A causal model for the quality of nursing care in Thailand

Abstract

Background: A growing global nursing shortage has affected the quality of care (QOC) provision.

Aim: To test the structure-process-outcome model for quality of nursing care in regional medical centres in Thailand.

Methods: A cross-sectional study with multi-stage, proportional stratified random sampling. The sample comprised 136 units, 916 nurses and 943 patients from nine regional medical centres. Data were collected from six instruments in February-June 2016 and analysed with structural equation modelling.

Results: The modified model fitted the empirical data. The nurse practice environment (NPE) had a negative direct effect on pressure ulcer prevalence and a positive direct effect on patient satisfaction, perceived QOC and interpersonal processes of care (IPC). Increasing the patient-to-nurse ratio had a positive direct effect on catheter-associated urinary tract infections and pressure ulcer prevalence and had negative direct effects on patient satisfaction and perceived QOC. Skill mix had negative direct effects on the two former conditions but had a positive direct effect on patient satisfaction. The patient-to-nurse ratio and skill mix also had indirect effect on four outcomes via NPE.

Limitations: The generalizability of findings may be limited to settings similar to this study.

Conclusion: We empirically demonstrated that NPE, patient-to-nurse- ratio and skill mix had direct effects on unfinished nursing care and four outcomes. Also, the IPC had significant influence on patient satisfaction.

Implications for nursing and health policy: The findings add to increasing international evidence that favourable nurse working conditions, low nurse-to-patient ratio and richer skill mix result in positive patient outcomes. Health systems can foster nurses to perform high-quality care by improving work conditions, and providing sufficient nurses and resources.

Keywords: Nurse-Patient Ratio; Nursing; Patient Satisfaction; Quality of Care; Skill Mix; Structural Equation Modelling; Thailand.