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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. Our Patients Are Already Using AI Many people now ask their first health question to a chatbot rather than to a clinician. Annals of Family Medicine , 23(1), 5–6.

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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. Intervention: Participants each completed two simulated patient scenarios with instructions to document their encounters in the EHR.

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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.

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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

Objectives: To link primary care electronic medical record (EMR) data with community and hospital data and to test the utility of the merged dataset through a targeted quality improvement (QI) intervention among high-risk patients with chronic obstructive pulmonary disease (COPD). Risk factors (i.e.,

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A brief theory driven patient education video to reduce potentially harmful regular over-the-counter NSAID use [Patient education/adherence]

Annals of Family Medicine

Context: Nonsteroidal anti-inflammatory drugs (NSAIDs) are common medications with numerous well documented adverse effects, leading many professional organizations to recommended that certain patient populations avoid regular use. Population Studied: High-risk patients (>18 years) who self-identified as regular OTC NSAID users.

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Describing Differences Across Place and Provider in Canadian Team-Based Care Settings Using Electronic Health Records [Health care informatics]

Annals of Family Medicine

Background Team-based care (TBC) has established benefits for patient outcomes. In both cases, TBC can help by providing a collaborative approach to care that can better manage the complex needs of patients. In both cases, TBC can help by providing a collaborative approach to care that can better manage the complex needs of patients.

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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).