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临床护理中预期异常情况的处理:调查临床医生在电子健康记录系统中使用“退出策略”的情况。

Handling anticipated exceptions in clinical care: investigating clinician use of 'exit strategies' in an electronic health records system.

机构信息

School of Public Health Department of Health Management and Policy, School of Information, University of Michigan, Ann Arbor, Michigan 48109-2029, USA.

出版信息

J Am Med Inform Assoc. 2011 Nov-Dec;18(6):883-9. doi: 10.1136/amiajnl-2011-000118. Epub 2011 Jun 14.

Abstract

Unpredictable yet frequently occurring exception situations pervade clinical care. Handling them properly often requires aberrant actions temporarily departing from normal practice. In this study, the authors investigated several exception-handling procedures provided in an electronic health records system for facilitating clinical documentation, which the authors refer to as 'data entry exit strategies.' Through a longitudinal analysis of computer-recorded usage data, the authors found that (1) utilization of the exit strategies was not affected by postimplementation system maturity or patient visit volume, suggesting clinicians' needs to 'exit' unwanted situations are persistent; and (2) clinician type and gender are strong predictors of exit-strategy usage. Drilldown analyses further revealed that the exit strategies were judiciously used and enabled actions that would be otherwise difficult or impossible. However, many data entries recorded via them could have been 'properly' documented, yet were not, and a considerable proportion containing temporary or incomplete information was never subsequently amended. These findings may have significant implications for the design of safer and more user-friendly point-of-care information systems for healthcare.

摘要

临床护理中充斥着难以预测但又经常出现的异常情况。妥善处理这些情况通常需要采取异常的行动,暂时偏离正常的操作流程。在这项研究中,作者研究了电子病历系统中提供的几种异常处理程序,以方便临床文档记录,作者将这些程序称为“数据输入出口策略”。通过对计算机记录的使用数据进行纵向分析,作者发现:(1)出口策略的使用不受实施后系统成熟度或患者就诊量的影响,这表明临床医生需要“退出”不需要的情况的需求是持续存在的;(2)临床医生类型和性别是出口策略使用的强有力预测因素。深入分析进一步表明,出口策略被明智地使用,并支持了原本难以或不可能完成的操作。然而,通过这些策略记录的许多数据条目本来可以“正确”记录,但却没有记录,并且相当一部分包含临时或不完整的信息从未被修改过。这些发现可能对设计更安全、更用户友好的医疗保健即时信息系统具有重要意义。

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