Based on our analysis of descriptions provided by four EHR vendors on their EHR usability efforts, we provide three recommendations aimed at improving the usability of health information technology ...and reducing clinician burnout. First, EHR vendors need to dedicate increased attention to the design of the entire sociotechnical (work) system, including the EHR technology and its usability as well as the interactions of the technology with other system elements. Second, EHR vendors need to deepen and broaden their understanding of the work of clinicians and care teams by using diverse and mixed method. Third, in collaboration with health care organizations, EHR vendors should engage in cycles of continuous design and learning in order to improve the usability of health IT.
Abstract
Delivering high-quality, patient-centered cancer care remains a challenge. Both the National Academy of Medicine and the American Society of Clinical Oncology recommend shared decision ...making to improve patient-centered care, but widespread adoption of shared decision making into clinical care has been limited. Shared decision making is a process in which a patient and the patient’s health-care professional weigh the risks and benefits of different options and come to a joint decision on the best course of action for that patient on the basis of their values, preferences, and goals for care. Patients who engage in shared decision making report higher quality of care, whereas patients who are less involved in these decisions have statistically significantly higher decisional regret and are less satisfied. Decision aids can improve shared decision making—for example, by eliciting patient values and preferences that can then be shared with clinicians and by providing patients with information that may influence their decisions. However, integrating decision aids into the workflows of routine care is challenging. In this commentary, we explore 3 workflow-related barriers to shared decision making: the who, when, and how of decision aid implementation in clinical practice. We introduce readers to human factors engineering and demonstrate its potential value to decision aid design through a case study of breast cancer surgical treatment decision making. By better employing the methods and principles of human factors engineering, we can improve decision aid integration, shared decision making, and ultimately patient-centered cancer outcomes.
In the coming years, artificial intelligence (AI) will pervade almost every aspect of the health care delivery system. AI has the potential to improve patient safety (e.g., diagnostic accuracy) as ...well as reduce the burden on clinicians (e.g., documentation-related workload); however, these benefits are yet to be realized. AI is only one element of a larger sociotechnical system that needs to be considered for effective AI application. In this paper, we describe the current challenges of integrating AI into clinical care and propose a sociotechnical systems (STS) approach for AI design and implementation. We demonstrate the importance of an STS approach through a case study on the design and implementation of a clinical decision support (CDS). In order for AI to reach its potential, the entire work system as well as clinical workflow must be systematically considered throughout the design of AI technology.
Objective
To evaluate the usability and use of human factors (HF)–based clinical decision support (CDS) implemented in the emergency department (ED).
Background
Clinical decision support can improve ...patient safety; however, the acceptance and use of CDS has faced challenges. Following a human-centered design process, we designed a CDS to support pulmonary embolism (PE) diagnosis in the ED. We demonstrated high usability of the CDS during scenario-based usability testing. We implemented the HF-based CDS in one ED in December 2018.
Method
We conducted a survey of ED physicians to evaluate the usability and use of the HF-based CDS. We distributed the survey via Qualtrics, a web-based survey platform. We compared the computer system usability questionnaire scores of the CDS between those collected in the usability testing to use of the CDS in the real environment. We asked physicians about their acceptance and use of the CDS, barriers to using the CDS, and areas for improvement.
Results
Forty-seven physicians (56%) completed the survey. Physicians agreed that diagnosing PE is a major problem and risk scores can support the PE diagnostic process. Usability of the CDS was reported as high, both in the experimental setting and the real clinical setting. However, use of the CDS was low. We identified several barriers to the CDS use in the clinical environment, in particular a lack of workflow integration.
Conclusion
Design of CDS should be a continuous process and focus on the technology’s usability in the context of the broad work system and clinician workflow.
Abstract Objective Decision support can improve shared decision-making for breast cancer treatment, but workflow barriers have hindered widespread use of these tools. The goal of this study was to ...understand the workflow among breast cancer teams of clinicians, patients, and their family caregivers when making treatment decisions and identify design guidelines for informatics tools to better support treatment decision-making. Materials and Methods We conducted observations of breast cancer clinicians during routine clinical care from February to August 2022. Guided by the work system model, a human factors engineering model that describes the elements of work, we recorded all aspects of clinician workflow using a tablet and smart pencil. Observation notes were transcribed and uploaded into Dedoose. Two researchers inductively coded the observations. We identified themes relevant to the design of decision support that we classified into the 4 components of workflow (ie, flow of information, tasks, tools and technologies, and people). Results We conducted 20 observations of breast cancer clinicians (total: 79 hours). We identified 10 themes related to workflow that present challenges and opportunities for decision support design. We identified approximately 48 different decisions discussed during breast cancer visits. These decisions were often interdependent and involved collaboration across the large cancer treatment team. Numerous patient-specific factors (eg, work, hobbies, family situation) were discussed when making treatment decisions as well as complex risk and clinical information. Patients were frequently asked to remember and relay information across the large cancer team. Discussion and Conclusion Based on these findings, we proposed design guidelines for informatics tools to support the complex workflows involved in breast cancer care. These guidelines should inform the design of informatics solutions to better support breast cancer decision-making and improve patient-centered cancer care.
