How is the electronic health record being used? Use of EHR data to assess physician-level variability in technology use
How is the electronic health record being used? Use of EHR data to assess physician-level variability in technology use
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DOI：
10.1136/amiajnl-2013-002627
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发表时间：
2014-11-01
影响因子：
6.4
通讯作者：
Kaushal, Rainu
中科院分区：
文献类型：
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作者：
Ancker, Jessica S.;Kern, Lisa M.;Kaushal, Rainu
背景电子健康记录(EHR)的影响研究结果喜忧参半，这可能是由于未测量的混杂因素，如使用电子健康记录功能的个体差异。目的收集医生级别的使用电子健康记录功能的差异、与其他预测因素的关联以及使用强度随时间的变化。方法使用2010年1月至2013年6月的商业电子健康记录数据，对有资格在联邦合格卫生中心网络中有意义使用的初级保健提供者进行回顾性队列研究，在此期间，该组织正在为有意义的使用做准备和处于有意义的使用的早期阶段。结果分析了112名医生和护士从业人员的数据，其中包括430 803名医生和99 649名患者。开发电子病历使用指标是为了捕获提供者如何访问和添加到患者数据(例如，问题列表更新)、使用临床决策支持(例如，对警报的响应)、沟通(例如，打印访问后摘要)以及使用小组管理选项(例如，查看小组报告)。提供商级别的可变性很高：例如，每个提供商每年遇到问题列表更新的平均比例在5%到60%之间。一些指标与提供者、患者或遭遇特征相关联。例如，新患者更新问题列表的可能性比现有患者更高，警报接受度与警报频率负相关。结论使用相同电子病历的提供者发展了个性化的电子病历功能使用模式。我们的结论是，在研究EHR对医疗质量和成本的影响时，医生级别的EHR功能的使用可能是一个有价值的额外预测指标。
Background Studies of the effects of electronic health records (EHRs) have had mixed findings, which may be attributable to unmeasured confounders such as individual variability in use of EHR features.Objective To capture physician-level variations in use of EHR features, associations with other predictors, and usage intensity over time.Methods Retrospective cohort study of primary care providers eligible for meaningful use at a network of federally qualified health centers, using commercial EHR data from January 2010 through June 2013, a period during which the organization was preparing for and in the early stages of meaningful use.Results Data were analyzed for 112 physicians and nurse practitioners, consisting of 430 803 encounters with 99 649 patients. EHR usage metrics were developed to capture how providers accessed and added to patient data (eg, problem list updates), used clinical decision support (eg, responses to alerts), communicated (eg, printing after-visit summaries), and used panel management options (eg, viewed panel reports). Provider-level variability was high: for example, the annual average proportion of encounters with problem lists updated ranged from 5% to 60% per provider. Some metrics were associated with provider, patient, or encounter characteristics. For example, problem list updates were more likely for new patients than established ones, and alert acceptance was negatively correlated with alert frequency.Conclusions Providers using the same EHR developed personalized patterns of use of EHR features. We conclude that physician-level usage of EHR features may be a valuable additional predictor in research on the effects of EHRs on healthcare quality and costs.