BMJ quality & safety
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Interest in human factors has increased across healthcare communities and institutions as the value of human centred design in healthcare becomes increasingly clear. However, as human factors is becoming more prominent, there is growing evidence of confusion about human factors science, both anecdotally and in scientific literature. Some of the misconceptions about human factors may inadvertently create missed opportunities for healthcare improvement. ⋯ The human factors concepts presented in this article may foster interdisciplinary collaborations to yield new, sustainable solutions for healthcare quality and patient safety.
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BMJ quality & safety · Oct 2013
The pursuit of better diagnostic performance: a human factors perspective.
Despite the relatively slow start in treating diagnostic error as an amenable research topic at the beginning of the patient safety movement, interest has steadily increased over the past few years in the form of solicitations for research, regularly scheduled conferences, an expanding literature and even a new professional society. Yet improving diagnostic performance increasingly is recognised as a multifaceted challenge. ⋯ To encourage empirical testing of interventions that aim to improve diagnostic performance, a systems engineering approach making use of rapid-cycle prototyping and simulation is proposed. To gain a fuller understanding of the complexity of the sociotechnical space where diagnostic work is performed, a final note calls for the formation of substantive partnerships with those in disciplines beyond the clinical domain.
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A wide variety of research studies suggest that breakdowns in the diagnostic process result in a staggering toll of harm and patient deaths. These include autopsy studies, case reviews, surveys of patient and physicians, voluntary reporting systems, using standardised patients, second reviews, diagnostic testing audits and closed claims reviews. ⋯ We argue that being able to measure the incidence of diagnostic error is essential to enable research studies on diagnostic error, and to initiate quality improvement projects aimed at reducing the risk of error and harm. Three approaches appear most promising in this regard: (1) using 'trigger tools' to identify from electronic health records cases at high risk for diagnostic error; (2) using standardised patients (secret shoppers) to study the rate of error in practice; (3) encouraging both patients and physicians to voluntarily report errors they encounter, and facilitating this process.
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In a companion paper, we proposed that cognitive debiasing is a skill essential in developing sound clinical reasoning to mitigate the incidence of diagnostic failure. We reviewed the origins of cognitive biases and some proposed mechanisms for how debiasing processes might work. In this paper, we first outline a general schema of how cognitive change occurs and the constraints that may apply. ⋯ We outline three groups of suggested interventions going forward: educational strategies, workplace strategies and forcing functions. We stress the importance of ambient and contextual influences on the quality of individual decision making and the need to address factors known to impair calibration of the decision maker. We also emphasise the importance of introducing these concepts and corollary development of training in critical thinking in the undergraduate level in medical education.
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BMJ quality & safety · Oct 2013
ReviewUse of health information technology to reduce diagnostic errors.
Health information technology (HIT) systems have the potential to reduce delayed, missed or incorrect diagnoses. We describe and classify the current state of diagnostic HIT and identify future research directions. ⋯ Diagnostic HIT research is still in its early stages with few demonstrations of measurable clinical impact. Future efforts need to focus on: (1) improving methods and criteria for measurement of the diagnostic process using electronic data; (2) better usability and interfaces in electronic health records; (3) more meaningful incorporation of evidence-based diagnostic protocols within clinical workflows; and (4) systematic feedback of diagnostic performance.