Home Research Research Library Well‐Being in the Nation: A Living Library of Measures to Drive Multi‐Sector Population Health Improvement and Address Social Determinants Well‐Being in the Nation: A Living Library of Measures to Drive Multi‐Sector Population Health Improvement and Address Social Determinants 2020 Author(s) Saha, Somava, Cohen, Bruce B, Nagy, Julia, McPHERSON, Marianne E, and Phillips, Robert L Topic(s) Role of Primary Care, and Achieving Health System Goals Keyword(s) Cost Of Care, and Quality Of Care Volume 1468-0009.12477 Source Milbank Quarterly Well-being In the Nation (WIN) offers the first parsimonious set of vetted common measures to improve population health and social determinants across sectors at local, state, and national levels and is driven by what communities need to improve health, well-being, and equity. The WIN measures were codesigned with more than 100 communities, federal agencies, and national organizations across sectors, in alignment with the National Committee on Vital and Health Statistics, the Foundations for Evidence-Based Policymaking Act, and Healthy People 2030. WIN offers a process for a collaborative learning measurement system to drive a learning health and well-being system across sectors at the community, state, and national levels. The WIN development process identified critical gaps and opportunities in equitable community-level data infrastructure, interoperability, and protections that could be used to inform the Federal Data Strategy. ABFM Research Read all 2023 Foundational Collective Actions for Achieving Agile High-Quality Primary Care in the United States Go to Foundational Collective Actions for Achieving Agile High-Quality Primary Care in the United States 2023 A Comparative Effectiveness Study on Opioid Use Disorder Prediction Using Artificial Intelligence and Existing Risk Models Go to A Comparative Effectiveness Study on Opioid Use Disorder Prediction Using Artificial Intelligence and Existing Risk Models 2025 Documentation of Compounded GLP‐1 Receptor Agonists in a Large Primary Care Dataset Go to Documentation of Compounded GLP‐1 Receptor Agonists in a Large Primary Care Dataset 2020 The Evolving Family Medicine Team Go to The Evolving Family Medicine Team
Author(s) Saha, Somava, Cohen, Bruce B, Nagy, Julia, McPHERSON, Marianne E, and Phillips, Robert L Topic(s) Role of Primary Care, and Achieving Health System Goals Keyword(s) Cost Of Care, and Quality Of Care Volume 1468-0009.12477 Source Milbank Quarterly
ABFM Research Read all 2023 Foundational Collective Actions for Achieving Agile High-Quality Primary Care in the United States Go to Foundational Collective Actions for Achieving Agile High-Quality Primary Care in the United States 2023 A Comparative Effectiveness Study on Opioid Use Disorder Prediction Using Artificial Intelligence and Existing Risk Models Go to A Comparative Effectiveness Study on Opioid Use Disorder Prediction Using Artificial Intelligence and Existing Risk Models 2025 Documentation of Compounded GLP‐1 Receptor Agonists in a Large Primary Care Dataset Go to Documentation of Compounded GLP‐1 Receptor Agonists in a Large Primary Care Dataset 2020 The Evolving Family Medicine Team Go to The Evolving Family Medicine Team
2023 Foundational Collective Actions for Achieving Agile High-Quality Primary Care in the United States Go to Foundational Collective Actions for Achieving Agile High-Quality Primary Care in the United States
2023 A Comparative Effectiveness Study on Opioid Use Disorder Prediction Using Artificial Intelligence and Existing Risk Models Go to A Comparative Effectiveness Study on Opioid Use Disorder Prediction Using Artificial Intelligence and Existing Risk Models
2025 Documentation of Compounded GLP‐1 Receptor Agonists in a Large Primary Care Dataset Go to Documentation of Compounded GLP‐1 Receptor Agonists in a Large Primary Care Dataset
