Decision Making and Clinical Work of Test Result Follow-up in Health IT Settings

背景：在门诊环境中，未能随访异常检测结果是一个重要的安全问题， 往往会导致病人伤害和医疗事故索赔。电子健康记录（EHR）可以帮助确保可靠的 提供异常检测结果，但不保证采取适当的后续行动。我们 退伍军人健康管理局（VA）的一项工作显示，近8%的异常门诊检查结果 作为基于EHR的警报传输的患者在4周时缺乏随访。我们随后发现， 异常测试受多种技术因素（软件/硬件）和非技术因素的影响 因素（用户行为、工作流程、信息负载、政策和程序、培训和其他组织因素） 因素）。改善测试结果的后续工作将需要更好地理解后续工作流程如何与 电子健康记录支持的医疗保健的复杂的“社会技术”背景。特别重要的是要澄清如何 这些语境特征影响着认知过程，而认知过程是感知、理解和 及时处理异常发现。鉴于实验室检测结果报告是阶段的一个组成部分， 2有意义的使用，进一步探索基于EHR的测试结果后续的漏洞势在必行。 目的/方法：我们建议应用基于人为因素的框架来理解系统， 影响基于EHR的门诊测试结果随访的认知弱点。为了更好地定义 临床工作，影响决策在这方面，我们将使用一个概念模型，假定一套八个 社会技术方面，必须考虑在现实世界中使用的信息技术。在我们以前的工作， VA，我们的研究环境包括与3个非VA机构附属的诊所，以提高普遍性。在 目的1，我们将确定在基于电子健康档案的健康中影响测试结果随访过程的认知因素 系统.我们将进行记录审查，以确定最近的异常测试结果，并及时跟踪- 与订购测试的供应商进行认知任务分析访谈。我们亦会评估 与测试结果相关的基于EHR的警报的认知负荷。在目标2中，我们将描述临床 个人和团队对启用EHR的异常测试结果做出适当反应所需的工作 门诊设置。为了在每个站点绘制这些流程，我们将使用快速 评估技术（结构化观察、简短调查和关键信息提供者访谈）。我们 对这些数据的解释将包括考虑不同的社会技术因素（例如EHR设计， 工作流程和组织因素）相互作用并影响测试结果后续的认知工作。在目标3中， 将进行前瞻性的风险评估，以确定特定的工作流程和特点， 最容易在我们的研究中心内和研究中心之间发生故障的社会技术背景。这种基础 这项工作将使人们更好地了解遗漏测试结果的“基础科学”，并将阐明 未来的干预措施，以改善后续的异常测试结果在电子健康档案启用门诊设置。

Background: Failure to follow up abnormal test results is a significant safety concern in outpatient settings and often leads to patient harm and malpractice claims. Electronic health records (EHRs) can help ensure reliable delivery of abnormal test results, but they do not guarantee that this results in appropriate follow-up action. Our work in the Veterans Health Administration (VA) reveals that almost 8% of abnormal outpatient test results transmitted as EHR-based alerts lacked follow-up at 4 weeks. We subsequently found that follow-up of abnormal tests is influenced by multitude of technological factors (software/hardware) and non-technological factors (user behaviors, workflow, information load, policies and procedures, training and other organizational factors). Improving test result follow-up will require a better understanding of how follow-up processes fit within the complex "socio-technical" context of EHR-enabled health care. It is especially important to clarify how these contextual features influence the cognitive processes that are necessary to perceive, comprehend, and act on abnormal findings in a timely manner. Given that laboratory test result reporting is a component of Stage 2 meaningful use, further exploration of vulnerabilities in EHR-based test result follow-up is imperative. Objectives/Methods: We propose to apply human factors-based frameworks to understand system and cognitive vulnerabilities that affect EHR-based outpatient test result follow-up. To better define the context of clinical work that affects decision-making in this area, we will use a conceptual model that posits a set of eight socio-technical dimensions that must be considered in the real-world use of IT. Building on our prior work in the VA, our study settings include clinics affiliated with 3 non-VA institutions in order to improve generalizability. In Aim 1, we will identify the cognitive factors that affect test result follow-up processes in EHR-based health systems. We will conduct record reviews to identify recent abnormal test results with and without timely follow- up and conduct cognitive task analysis interviews with providers who ordered the tests. We will also assess the cognitive load of EHR-based alerts related to test results. In Aim 2, we will characterize the nature of clinical work required for individuals and teams to respond appropriately to abnormal test results in EHR-enabled outpatient settings. To map these processes at each site, we will collect qualitative data using rapid assessment techniques (structured observations, brief surveys, and key informant interviews). Our interpretation of these data will include consideration of how different socio-technical factors (e.g. EHR design, workflow, and organizational factors) interact and affect the cognitive work of test result follow-up. In Aim 3, we will conduct prospective risk assessments to characterize the particular work processes and features of the socio-technical context that are most vulnerable to failure within and across our study sites. This foundational work will lead to better understanding of the "basic science" of missed test results and will clarify targets for future interventions to improve follow-up of abnormal test results in EHR-enabled outpatient settings.