Nevin Manimala Statistics

Exploring the relationship between simulation-based team training and sick leave among healthcare professionals: a cohort study across multiple hospital sites

BMJ Open. 2023 Oct 29;13(10):e076163. doi: 10.1136/bmjopen-2023-076163.


OBJECTIVE: Burnout and mental illness are frequent among healthcare professionals, leading to increased sick leave. Simulation-based team training has been shown to improve job satisfaction and mental health among healthcare professionals. This study seeks to investigate the relationship between simulation-based team training and sick leave.

DESIGN: Cohort study.

SETTING AND INTERVENTION: Five Danish hospitals.

PARTICIPANTS: A total of 15 751 individuals were screened for eligibility. To meet the eligibility criteria, individuals had to be employed in the same group (intervention or control) for the whole study period. A total of 14 872 individuals were eligible for analysis in the study.

INTERVENTION: From 2017 to 2019, a simulation-based team training intervention was implemented at two hospital sites. Three hospital sites served as the control group.

OUTCOME MEASURES: Data on sick leave from 2015 to 2020 covered five hospital sites. Using a difference-in-difference analysis, the rate of sick leave was compared across hospital sites (intervention vs control) and time periods (before vs after intervention).

RESULTS: Significant alterations in sick leave were evident when comparing the intervention and control groups. When comparing groups over time, the increase in sick leave was -0.3% (95% CI -0.6% to -0.0%) lower in the intervention group than in the control group. The difference-in-difference for the complete case analysis showed that this trend remained consistent, with analysis indicating a comparable lower increase in sick leave by -0.7% (95% CI -1.3% to -0.1%) in the intervention group.

CONCLUSION: The increase in sick leave rate was statistically significantly lower in the intervention group, implying that simulation-based team training could serve as a protective factor against sick leave. However, when investigating this simulation intervention over 5 years, other potential factors may have influenced sick leave, so caution is required when interpreting the results.

PMID:37899150 | DOI:10.1136/bmjopen-2023-076163

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