Journal of evaluation in clinical practice
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During the devastating early months of the unfolding COVID-19 pandemic in New York, healthcare systems and clinicians dynamically adapted to drastically changing everyday practice despite having little guidance from formal research evidence in the face of a novel virus. Through new, silo-breaking networks of communication, clinical teams transformed and synthesized provisional recommendations, rudimentary published research findings and numerous other sources of knowledge to address the immediate patient care needs they faced during the pandemic surge. ⋯ We draw on the concept of mindlines as developed by Gabbay and Le May as a conceptual framework for interpreting that experience from the standpoint of how early information from research and guidelines was drawn on and transformed in the course of day-to-day struggle with the crisis in New York City emergency rooms. Finally, briefly referencing the challenges to conventional models of healthcare knowledge creation and translation through research and guideline production posed by COVID-19 crisis, we offer a provisional perspective on current and future developments.
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As big data becomes more publicly accessible, artificial intelligence (AI) is increasingly available and applicable to problems around clinical decision-making. Yet the adoption of AI technology in healthcare lags well behind other industries. The gap between what technology could do, and what technology is actually being used for is rapidly widening. ⋯ To aid with change, we propose facilitating clinician decisions through technology by seamlessly weaving what we call 'invisible AI' into existing clinician workflows, rather than sequencing new steps into clinical processes. We explore evidence from the change management and human factors literature to conceptualize a new approach to AI implementation in health organizations. We discuss challenges and provide recommendations for organizations to employ this strategy.
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Preoperative patient education through 'joint class' has potential to improve quality of care for total joint replacement (TJR). However, no formal guidance exists regarding curriculum content, potentially resulting in inter-institutional variation. ⋯ Our synthesis identified core common topics included in pre-TJR education but also highlighted variation across institutions, supporting opportunities for standardization. Clinicians and researchers can use our preliminary model to systematically develop and evaluate 'joint classes,' with the goal of establishing a standard of care for TJR preoperative education.
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Diagnostic momentum refers to ruling in a particular diagnosis without adequate evidence. As the field of physical therapy continues to transition more towards autonomous practitioners with direct access, there is a need to identify the effect of a physician diagnosis on a therapist's examination and treatment. The purpose of this study was to identify if diagnostic momentum exists in physical therapy and whether this phenomenon could affect the ability of the therapist to identify clinical red flags. ⋯ This study suggests that practicing physical therapists may be influenced by diagnostic decisions made by other clinicians, causing them to overlook signs and symptoms of possible myocardial infarction.