Assessing the Effect of Telemedicine on Physician EHR Work, Cognition, and Process Outcomes (ASPIRE)

评估远程医疗对医生 EHR 工作、认知和流程结果的影响 (ASPIRE)

基本信息

项目摘要

PROJECT SUMMARY The Coronavirus disease 2019 (COVID-19) pandemic dramatically altered healthcare delivery in persistent ways. To adhere to the physical distancing guidelines and to provide continuity of patient care, organizations shifted the primary modality of ambulatory care to telemedicine-based virtual encounters. This transition has altered the structure, management, and delivery of patient care—with large potential changes to patient-provider communication and availability of clinical information. For example, during telemedicine encounters clinicians can no longer conduct physical exams or obtain vitals that inform clinical reasoning and decision making in routine ambulatory evaluation and management (E&M) encounters. In turn, these factors may contribute to clinical uncertainty, and thereby alter how the clinician leverages the electronic health record (EHR). They may need to engage in additional chart review to fill information gaps, enter patient-generated health data, or send more follow-up communications. One or more of these changes serves to intensify EHR-based cognitive load as EHR activities and activity switching increase, both at the encounter level and cumulatively over the course of a workday. In turn, greater EHR-based cognitive load could contribute to suboptimal clinical decisions (e.g., more diagnostic tests or referrals) and more errors (e.g., wrong-patient orders). In the proposed Assessing the Effect of Telemedicine on Physician EHR Work, Cognition, and Process Outcomes (ASPIRE) project, we investigate the primary hypothesis that ambulatory telemedicine encounters in the COVID context are associated with increased EHR-based cognitive load among clinicians, and downstream suboptimal clinical decisions and more frequent errors. We leverage novel, EHR-based audit log data from a 3- year period spanning pre- and COVID-periods (March 2019 – February 2022) to directly measure clinicians' EHR activities in telemedicine and face-to-face encounters at two large academic medical centers (Washington University in St Louis and University of California, San Francisco). Using the COVID-19 pandemic as a natural experiment that dramatically increased ambulatory telemedicine encounters (more than 25-fold at the two health systems), our first aim will characterize the differences in EHR-based activities between face-to-face and telemedicine encounters. We will then construct a derivative measure of EHR activity switches (within and across encounters) as a proxy measure of cognitive load and evaluate the downstream impact of cognitive load on clinical decision making and wrong-patient errors. The findings from these aims will be leveraged in our final “design” aim that uses frontline clinician interviews and a national expert eDelphi process to elicit the EHR-based factors impacting telemedicine encounters and to identify potential design strategies to address associated challenges. The eDelphi process will focus on translating and prioritizing the identified design strategies into pragmatic goals to improve EHR support for telemedicine encounters.
项目总结 2019年冠状病毒病(新冠肺炎)大流行以持续的方式极大地改变了医疗服务。 为了遵守物理距离指南并提供患者护理的连续性,组织转移了 门诊护理的主要方式是基于远程医疗的虚拟会诊。这一过渡改变了 患者护理的结构、管理和交付--患者提供者可能会发生巨大变化 临床信息的沟通和可用性。例如,在远程医疗与临床医生会面期间 不能再进行体检或获取为临床推理和决策提供信息的生命体征 常规门诊评估和管理(E&M)会诊。反过来,这些因素可能会导致 临床不确定性,从而改变临床医生利用电子健康记录(EHR)的方式。他们可能会 需要进行额外的图表审查以填补信息空白,输入患者生成的健康数据,或发送 更多的后续沟通。这些变化中的一个或多个有助于强化基于EHR的认知负荷 随着EHR活动和活动切换的增加,无论是在遭遇层面上还是在整个过程中积累起来 一天的工作。反过来,更大的基于电子病历的认知负荷可能会导致次优的临床决策(例如, 更多的诊断测试或转诊)和更多的错误(例如,错误的患者订单)。 在建议的评估远程医疗对医生电子病历工作、认知和过程的影响中 结果(ASPIRE)项目,我们调查了门诊远程医疗遇到的主要假设 COVID背景与临床医生和下游患者中基于EHR的认知负荷增加相关 不太理想的临床决策和更频繁的错误。我们利用新的、基于EHR的审核日志数据,这些数据来自3- 直接测量临床医生EHR的年份(2019年3月至2022年2月) 在两个大型学术医疗中心(华盛顿)开展远程医疗活动和面对面交流 圣路易斯大学和加州大学旧金山分校)。将新冠肺炎大流行视为一种自然现象 极大地增加了非卧床远程医疗接诊次数的实验(超过25倍的两个健康 系统),我们的第一个目标将描述面对面和面对面的基于电子病历的活动的区别 远程医疗相遇。然后我们将构建EHR活动开关(内部和跨区域)的派生度量 遭遇)作为认知负荷的代理测量,并评估认知负荷对 临床决策和错误的病人错误。来自这些目标的发现将在我们的期末考试中发挥杠杆作用 使用一线临床医生访谈和国家专家eDelphi流程来引出基于eHR的 影响远程医疗接触的因素,并确定潜在的设计战略以解决相关问题 挑战。EDelphi流程将侧重于将已确定的设计战略转化为 改善电子病历对远程医疗会诊的支持的务实目标。

