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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. Within minutes he integrated the latest findings into practical recommendations for the family. How are you integrating AI into your clinical, teaching or supervisory work?

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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. Population: Ten resident physicians and six staff physicians.

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Position Statement on Measurement Based Care

Integrated Care News by CFHA

This position statement from the Collaborative Family Healthcare Association (CFHA) outlines our organizational commitment to Measurement-Based Care (MBC) as a foundational element of integrated healthcare. MBC supports optimal clinical practice, demonstrates the value of integrated care teams, and improves outcomes. What is MBC?

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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).

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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

Community Health Centres (CHCs) provide TBC for both urban and rural populations with barriers to care in Ontario, Canada, and they share a common electronic health record (EHR) system that records codes assigned by providers during an encounter.

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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

Machine learning (ML) models offer potential for improved detection of AFib from electronic health records (EHR). Objective: To synthesize data on the effectiveness, generalizability, and clinical relevance of ML models in detecting AFib cases using EHR in primary care settings. We searched seven databases from inception to May 2023.

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Pajama Time: The Association of EHR Documentation Time with Family Medicine Resident Outcomes [Education and training]

Annals of Family Medicine

Context: Multiple studies have identified that working on the electronic health record (EHR) after clinic hours ("pajama time") is a source of burnout and decreasing professional satisfaction. Study Design and Analysis: Survey of US family medicine (FM) residents. Population Studied: PGY2 and above US FM residents.