Numerous challenges with the implementation, acceptance, and use of health IT are related to poor usability and a lack of integration of the technologies into clinical workflow, and have, therefore, ...limited the potential of these technologies to improve patient safety. We propose a definition and conceptual model of health IT workflow integration. Using interviews of 12 emergency department (ED) physicians, we identify 134 excerpts of barriers and facilitators to workflow integration of a human factors (HF)-based clinical decision support (CDS) implemented in the ED. Using data on these 134 barriers and facilitators, we distinguish 25 components of workflow integration of the CDS, which are described according to four dimensions of workflow integration: time, flow, scope of patient journey, and level. The proposed definition and conceptual model of workflow integration can be used to inform health IT design; this is the purpose of the proposed checklist that can help to ensure consideration of workflow integration during the development of health IT.
•We propose a definition and conceptual model of workflow integration of health IT.•We identify barriers and facilitators to workflow integration of a CDS in the ED.•We describe 25 components of workflow integration of a CDS.•We propose a checklist to help consider workflow integration in health IT design.
This article explores the impact of recent applications of artificial intelligence on clinical anesthesiologists' decision-making.
Naturalistic decision-making, a rich research field that aims to ...understand how cognitive work is accomplished in complex environments, provides insight into anesthesiologists' decision processes. Due to the complexity of clinical work and limits of human decision-making (e.g. fatigue, distraction, and cognitive biases), attention on the role of artificial intelligence to support anesthesiologists' decision-making has grown. Artificial intelligence, a computer's ability to perform human-like cognitive functions, is increasingly used in anesthesiology. Examples include aiding in the prediction of intraoperative hypotension and postoperative complications, as well as enhancing structure localization for regional and neuraxial anesthesia through artificial intelligence integration with ultrasound.
To fully realize the benefits of artificial intelligence in anesthesiology, several important considerations must be addressed, including its usability and workflow integration, appropriate level of trust placed on artificial intelligence, its impact on decision-making, the potential de-skilling of practitioners, and issues of accountability. Further research is needed to enhance anesthesiologists' clinical decision-making in collaboration with artificial intelligence.
With the growing implementation and use of health IT such as Clinical Decision Support (CDS), there is increasing attention on the potential negative impact of these technologies on patients (e.g., ...medication errors) and clinicians (e.g., increased workload, decreased job satisfaction, burnout). Human-Centered Design (HCD) and Human Factors (HF) principles are recommended to improve the usability of health IT and reduce its negative impact on patients and clinicians; however, challenges persist. The objective of this study is to understand how an HCD process influences the usability of health IT. We conducted a systematic retrospective analysis of the HCD process used in the design of a CDS for pulmonary embolism diagnosis in the emergency department (ED). Guided by the usability outcomes (e.g., barriers and facilitators) of the CDS use “in the wild” (see Part 1 of this research in the accompanying manuscript), we performed deductive content analysis of 17 documents (e.g., design session transcripts) produced during the HCD process. We describe if and how the design team considered the barriers and facilitators during the HCD process. We identified 7 design outcomes of the HCD process, for instance designing a workaround and making a design change to the CDS. We identify gaps in the current HCD process and demonstrate the need for a continuous health IT design process.
While there is promise for health IT, such as Clinical Decision Support (CDS), to improve patient safety and clinician efficiency, poor usability has hindered widespread use of these tools. Human ...Factors (HF) principles and methods remain the gold standard for health IT design; however, there is limited information on how HF methods and principles influence CDS usability “in the wild”. In this study, we explore the usability of an HF-based CDS used in the clinical environment; the CDS was designed according to a human-centered design process, which is described in Carayon et al. (2020). In this study, we interviewed 12 emergency medicine physicians, identifying 294 excerpts of barriers and facilitators of the CDS. Sixty-eight percent of excerpts related to the HF principles applied in the human-centered design of the CDS. The remaining 32% of excerpts related to 18 inductively-created categories, which highlight gaps in the CDS design process. Several barriers were related to the physical environment and organization work system elements as well as physicians’ broader workflow in the emergency department (e.g., teamwork). This study expands our understanding of the usability outcomes of HF-based CDS “in the wild”. We demonstrate the value of HF principles in the usability of CDS and identify areas for improvement to future human-centered design of CDS. The relationship between these usability outcomes and the HCD process is explored in an accompanying Part 2 manuscript.
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