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Burnout in the neonatal intensive care unit and its relation to healthcare-associated infections

Journal title
Journal of perinatology : official journal of the California Perinatal Association
Publication year
Tawfik, D. S.; Sexton, J. B.; Kan, P.; Sharek, P. J.; Nisbet, C. C.; Rigdon, J.; Lee, H. C.; Profit, J.

OBJECTIVE: To examine burnout prevalence among California neonatal intensive care units (NICUs) and to test the relation between burnout and healthcare-associated infection (HAI) rates in very low birth weight (VLBW) neonates. STUDY DESIGN: Retrospective observational study of provider perceptions of burnout from 2073 nurse practitioners, physicians, registered nurses and respiratory therapists, using a validated four-item questionnaire based on the Maslach Burnout Inventory. The relation between burnout and HAI rates among VLBW (<1500 g) neonates from each NICU was evaluated using multi-level logistic regression analysis with patient-level factors as fixed effects. RESULTS: We found variable prevalence of burnout across the NICUs surveyed (mean 25.2+/-10.1%). Healthcare-associated infection rates were 8.3+/-5.1% during the study period. Highest burnout prevalence was found among nurses, nurse practitioners and respiratory therapists (non-physicians, 28+/-11% vs 17+/-19% physicians), day shift workers (30+/-3% vs 25+/-4% night shift) and workers with 5 or more years of service (29+/-2% vs 16+/-6% in fewer than 3 years group). Overall burnout rates showed no correlation with risk-adjusted rates of HAIs (r=-0.133). Item-level analysis showed positive association between HAIs and perceptions of working too hard (odds ratio 1.15, 95% confidence interval 1.04-1.28). Sensitivity analysis of high-volume NICUs suggested a moderate correlation between burnout prevalence and HAIs (r=0.34). CONCLUSION: Burnout is most prevalent among non-physicians, daytime workers and experienced workers. Perceptions of working too hard associate with increased HAIs in this cohort of VLBW infants, but overall burnout prevalence is not predictive.

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