Phoenix Newsletter - October 2025 President’s Message: Enduring Commitments in a Time of Change Read President’s Message: Enduring Commitments in a Time of Change
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 Milbank Quarterly 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 2024 What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care Go to What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care 2019 Research gaps in the organisation of primary healthcare in low-income and middle-income countries and ways to address them: a mixed-methods approach Go to Research gaps in the organisation of primary healthcare in low-income and middle-income countries and ways to address them: a mixed-methods approach 2013 Specialty board certification in the United States: issues and evidence Go to Specialty board certification in the United States: issues and evidence 2020 Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments Go to Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments
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 Milbank Quarterly Source Milbank Quarterly
ABFM Research Read all 2024 What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care Go to What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care 2019 Research gaps in the organisation of primary healthcare in low-income and middle-income countries and ways to address them: a mixed-methods approach Go to Research gaps in the organisation of primary healthcare in low-income and middle-income countries and ways to address them: a mixed-methods approach 2013 Specialty board certification in the United States: issues and evidence Go to Specialty board certification in the United States: issues and evidence 2020 Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments Go to Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments
2024 What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care Go to What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care
2019 Research gaps in the organisation of primary healthcare in low-income and middle-income countries and ways to address them: a mixed-methods approach Go to Research gaps in the organisation of primary healthcare in low-income and middle-income countries and ways to address them: a mixed-methods approach
2013 Specialty board certification in the United States: issues and evidence Go to Specialty board certification in the United States: issues and evidence
2020 Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments Go to Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments
