J Am Board Fam Med
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The rising obesity epidemic is a phenomenon that has gained increasing attention from health providers and health policy makers. This led to recognition of nonalcoholic fatty liver disease (MASLD). The standard for its assessment has been histologic, which is neither practical nor acceptable by patients. ⋯ Imaging methods are useful in evaluation, estimation, and following the progression of steatosis and fibrosis with particular attention to controlled attenuation parameter (CAP) and MRI-Proton Density Fat Fraction (MRI-PDFF). The choices for the family physician are broad and rely on tests' availability, cost, and patient acceptance. Great efforts have been undertaken to produce more robust and novel noninvasive markers that indicate fibrinogenesis directly in an implementable and cost-effective way.
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We propose a paper that provides education on commonly used long-acting injectable antipsychotics (LAIs) to improve primary care based mental health interventions in patients with severe mental illnesses (SMIs) such as schizophrenia, schizoaffective disorder, and bipolar disorders. With the expanding interface of primary care and psychiatry across all healthcare settings, it has become increasingly important for primary care clinicians to have a broader understanding of common psychiatric treatments, including LAIs. ⋯ We provide an overview of the treatment of SMI with LAIs, mainly focusing on the most commonly used long-acting injectable antipsychotics, advantages and disadvantages of each, along with outlining important clinical pearls for ease of practical application. Equipped with increased familiarity and understanding of these essential therapies, primary care clinicians can better facilitate early engagement with psychiatric care, promote more widespread use, and thus significantly improve the wellbeing and quality of life of patients with severe mental illness.
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Continuous glucose monitoring (CGM) for patients with type 1 and type 2 diabetes is associated with improved clinical, behavioral, and psychosocial patient health outcomes and is part of the American Diabetes Association's Standards of Medical Care. CGM prescription often takes place in endocrinology practices, yet 50% of adults with type 1 diabetes and 90% of all people with type 2 diabetes receive their diabetes care in primary care settings. This study examined primary care clinicians' perceptions of barriers and resources needed to support CGM use in primary care. ⋯ Primary care clinicians face several challenges to prescribing CGM, but they are interested in learning more to help them offer it to their patients. This study reinforces the ongoing need for improved clinician education on CGM technology and continued expansion of insurance coverage for people with both type 1 and type 2 diabetes.
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Artificial Intelligence (AI) is poised to revolutionize family medicine, offering a transformative approach to achieving the Quintuple Aim. This article examines the imperative for family medicine to adapt to the rapidly evolving field of AI, with an emphasis on its integration in clinical practice. AI's recent advancements have the potential to significantly transform health care. ⋯ However, we also acknowledge the risks associated with AI, including the potential for automation to diverge from patient-centered care and exacerbate health care disparities. Our recommendations stress the need for family medicine education to incorporate AI literacy, the development of a collaborative for AI integration, and the establishment of guidelines and standards through interdisciplinary cooperation. We conclude that although AI poses challenges, its responsible and ethical implementation can revolutionize family medicine, optimizing patient care and enhancing the role of clinicians in a technology-driven future.
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High-quality primary care can reduce avoidable emergency department visits and emergency hospitalizations. The availability of electronic medical record (EMR) data and capacities for data storage and processing have created opportunities for predictive analytics. This systematic review examines studies which predict emergency department visits, hospitalizations, and mortality using EMR data from primary care. ⋯ This review helps address critical gaps in the literature regarding the potential of primary care EMR data. Despite further work required to address bias and improve the quality and reporting of prediction models, the use of primary care EMR data for predictive analytics holds promise.