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确保对医疗差错进行匿名研究的数据库设计:来自ASIPS协作组的报告

Database design to ensure anonymous study of medical errors: a report from the ASIPS Collaborative.

作者信息

Pace Wilson D, Staton Elizabeth W, Higgins Gregory S, Main Deborah S, West David R, Harris Daniel M

机构信息

Department of Family Medicine, University of Colorado Health Sciences Center, Aurora 80045-0508, USA.

出版信息

J Am Med Inform Assoc. 2003 Nov-Dec;10(6):531-40. doi: 10.1197/jamia.M1339. Epub 2003 Aug 4.

Abstract

Medical error reporting systems are important information sources for designing strategies to improve the safety of health care. Applied Strategies for Improving Patient Safety (ASIPS) is a multi-institutional, practice-based research project that collects and analyzes data on primary care medical errors and develops interventions to reduce error. The voluntary ASIPS Patient Safety Reporting System captures anonymous and confidential reports of medical errors. Confidential reports, which are quickly de-identified, provide better detail than do anonymous reports; however, concerns exist about the confidentiality of those reports should the database be subject to legal discovery or other security breaches. Standard database elements, for example, serial ID numbers, date/time stamps, and backups, could enable an outsider to link an ASIPS report to a specific medical error. The authors present the design and implementation of a database and administrative system that reduce this risk, facilitate research, and maintain near anonymity of the events, practices, and clinicians.

摘要

医疗差错报告系统是设计提高医疗保健安全性策略的重要信息来源。应用提高患者安全策略(ASIPS)是一个多机构、基于实践的研究项目,该项目收集和分析初级保健医疗差错数据,并开发减少差错的干预措施。自愿性的ASIPS患者安全报告系统收集医疗差错的匿名和保密报告。经过快速去识别处理的保密报告比匿名报告提供的细节更多;然而,如果数据库遭遇法律调查或其他安全漏洞,这些报告的保密性就会受到关注。标准的数据库元素,例如序列号、日期/时间戳和备份,可能会使外部人员将一份ASIPS报告与特定的医疗差错联系起来。作者介绍了一个数据库和管理系统的设计与实施,该系统降低了这种风险,便于开展研究,并使事件、医疗机构和临床医生几乎保持匿名状态。

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本文引用的文献

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Multicenter patient records research: security policies and tools.多中心患者记录研究:安全政策与工具
J Am Med Inform Assoc. 1999 Nov-Dec;6(6):435-43. doi: 10.1136/jamia.1999.0060435.
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Using Boolean reasoning to anonymize databases.使用布尔推理对数据库进行匿名化处理。
Artif Intell Med. 1999 Mar;15(3):235-54. doi: 10.1016/s0933-3657(98)00056-6.
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Cryptographic protection of health information: cost and benefit.健康信息的加密保护:成本与效益
Int J Biomed Comput. 1996 Oct;43(1-2):61-7. doi: 10.1016/s0020-7101(96)01228-7.

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