Home Research Research Library Relationship Between Physician Burnout And The Quality And Cost Of Care For Medicare Beneficiaries Is Complex Relationship Between Physician Burnout And The Quality And Cost Of Care For Medicare Beneficiaries Is Complex 2022 Author(s) Casalino, Lawrence P, Li, Jing, Peterson, Lars E, Rittenhouse, Diane R, Zhang, Manyao, O'Donnell, Eloise May, and Phillips, Robert L Topic(s) Role of Primary Care, and Achieving Health System Goals Keyword(s) Quality Of Care Volume Health Affairs Source Health Affairs Despite reports of a physician burnout epidemic, there is little research on the relationship between burnout and objective measures of care outcomes and no research on the relationship between burnout and costs of care. Linking survey data from 1,064 family physicians to Medicare claims, we found no consistent statistically significant relationship between seven categories of self-reported burnout and measures of ambulatory care-sensitive admissions, ambulatory care-sensitive emergency department visits, readmissions, or costs. The coefficients for ambulatory care-sensitive admissions and readmissions for all burnout levels, compared with never being burned out, were consistently negative (fewer ambulatory care-sensitive admissions and readmissions), suggesting that, counterintuitively, physicians who report burnout may nevertheless be able to create better outcomes for their patients. Even if true, this hypothesis should not indicate that physician burnout is beneficial or that efforts to reduce physician burnout are unimportant. Our findings suggest that the relationship between burnout and outcomes is complex and requires further investigation. ABFM Research Read all 2022 Informing Equity & Diversity in Primary Care Policy and Practice: Introducing a New Series of Policy Briefs, Commentaries, and Voices in JABFM Go to Informing Equity & Diversity in Primary Care Policy and Practice: Introducing a New Series of Policy Briefs, Commentaries, and Voices in JABFM 2025 Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence Go to Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence 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 2018 Rapid Sense Making: A Feasible, Efficient Approach for Analyzing Large Data Sets of Open-Ended Comments Go to Rapid Sense Making: A Feasible, Efficient Approach for Analyzing Large Data Sets of Open-Ended Comments
Author(s) Casalino, Lawrence P, Li, Jing, Peterson, Lars E, Rittenhouse, Diane R, Zhang, Manyao, O'Donnell, Eloise May, and Phillips, Robert L Topic(s) Role of Primary Care, and Achieving Health System Goals Keyword(s) Quality Of Care Volume Health Affairs Source Health Affairs
ABFM Research Read all 2022 Informing Equity & Diversity in Primary Care Policy and Practice: Introducing a New Series of Policy Briefs, Commentaries, and Voices in JABFM Go to Informing Equity & Diversity in Primary Care Policy and Practice: Introducing a New Series of Policy Briefs, Commentaries, and Voices in JABFM 2025 Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence Go to Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence 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 2018 Rapid Sense Making: A Feasible, Efficient Approach for Analyzing Large Data Sets of Open-Ended Comments Go to Rapid Sense Making: A Feasible, Efficient Approach for Analyzing Large Data Sets of Open-Ended Comments
2022 Informing Equity & Diversity in Primary Care Policy and Practice: Introducing a New Series of Policy Briefs, Commentaries, and Voices in JABFM Go to Informing Equity & Diversity in Primary Care Policy and Practice: Introducing a New Series of Policy Briefs, Commentaries, and Voices in JABFM
2025 Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence Go to Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence
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
2018 Rapid Sense Making: A Feasible, Efficient Approach for Analyzing Large Data Sets of Open-Ended Comments Go to Rapid Sense Making: A Feasible, Efficient Approach for Analyzing Large Data Sets of Open-Ended Comments