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Artificial Intelligence in Health Care

Integrated Care News by CFHA

That small win reminded me that artificial intelligence is already shaping the way our patients (and our families) search for health advice. Three reasons why learning Artificial Intelligence in health care may be a responsibility and not an option: 1. Evidence‑informed care was literally at his fingertips.

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Implementation of a novel linkage of primary care electronic medical record data with hospital data in South Eastern Ontario [Big data]

Annals of Family Medicine

Context: Currently, primary care data, community data, and hospital data are not linked in Ontario, resulting in a disconnect in continuity of care. 1072 patients with COPD were identified within the merged dataset, 50% of whom visited the ED within two years. Risk factors (i.e.,

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Machine learning models for atrial fibrillation detection in primary care using electronic health records: systematic review [Cardiovascular disease]

Annals of Family Medicine

Context: Atrial fibrillation (AFib) significantly impacts patient morbidity and mortality, despite existing screening practices. Machine learning (ML) models offer potential for improved detection of AFib from electronic health records (EHR). Setting or Dataset: Studies conducted in primary care settings were included.

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Electronic Health Record Use and Patient-Centredness [Education and training]

Annals of Family Medicine

Context: Large-scale electronic health record (EHR) programs have reported a number of issues to their implementation in primary care including physician patient-centredness and clinical performance. Setting: An academic primary care clinic based in a hospital. Sessions were virtual and recorded over Zoom.

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Maryland's Primary Care Program: incremental progress or breakthrough?

The Health Policy Exchange

Our residency, formerly a collaboration with Providence Hospital, is now known as the Medstar Health/Georgetown-Washington Hospital Center Family Medicine Residency Program. What hasn't changed is that our family medicine residents remain excited about health policy and advocacy. Phillips, Jr.

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Predicting Likelihood of Missed Appointments in Primary Care [Health care informatics]

Annals of Family Medicine

Context Optimizing continuity of care improves care quality, outcomes, and costs. Despite efforts to improve patient-clinician relationships, access to care, and healthcare workflows, annual rates of missed appointments (MA) in the U.S Female patients had lower rates of NS, but higher rates of SDC. for CA, 0.85

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Transitional Care Management care team impact on no-show rates to hospital discharge appointments [Patient education/adherence]

Annals of Family Medicine

Context: The Transitional Care Management (TCM) clinic visit is a uniquely billed visit type to review a recently discharged patient’s hospital course, reconcile medications, and continue ongoing workup. Objective: Our objective was to improve the TCM clinic no-show rate and thereby improve patient outcomes.