The American journal of managed care
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Electronic consultation, or e-consult, systems improve specialty care access by conveying specialist expertise to primary care clinicians (PCCs) without requiring specialist visits. Our study evaluates organizational factors for e-consult implementation across 5 publicly financed, county-based health systems in California. Each system serves 40,000 to 180,000 culturally and linguistically diverse patients across 4 to 19 primary care locations. ⋯ Successful e-consult implementations in public delivery systems leveraged (1) prior primary care and specialty care clinician relationships and (2) integrated EHR and e-consult platforms. This contrasts with common expectations that new technology will overcome care delivery gaps. Findings add to existing e-consult implementation literature that emphasizes reimbursement and leadership champions.
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Observational Study
Does machine learning improve prediction of VA primary care reliance?
The Veterans Affairs (VA) Health Care System is among the largest integrated health systems in the United States. Many VA enrollees are dual users of Medicare, and little research has examined methods to most accurately predict which veterans will be mostly reliant on VA services in the future. This study examined whether machine learning methods can better predict future reliance on VA primary care compared with traditional statistical methods. ⋯ The modest gains in performance from the best-performing model, gradient boosting machine, are unlikely to outweigh inherent drawbacks, including computational complexity and limited interpretability compared with traditional logistic regression.
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Editorial
The health IT special issue: enduring barriers to adoption and innovative predictive methods.
Electronic health record systems have the potential to significantly improve care coordination and, ultimately, clinical care delivery. Still, it is clear that these systems are not silver bullets that will automatically result in better coordination of care and quality.
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The learning health system (LHS) has gained traction as a powerful framework for improving the cost and quality of healthcare. The goal of an LHS is to systematically integrate internal data and experience with external evidence so patients receive higher-quality, safer, and more efficient care. ⋯ We also discuss how integrating data on the social determinants and activities to reduce patients' social risk factors could advance the mission of the LHS to enhance patient engagement, improve the delivery of personalized care, and more accurately evaluate the effectiveness of care. Without the collection and integration of data on the social determinants of health, the LHS may fail to reach its full potential to improve health and healthcare.
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Telemedicine offers a promising solution to the growing physician shortage, but state-based medical licensing poses a significant barrier to the widespread adoption of telemedicine services. We thus recommend a mutual recognition scheme whereby states honor each other's medical licenses. Successfully implementing mutual recognition requires policy, technological, and administrative changes, including a federal mandate for states to participate in mutual recognition, consistent standards for using and regulating telemedicine, a mechanism to enable interstate data sharing, financial support for states, and a "state of principal license" requirement for physicians. Reforming the United States' outdated system of state-based medical licensure can help meet patient demand for virtual care services and improve access to care in rural and medically underserved areas.