The American journal of managed care
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The understanding of which factors are associated with inability to access health care services due to the COVID-19 pandemic is limited. We aimed to examine factors associated with being unable to access health care due to the pandemic among Medicare beneficiaries. ⋯ Given that sociodemographics and comorbidity burden contributed to the disparities that we observed in accessibility of health care services due to the pandemic, these findings can allow decision makers to target resource allocation and outreach efforts to those populations most at risk.
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One-third of health care in the United States is wasted. Despite this recognition, solutions are sparse. The Optimal Care model combines evidence-based medicine, patient-centered technology, and outcomes reporting to transform health care.
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Empiric segmentation is a rapidly growing, learning health system approach that uses large health care system data sets to identify groups of high-risk patients who may benefit from similar interventions. We aimed to review studies that used data-driven approaches to segment high-risk patient populations and describe how their designs and findings can inform health care leaders who are interested in applying similar techniques to their patient populations. ⋯ Empiric segmentation can yield clinically relevant groups of patients with complex medical needs. Segmentation results are context dependent, suggesting the need for careful design and interpretation of segmentation models to ensure that results can inform clinical care and program design in the target setting.
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Existing literature indicates that multimorbidity, mental health (MH) conditions, substance use disorders (SUDs), and social determinants of health are hallmarks of high-need, high-cost patients. Health Resources and Services Administration-funded health centers (HCs) provide care to nearly 30 million patients, but data on their patients' complexity and utilization patterns are limited. We identified subgroups of HC patients based on latent concepts of complexity and utilization. ⋯ Our examination of complexity and utilization indicated distinct HC patient populations. Managing the care of each group may require different targeted intervention approaches such as multidisciplinary care teams that include MH providers or specialists.
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To understand real-world implementation of the updated CDC HIV diagnostic testing algorithm. ⋯ Our study findings suggest that the CDC HIV diagnostic algorithm is complex and may pose suboptimal testing efficiency. Opportunities to improve diagnostic efficiency by reducing indeterminate results and repeat tests are warranted.