Annals of family medicine
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Annals of family medicine · Nov 2022
Measuring the Value Functions of Primary Care: Physician-Level Continuity of Care Quality Measure.
Care continuity is foundational to the clinician/patient relationship; however, little has been done to operationalize continuity of care (CoC) as a clinical quality measure. The American Board of Family Medicine developed the Primary Care CoC clinical quality measure as part of the Measures That Matter to Primary Care initiative. ⋯ Continuity is associated with desirable health and cost outcomes as well as patient preference. The CoC clinical quality measure meets validity and reliability requirements for implementation in primary care payment and accountability. Care continuity is important and complementary to access to care, and prioritizing this measure could help shift physician and health system behavior to support continuity.
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Annals of family medicine · Nov 2022
Competencies for the Use of Artificial Intelligence in Primary Care.
The artificial intelligence (AI) revolution has arrived for the health care sector and is finally penetrating the far-reaching but perpetually underfinanced primary care platform. While AI has the potential to facilitate the achievement of the Quintuple Aim (better patient outcomes, population health, and health equity at lower costs while preserving clinician well-being), inattention to primary care training in the use of AI-based tools risks the opposite effects, imposing harm and exacerbating inequalities. ⋯ Integrating these competencies will not be straightforward because of the breadth of knowledge already incorporated into family medicine training and the constantly changing technological landscape. Nonetheless, even incremental increases in AI-relevant training may be beneficial, and the sooner these challenges are tackled, the sooner the primary care workforce and those served by it will begin to reap the benefits.
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Annals of family medicine · Nov 2022
Leveraging Free-Form Comments to Assess and Improve Patient Satisfaction.
This study employed a text-analysis methodology to identify themes within patient comments and measure the relationship of those themes to patient satisfaction. Using these findings, a spreadsheet tool was created to allow a large sample of comments to be readily analyzed. ⋯ The tool gives clinicians the ability to easily analyze patient comments and identify actionable measures of patient satisfaction. Additionally, this tool will allow researchers to reduce vast sets of comment text into numerical data suited for quantitative analyses.