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 Building a Sustainable Primary Care Workforce: Where Do We Go from Here? Building a Sustainable Primary Care Workforce: Where Do We Go from Here? 2017 Author(s) Linzer, M, and Poplau, S Topic(s) Achieving Health System Goals Keyword(s) Physician Experience (Burnout / Satisfaction), and Policy Brief Commentaries Volume Journal of the American Board of Family Medicine Source Journal of the American Board of Family Medicine The article by Puffer et al in this month’s JABFM confirms a high burnout rate (25%) among family physicians renewing their credentials, with a higher rate among young and female doctors. Recent reports confirm high burnout rates among general internists. Thus, mechanisms to monitor and improve worklife in primary care are urgently needed. We describe the Mini Z (for “zero burnout program”) measure, designed for these purposes, and suggest interventions that might improve satisfaction and sustainability in primary care, including longer visits, clinician control of work schedules, scribe support for electronic medical record work, team-based care, and an explicit emphasis on work-home balance. ABFM Research Read all 2020 Advancing bibliometric assessment of research productivity: an analysis of US Departments of Family Medicine Go to Advancing bibliometric assessment of research productivity: an analysis of US Departments of Family Medicine 2019 Endoscopic Services in the United States: By Whom, for What, and Why? Go to Endoscopic Services in the United States: By Whom, for What, and Why? 2019 Payment Structures That Support Social Care Integration With Clinical Care: Social Deprivation Indices and Novel Payment Models Go to Payment Structures That Support Social Care Integration With Clinical Care: Social Deprivation Indices and Novel Payment Models 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
Author(s) Linzer, M, and Poplau, S Topic(s) Achieving Health System Goals Keyword(s) Physician Experience (Burnout / Satisfaction), and Policy Brief Commentaries Volume Journal of the American Board of Family Medicine Source Journal of the American Board of Family Medicine
ABFM Research Read all 2020 Advancing bibliometric assessment of research productivity: an analysis of US Departments of Family Medicine Go to Advancing bibliometric assessment of research productivity: an analysis of US Departments of Family Medicine 2019 Endoscopic Services in the United States: By Whom, for What, and Why? Go to Endoscopic Services in the United States: By Whom, for What, and Why? 2019 Payment Structures That Support Social Care Integration With Clinical Care: Social Deprivation Indices and Novel Payment Models Go to Payment Structures That Support Social Care Integration With Clinical Care: Social Deprivation Indices and Novel Payment Models 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
2020 Advancing bibliometric assessment of research productivity: an analysis of US Departments of Family Medicine Go to Advancing bibliometric assessment of research productivity: an analysis of US Departments of Family Medicine
2019 Endoscopic Services in the United States: By Whom, for What, and Why? Go to Endoscopic Services in the United States: By Whom, for What, and Why?
2019 Payment Structures That Support Social Care Integration With Clinical Care: Social Deprivation Indices and Novel Payment Models Go to Payment Structures That Support Social Care Integration With Clinical Care: Social Deprivation Indices and Novel Payment Models
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
