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Τρίτη 24 Απριλίου 2018

Nursing workload, patient safety incidents and mortality: an observational study from Finland

Objective

To investigate whether the daily workload per nurse (Oulu Patient Classification (OPCq)/nurse) as measured by the RAFAELA system correlates with different types of patient safety incidents and with patient mortality, and to compare the results with regressions based on the standard patients/nurse measure.

Setting

We obtained data from 36 units from four Finnish hospitals. One was a tertiary acute care hospital, and the three others were secondary acute care hospitals.

Participants

Patients' nursing intensity (249 123 classifications), nursing resources, patient safety incidents and patient mortality were collected on a daily basis during 1 year, corresponding to 12 475 data points. Associations between OPC/nurse and patient safety incidents or mortality were estimated using unadjusted logistic regression models, and models that adjusted for ward-specific effects, and effects of day of the week, holiday and season.

Primary and secondary outcome measures

Main outcome measures were patient safety incidents and death of a patient.

Results

When OPC/nurse was above the assumed optimal level, the adjusted odds for a patient safety incident were 1.24 (95% CI 1.08 to 1.42) that of the assumed optimal level, and 0.79 (95% CI 0.67 to 0.93) if it was below the assumed optimal level. Corresponding estimates for patient mortality were 1.43 (95% CI 1.18 to 1.73) and 0.78 (95% CI 0.60 to 1.00), respectively. As compared with the patients/nurse classification, models estimated on basis of the RAFAELA classification system generally provided larger effect sizes, greater statistical power and better model fit, although the difference was not very large. Net benefits as calculated on the basis of decision analysis did not provide any clear evidence on which measure to prefer.

Conclusions

We have demonstrated an association between daily workload per nurse and patient safety incidents and mortality. Current findings need to be replicated by future studies.



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