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.
A significant number of patients with abnormal test results fall through the cracks of the health care system and experience delays in diagnosis and treatment. Although electronic health records enhance the communication of abnormal test results, they do not guarantee the prompt follow-up that is required for timely care. We propose to study test result follow-up practices across healthcare institutions that use various electronic health record systems to understand why abnormal test results are missed.
|Kwan, Janice L; Singh, Hardeep (2017) Assigning responsibility to close the loop on radiology test results. Diagnosis (Berl) 4:173-177|
|Singh, Hardeep; Schiff, Gordon D; Graber, Mark L et al. (2017) The global burden of diagnostic errors in primary care. BMJ Qual Saf 26:484-494|
|Singh, Hardeep; Graber, Mark L; Hofer, Timothy P (2016) Measures to Improve Diagnostic Safety in Clinical Practice. J Patient Saf :|
|Sittig, D F; Wright, A; Ash, J et al. (2016) New Unintended Adverse Consequences of Electronic Health Records. Yearb Med Inform :7-12|
|Medford-Davis, Laura; Park, Elizabeth; Shlamovitz, Gil et al. (2016) Diagnostic errors related to acute abdominal pain in the emergency department. Emerg Med J 33:253-9|
|Okafor, Nnaemeka; Payne, Velma L; Chathampally, Yashwant et al. (2016) Using voluntary reports from physicians to learn from diagnostic errors in emergency medicine. Emerg Med J 33:245-52|
|Giardina, Traber Davis; Sarkar, Urmimala; Gourley, Gato et al. (2016) Online public reactions to frequency of diagnostic errors in US outpatient care. Diagnosis (Berl) 3:17-22|
|Murphy, Daniel R; Meyer, Ashley N D; Russo, Elise et al. (2016) The Burden of Inbox Notifications in Commercial Electronic Health Records. JAMA Intern Med 176:559-60|
|Meyer, Ashley N D; Longhurst, Christopher A; Singh, Hardeep (2016) Crowdsourcing Diagnosis for Patients With Undiagnosed Illnesses: An Evaluation of CrowdMed. J Med Internet Res 18:e12|
|Singh, Hardeep; Sittig, Dean F (2016) Measuring and improving patient safety through health information technology: The Health IT Safety Framework. BMJ Qual Saf 25:226-32|
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