AI technology as solution or stressor: A meta-analysis of healthcare provider burnout outcomes
Description
Mental health problems are an increasingly important aspect of modern healthcare that needs to be addressed given their widespread impact and complex etiology. Workplace burnout among healthcare providers significantly impacts job performance and patient health outcomes. With rapid integration of artificial intelligence (AI) technologies in clinical settings—including ambient documentation systems, diagnostic assistance tools, and clinical decision support—understanding their impact on provider burnout has become critical. This study systematically evaluates current literature on healthcare provider burnout and AI technology implementation to determine whether these emerging technologies are associated with changes in burnout levels.
Comprehensive systematic searches of EBSCOhost, PubMed, ProQuest, and additional databases were conducted following PRISMA guidelines to identify eligible studies reporting validated burnout measures in healthcare provider populations utilizing AI technologies. Inclusion criteria required peer-reviewed empirical research, quantitative burnout measurement using validated instruments (Maslach Burnout Inventory, Professional Quality of Life Scale, Copenhagen Burnout Inventory), clearly defined AI technology implementation, healthcare provider populations, and publication between 2019-2025. Meta-analytic synthesis using R (metafor package) with random-effects models will account for between-study heterogeneity.
Preliminary screening identified 458 studies; 79 advanced to full-text review. Preliminary assessment reveals diverse AI applications with varied burnout measurement timepoints across studies. This meta-analysis will establish pooled effect estimates of AI technology's impact on healthcare provider burnout, determining whether AI technologies represent a solution to technology-related burnout or contribute to new workplace stressors among healthcare providers.
Citation Information
Vemulapati, Vishnu; Modukuri, Rahul; and Datzman, Jared, "AI technology as solution or stressor: A meta-analysis of healthcare provider burnout outcomes" (2026). Office of Research DMU Research Symposium. 1.
https://digitalcommons.dmu.edu/researchsymposium/2025rs/2025abstracts/1
AI technology as solution or stressor: A meta-analysis of healthcare provider burnout outcomes
Mental health problems are an increasingly important aspect of modern healthcare that needs to be addressed given their widespread impact and complex etiology. Workplace burnout among healthcare providers significantly impacts job performance and patient health outcomes. With rapid integration of artificial intelligence (AI) technologies in clinical settings—including ambient documentation systems, diagnostic assistance tools, and clinical decision support—understanding their impact on provider burnout has become critical. This study systematically evaluates current literature on healthcare provider burnout and AI technology implementation to determine whether these emerging technologies are associated with changes in burnout levels.
Comprehensive systematic searches of EBSCOhost, PubMed, ProQuest, and additional databases were conducted following PRISMA guidelines to identify eligible studies reporting validated burnout measures in healthcare provider populations utilizing AI technologies. Inclusion criteria required peer-reviewed empirical research, quantitative burnout measurement using validated instruments (Maslach Burnout Inventory, Professional Quality of Life Scale, Copenhagen Burnout Inventory), clearly defined AI technology implementation, healthcare provider populations, and publication between 2019-2025. Meta-analytic synthesis using R (metafor package) with random-effects models will account for between-study heterogeneity.
Preliminary screening identified 458 studies; 79 advanced to full-text review. Preliminary assessment reveals diverse AI applications with varied burnout measurement timepoints across studies. This meta-analysis will establish pooled effect estimates of AI technology's impact on healthcare provider burnout, determining whether AI technologies represent a solution to technology-related burnout or contribute to new workplace stressors among healthcare providers.
