Identifying Physicians’ User Experience (UX) Pain Points in Using Electronic Health Record (EHR) Systems

Healthcare institutions have migrated to online electronic documentation through the means of Electronic Health Record (EHR) systems. Physicians rely on these systems to support their various clinical work processes, such as entering clinical orders, reviewing essential clinical data, and making important medical decisions using reporting analytics. Although EHR systems appear to be useful and have known advantages over paper records, studies suggest there are persistent user interface design problems that may hinder physician productivity. The study focused on the research problem that EHR system designs create productivity problems for physician users who frequently report that system workflows are inefficient and do not map to their clinical process needs. Although researchers have examined EHR system adaptation and user interface design with various stakeholders, research is limited on the lived experiences of physicians who use the system. A few studies have focused on quantifying the factors that describe the phenomena of “meaningful use” of EHR systems. A qualitative approach to studying the phenomenon of physicians\u27 use of EHR systems is understudied and is relevant to investigate given EHR systems have become commonplace tools in clinical settings. An interpretive phenomenological analysis (IPA) study was conducted with the goal to discover what emergency room physicians describe as the pain points of their user experiences with EHR systems, which may include many different experiences to be uncovered, and their perspectives about how they manage the difficulty of system tasks and demands. Eight participants who represented a purposeful sample were recruited from one hospital in the Southeast region of the United States and participated in semi-structured interviews with open-ended questions. The data derived from the personal lived experiences of the participants were reviewed and analyzed through a step-by-step analytical process to develop five super-ordinate themes: Historical Chart Review, Inadequate Note Documentation, Difficult Order Entry, Patient Throughput Barriers, and Poor System Performance. The findings reveal consistencies with previous research that suggests physicians experience mental burden and burnout using EHR systems due to task complexity, task demand, and inefficiencies of system design. The findings have multiple implications for information technology (IT) system designers, healthcare administrators, and physician end users. This study provides future research opportunities to investigate the experiences of individuals who work in a different specialized area of the hospital, such as the intensive care unit (ICU)

Healing the Healers: Legal Remedies for Physician Burnout

A career as a doctor was long considered to be among the best professional paths that one could pursue. But medicine may no longer be the sought-after career that it once was. All too often, doctors, struggling with the demands of electronic health record systems and a myriad of administrative and regulatory responsibilities, find that they fail to derive much joy from their work and become victims of burnout. Physician burnout is an acute concern in the medical community, with forty-four percent of doctors reporting that they suffer from it. Physician burnout is a public health threat. Doctors who are profoundly distressed cannot provide their patients with the highest quality of care

A dynamic visual analytics framework for complex temporal environments

Introduction: Data streams are produced by sensors that sample an external system at a periodic interval. As the cost of developing sensors continues to fall, an increasing number of data stream acquisition systems have been deployed to take advantage of the volume and velocity of data streams. An overabundance of information in complex environments have been attributed to information overload, a state of exposure to overwhelming and excessive information. The use of visual analytics provides leverage over potential information overload challenges. Apart from automated online analysis, interactive visual tools provide significant leverage for human-driven trend analysis and pattern recognition. To facilitate analysis and knowledge discovery in the space of multidimensional big data, research is warranted for an online visual analytic framework that supports human-driven exploration and consumption of complex data streams. Method: A novel framework was developed called the temporal Tri-event parameter based Dynamic Visual Analytics (TDVA). The TDVA framework was instantiated in two case studies, namely, a case study involving a hypothesis generation scenario, and a second case study involving a cohort-based hypothesis testing scenario. Two evaluations were conducted for each case study involving expert participants. This framework is demonstrated in a neonatal intensive care unit case study. The hypothesis generation phase of the pipeline is conducted through a multidimensional and in-depth one subject study using PhysioEx, a novel visual analytic tool for physiologic data stream analysis. The cohort-based hypothesis testing component of the analytic pipeline is validated through CoRAD, a visual analytic tool for performing case-controlled studies. Results: The results of both evaluations show improved task performance, and subjective satisfaction with the use of PhysioEx and CoRAD. Results from the evaluation of PhysioEx reveals insight about current limitations for supporting single subject studies in complex environments, and areas for future research in that space. Results from CoRAD also support the need for additional research to explore complex multi-dimensional patterns across multiple observations. From an information systems approach, the efficacy and feasibility of the TDVA framework is demonstrated by the instantiation and evaluation of PhysioEx and CoRAD. Conclusion: This research, introduces the TDVA framework and provides results to validate the deployment of online dynamic visual analytics in complex environments. The TDVA framework was instantiated in two case studies derived from an environment where dynamic and complex data streams were available. The first instantiation enabled the end-user to rapidly extract information from complex data streams to conduct in-depth analysis. The second allowed the end-user to test emerging patterns across multiple observations. To both ends, this thesis provides knowledge that can be used to improve the visual analytic pipeline in dynamic and complex environments

Modeling Clinicians’ Cognitive and Collaborative Work in Post-Operative Hospital Care

abstract: Clinicians confront formidable challenges with information management and coordination activities. When not properly integrated into clinical workflow, technologies can further burden clinicians’ cognitive resources, which is associated with medical errors and risks to patient safety. An understanding of workflow is necessary to redesign information technologies (IT) that better support clinical processes. This is particularly important in surgical care, which is among the most clinical and resource intensive settings in healthcare, and is associated with a high rate of adverse events. There are a growing number of tools to study workflow; however, few produce the kinds of in-depth analyses needed to understand health IT-mediated workflow. The goals of this research are to: (1) investigate and model workflow and communication processes across technologies and care team members in post-operative hospital care; (2) introduce a mixed-method framework, and (3) demonstrate the framework by examining two health IT-mediated tasks. This research draws on distributed cognition and cognitive engineering theories to develop a micro-analytic strategy in which workflow is broken down into constituent people, artifacts, information, and the interactions between them. It models the interactions that enable information flow across people and artifacts, and identifies dependencies between them. This research found that clinicians manage information in particular ways to facilitate planned and emergent decision-making and coordination processes. Barriers to information flow include frequent information transfers, clinical reasoning absent in documents, conflicting and redundant data across documents and applications, and that clinicians are burdened as information managers. This research also shows there is enormous variation in how clinicians interact with electronic health records (EHRs) to complete routine tasks. Variation is best evidenced by patterns that occur for only one patient case and patterns that contain repeated events. Variation is associated with the users’ experience (EHR and clinical), patient case complexity, and a lack of cognitive support provided by the system to help the user find and synthesize information. The methodology is used to assess how health IT can be improved to better support clinicians’ information management and coordination processes (e.g., context-sensitive design), and to inform how resources can best be allocated for clinician observation and training.Dissertation/ThesisDoctoral Dissertation Biomedical Informatics 201