Predictive Validity of the International Hospital Outcomes Study Questionnaire: An RN4CAST Pilot Study

Abstract

Purpose: To study the predictive validity of the instrument used in the International Hospital Outcomes Study (IHOS) for an upcoming EU‐funded project (RN4CAST), which will indicate the effect of the nursing work environment and nursing staff deployment on nurse recruitment, retention, and productivity; and on patient outcomes in 11 European countries. Methods: Cross‐sectional analysis of data from 179 nurses (75% response rate) who completed an IHOS‐like nurse survey questionnaire, which included the Revised Nursing Work Index and the Maslach Burnout Inventory. The nurses worked in four Belgian acute‐care hospitals. Logistic regression modeling was performed to explore associations between nurse‐perceived outcomes and nursing work environment factors that were checked with confirmatory factor analysis. Findings: We confirmed associations between nurse‐perceived outcomes and the following nursing work environment factors: nurse‐physician relationship; staffing, and resource adequacy; and nurse manager ability, leadership, and support of nurses. A 1‐point increase in the rating of the factor nurse‐physician relationship was significantly associated with a 2.5‐fold (OR, 2.53; 95%CI, 1.29–4.93; pOR, 4.02; 95%CI, 1.85–8.70; pOR, 2.81; 95%CI, 1.38–5.72; pOR, 0.23; 95%CI, 0.12–0.47; p<0.001) decrease in the odds of reporting burnout. Conclusions: The predictive validity of the IHOS instrument was supported by the confirmation of key factors, which were previously identified by previous international research, and by the finding of similar associations between these factors and nurse‐perceived outcomes. The IHOS questionnaire that will be used in the RN4CAST project is robust and psychometrically sound. Clinical Relevance: The RN4CAST consortium, consisting of members from 15 countries, will use a similar instrument to that used in the International Hospital Outcomes study to measure the nursing work environment. This information will be linked with patients’ experiences and data extracted from routinely collected hospital discharge data. RN4CAST will show the important role of nursing staff in providing high quality care and allow refinement of current forecasting models for personnel planning in nursing.