JAMA network open
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Emergency medical services (EMS) are an essential component of the health care system, but the effect of insurance expansion on EMS call volume remains unclear. ⋯ Insurance expansion within New York City under the ACA was associated with a significant reduction in the asthma EMS dispatch rate. Insurance expansion may be a viable method to reduce EMS utilization for ambulatory care-sensitive conditions such as asthma.
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Little is known about how US clinicians have responded to resource limitation during the coronavirus disease 2019 (COVID-19) pandemic. ⋯ The findings of this qualitative study highlighted the complexity of providing high-quality care for patients during the COVID-19 pandemic. Expanding the scope of institutional planning to address resource limitation challenges that can arise long before declarations of crisis capacity may help to support frontline clinicians, promote equity, and optimize care as the pandemic evolves.
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The Press Ganey Outpatient Medical Practice Survey is used to measure the patient experience. An understanding of the patient- and physician-related determinants of the patient experience may help identify opportunities to improve health care delivery and physician ratings. ⋯ In this study, higher Press Ganey survey scores were associated with racial/ethnic concordance between patients and their physicians. Efforts to improve physician workforce diversity are imperative. Delivery of health care in a culturally mindful manner between racially/ethnically discordant patient-physician dyads is also essential. Furthermore, Press Ganey scores may differ by a physician's patient demographic mix; thus, care must be taken when publicly reporting or using Press Ganey scores to evaluate physicians on an individual level.
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Machine-learning algorithms offer better predictive accuracy than traditional prognostic models but are too complex and opaque for clinical use. ⋯ In this study, simple machine learning techniques performed as well as the more advanced ensemble gradient boosting. Using the clinical variables identified from simple machine learning in a cirrhosis mortality model produced a new score more transparent than machine learning and more predictive than the MELD-Na score.
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Postoperative chemoradiation is the standard of care for cancers with positive margins or extracapsular extension, but the benefit of chemotherapy is unclear for patients with other intermediate risk features. ⋯ These findings suggest that machine learning models may identify patients with intermediate risk who could benefit from chemoradiation. These models predicted that approximately half of such patients have no added benefit from chemotherapy.