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

描述(申请人提供)：背景：未能跟进异常检测结果在门诊环境中是一个重大的安全问题，经常导致患者伤害和医疗事故索赔。电子健康记录(EHR)有助于确保可靠地提供异常检测结果，但不能保证这会导致适当的后续行动。 我们在退伍军人健康管理局(VA)的工作显示，以EHR为基础的警报传输的异常门诊测试结果中，近8%在4周时缺乏随访。我们随后发现，异常测试的跟踪受到多种技术因素(软件/硬件)和非技术因素(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)的影响。改善检测结果的后续工作需要更好地了解后续流程如何与 电子病历支持的医疗保健的复杂“社会-技术”背景。特别重要的是要阐明这些背景特征如何影响认知过程，而认知过程是及时感知、理解异常发现并对其采取行动所必需的。鉴于实验室检测结果报告是第二阶段有意义使用的一个组成部分，进一步探索基于电子病历的检测结果后续行动中的漏洞势在必行。目的/方法：我们建议应用基于人的因素的框架来理解影响基于EHR的门诊测试结果的系统和认知脆弱性。为了更好地定义影响这一领域决策的临床工作的内容，我们将使用一个概念模型，该模型假设了在现实世界中使用IT时必须考虑的八个社会技术维度。在我们先前在退伍军人管理局工作的基础上，我们的研究设置包括3个非A机构的附属诊所，以提高推广能力。在目标1中，我们将确定在基于电子病历的卫生系统中影响测试结果跟踪过程的认知因素。我们将进行记录审查，以确定最近的异常测试结果是否及时跟进，并与订购测试的供应商进行认知任务分析访谈。我们还将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，我们将描述个人和团队在启用EHR的门诊环境中对异常测试结果做出适当反应所需的临床工作的性质。为了绘制出每个站点的这些流程，我们将使用快速评估技术(结构化观察、简要调查和关键线人访谈)收集定性数据。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)如何相互作用并影响测试结果后续的认知工作。在目标3中，e将进行前瞻性风险评估，以确定在我们的研究地点内和整个研究地点内最容易发生故障的特定工作流程和社会技术背景的特点。这项基础性工作将有助于更好地理解遗漏检测结果的“基础科学”，并将明确未来干预措施的目标，以改善启用电子病历的门诊环境中异常检测结果的跟踪。

DESCRIPTION (provided by applicant): 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 contex 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-A institutions in order to improve generalizability. In Aim 1, we will identify the cognitive factorsthat 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, e 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.