Evaluating the Costs of Nurse Burnout-Attributed Turnover: A Markov Modeling Approach

Objective Burnout is a public health crisis that impacts 1 in 3 registered nurses in the United States and the safe provision of patient care. This study sought to understand the cost of nurse burnout-attributed turnover using hypothetical hospital scenarios. Methods A cost-consequence analysis with a Markov model structure was used to assess nurse burnout-attributed turnover costs under the following scenarios: (1) a hospital with status quo nurse burnout prevalence and (2) a hospital with a burnout reduction program and decreased nurse burnout prevalence. The model evaluated turnover costs from a hospital payer perspective and modeled a cohort of nurses who were new to a hospital. The outcome measures were defined as years in burnout among the nurse cohort and years retained/employed in the hospital. Data inputs derived from the health services literature base. Results The expected model results demonstrated that at status quo, a hospital spends an expected $16,736 per nurse per year employed on nurse burnout-attributed turnover costs. In a hospital with a burnout reduction program, such costs were $11,592 per nurse per year employed. Nurses spent more time in burnout under the status quo scenario compared with the burnout reduction scenario (1.5 versus 1.1 y of employment) as well as less time employed at the hospital (2.9 versus 3.5 y of employment). Conclusions Given that status quo costs of burnout are higher than those in a hospital that invests in a nurse burnout reduction program, hospitals should strongly consider proactively supporting programs that reduce nurse burnout prevalence and associated costs.

Automated summary

This study assessed the costs of nurse burnout-attributed turnover using hypothetical hospital scenarios. The results showed that nurse burnout leads to high costs for hospitals, but investing in nurse burnout reduction programs can lower these costs and result in longer nurse employment and retention in hospitals.