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数据丰富、信息匮乏(DRIP)综合征:有治疗方法吗?

Data rich, information poor (DRIP) syndrome: is there a treatment?

作者信息

Goodwin S

出版信息

Radiol Manage. 1996 May-Jun;18(3):45-9.

Abstract

DRIP (data rich, information poor) syndrome is paralyzing the performance improvement efforts of many healthcare organizations. Symptoms of DRIP syndrome include the use of an abundance of indicators and the predominant use of a retrospective medical record review to collect data. Often, too many indicators are used because the organization is still subscribing to a traditional quality assurance methodology for performance improvement. In these cases, quality assurance programs monitor multiple areas of performance assuming that, except for occasional outliers, the results will be acceptable. Another cause of an unmanageable number of indicators may be a lack of understanding of JCAHO measurement requirements. The ¿prescription¿ includes changing to a continuous quality improvement culture, learning measurement requirements, inventorying current data collection to identify and eliminate useless data and aligning data collection with the goals and objectives of the organization. An organization should collect only data that is required to improve performance and meet accreditation and regulatory requirements. Data collection should be automated and built into work processes as much as possible. Ideally, a well-integrated computer system offers access to real-time information and permits timely or even proactive performance.

摘要

数据丰富但信息匮乏(DRIP)综合征正使许多医疗保健机构的绩效改进工作陷入瘫痪。DRIP综合征的症状包括使用大量指标以及主要通过回顾性病历审查来收集数据。通常,使用过多指标是因为该机构仍遵循传统的质量保证方法来进行绩效改进。在这些情况下,质量保证计划会监控多个绩效领域,假定除了偶尔的异常值外,结果将是可接受的。指标数量难以管理的另一个原因可能是对联合委员会国际部(JCAHO)测量要求缺乏了解。“处方”包括转变为持续质量改进文化、了解测量要求、清查当前的数据收集情况以识别和消除无用数据,以及使数据收集与机构的目标和宗旨保持一致。一个机构应该只收集为改进绩效以及满足认证和监管要求所需的数据。数据收集应尽可能自动化并融入工作流程。理想情况下,一个集成良好的计算机系统能够提供实时信息访问,并允许及时甚至主动地开展绩效工作。

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