Investigating patient safety culture across a health system: multilevel modelling of differences associated with service types and staff demographics
- PMID: 22687703
- DOI: 10.1093/intqhc/mzs028
Investigating patient safety culture across a health system: multilevel modelling of differences associated with service types and staff demographics
Abstract
Objective: To use multilevel modelling to compare the patient safety cultures of types of services across a health system and to determine whether differences found can be accounted for by staffs' professions, organizational roles, ages and type of patient care provided.
Design: Application of a hierarchical two-level regression model.
Setting: All services in the South Australian public health system.
Participants: Approximately half of the health staff (n = 14 054) in the 46 organizations, classified into 18 types of service, which made up the South Australian public health system.
Interventions: Staff completed the Safety Attitudes Questionnaire.
Main outcome measures: Attitudes regarding Teamwork Climate, Safety Climate, Job Satisfaction, Stress Recognition, Perception of Management and Working Conditions in participants' workplaces.
Results: All SAQ indices showed statistically significant although modest variations according to service type. However, most of these differences were not accounted for by the differences in the demographic composition of services' staff. Most favourable safety attitudes were found in the breast screening, primary/community health services, community nursing and metropolitan non-teaching hospitals. Poorer cultures were reported in the psychiatric hospital, mental health, metropolitan ambulance services and top-level teaching hospitals. Demographic differences in safety attitudes were observed; particularly, clinical, senior managerial, aged care and older staff held more favourable attitudes.
Conclusions: Differences in staff attitudes have been demonstrated at a macro-level across the type of health services but for the most part, differences could not be explained by staffing composition.
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