挖掘新策略,第 1 部分:基于动态和绩效的报销。

New strategies for medical data mining, part 1: dynamic and performance-based reimbursement.

机构信息

Department of Diagnostic Imaging, Baltimore VA Medical Center, 22 N Greene Street, Baltimore, MD 21201, USA.

出版信息

J Am Coll Radiol. 2010 Dec;7(12):975-9. doi: 10.1016/j.jacr.2010.06.007.

Abstract

The current professional reimbursement model within medicine was created more than 20 years ago in response to physician dissatisfaction and health care inflationary pressures. Despite many resulting improvements, several deficiencies currently exist within the current reimbursement model, related to transparency, accountability, and quality. As the tenets of evidence-based medicine and pay for performance become ingrained within health care delivery, it would be beneficial to modify the existing reimbursement model to reflect these principles. The opportunity to accomplish this goal is advanced through the continued evolution of information systems technologies and data mining. The author discusses the existing deficiencies in medical reimbursement and makes a number of recommendations for improvement. The ultimate goal is to incorporate objective and standardized data into a transparent and readily accessible database, which can be used to enhance performance, education, and informed decision making.

摘要

当前医学领域的专业报销模式是 20 多年前为应对医生的不满和医疗通胀压力而设立的。尽管取得了许多改进,但当前的报销模式仍存在一些缺陷,涉及透明度、问责制和质量。随着循证医学和按绩效付费的原则在医疗服务中得到巩固,修改现有的报销模式以反映这些原则将是有益的。通过信息系统技术和数据挖掘的持续发展,为实现这一目标提供了机会。作者讨论了医疗报销中存在的缺陷,并提出了一些改进建议。最终目标是将客观和标准化的数据纳入透明且易于访问的数据库,以提高绩效、教育和决策水平。

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