项目成果

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JULIA Rose ADLER-MILSTEIN其他文献

JULIA Rose ADLER-MILSTEIN的其他文献

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{{ truncateString('JULIA Rose ADLER-MILSTEIN', 18)}}的其他基金

Advancing Coordination of Home and Community based Services for the ADRD Population
促进针对 ADRD 人群的家庭和社区服务的协调
  • 批准号:
    10594544
  • 财政年份:
    2022
  • 资助金额:
    $ 34.04万
  • 项目类别:
Assessing the Long-term Impact of COVID-induced Telemedicine Expansion on Dementia Care
评估新冠肺炎引起的远程医疗扩展对痴呆症护理的长期影响
  • 批准号:
    10447947
  • 财政年份:
    2022
  • 资助金额:
    $ 34.04万
  • 项目类别:
Advancing Coordination of Home and Community based Services for the ADRD Population
促进针对 ADRD 人群的家庭和社区服务的协调
  • 批准号:
    10370234
  • 财政年份:
    2022
  • 资助金额:
    $ 34.04万
  • 项目类别:
Assessing the Effect of Telemedicine on Physician EHR Work, Cognition, and Process Outcomes (ASPIRE)
评估远程医疗对医生 EHR 工作、认知和流程结果的影响 (ASPIRE)
  • 批准号:
    10278832
  • 财政年份:
    2021
  • 资助金额:
    $ 34.04万
  • 项目类别:
Assessing the Effect of Telemedicine on Physician EHR Work, Cognition, and Process Outcomes (ASPIRE)
评估远程医疗对医生 EHR 工作、认知和流程结果的影响 (ASPIRE)
  • 批准号:
    10449362
  • 财政年份:
    2021
  • 资助金额:
    $ 34.04万
  • 项目类别:
Health Information Exchange to Improve Outcomes in Complex Older Patients
健康信息交换可改善复杂老年患者的治疗结果
  • 批准号:
    10385686
  • 财政年份:
    2019
  • 资助金额:
    $ 34.04万
  • 项目类别:
Health Information Exchange to Improve Outcomes in Complex Older Patients
健康信息交换可改善复杂老年患者的治疗结果
  • 批准号:
    10565929
  • 财政年份:
    2019
  • 资助金额:
    $ 34.04万
  • 项目类别:
Health Information Exchange to Improve Outcomes in Complex Older Patients
健康信息交换可改善复杂老年患者的治疗结果
  • 批准号:
    9899910
  • 财政年份:
    2019
  • 资助金额:
    $ 34.04万
  • 项目类别:
Health Information Exchange to Improve Outcomes in Complex Older Patients
健康信息交换可改善复杂老年患者的治疗结果
  • 批准号:
    10092887
  • 财政年份:
    2019
  • 资助金额:
    $ 34.04万
  • 项目类别:
Synergies and Sequencing in Delivery and Payment Reform: Understanding What Works
交付和支付改革中的协同效应和排序:了解什么是有效的
  • 批准号:
    9446507
  • 财政年份:
    2017
  • 资助金额:
    $ 34.04万
  • 项目类别:

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