Journal of general internal medicine
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Geographic variation in high-cost medical procedure utilization in the USA is not fully explained by patient factors but may be influenced by the supply of procedural physicians and marketing payments. ⋯ Among Medicare FFS beneficiaries, regional supply of physicians and receipt of industry payments were associated with greater use of PCIs and KAs. Relationships between payments and procedural utilization were more consistent for KAs, a largely elective procedure, compared to PCIs, which may be elective or emergent.
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Non-arrivals to scheduled ambulatory visits are common and lead to a discontinuity of care, poor health outcomes, and increased subsequent healthcare utilization. Reducing non-arrivals is important given their association with poorer health outcomes and cost to health systems. ⋯ Using a machine learning algorithm, we developed a prediction model for non-arrivals to scheduled ambulatory appointments usable for all medical specialties. The proposed prediction model can be deployed within an electronic health system or integrated into other dashboards to reduce non-arrivals. Future work will focus on the implementation and application of the model to reduce non-arrivals.
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Racial/ethnic minorities in the USA exhibit reduced health literacy (HL) proficiency, leading to increased health disparities. It is unclear how the effect of birth status (immigrant/US-born) affects HL proficiency among racial/ethnic minorities. ⋯ Immigrant status has a strong, negative, direct effect on HL proficiency among racial/ethnic minorities in the USA. This may be a result of barriers that prevent equitable access to resources that improve proper HL proficiency. US policymakers may consider several methods to reduce this disparity at the health-system-, provider-, and patient-levels.
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Preventive screening at the point of care can increase desired clinical outcomes. However, the impact of repeated screening for tobacco use on receiving smoking cessation treatment among women Veteran population has not been documented. ⋯ Repeated screening was associated with higher predicted probabilities of being prescribed smoking cessation treatment.
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It is important to identify older adults at high risk of functional disability and to take preventive measures for them at an early stage. To our knowledge, there are no studies that predict functional disability among community-dwelling older adults using machine learning algorithms. ⋯ Machine learning-based models showed effective performance prediction over 5 years. Our findings suggest that measuring and adding the variables identified as important features can improve the prediction of functional disability.