Research Article
Merino-Plaza MJ, Carrera-Hu
Abstract
Aim: To identify dimensions with the greatest impact on health staff job satisfaction, evaluating their evolution over time and selecting the most sensitive monitoring indicators to detecting changes. Methods: Two cross-sectional studies were conducted in 2013 and 2016. The population studied was the staff of a Long Stay Chronic Care hospital in Valencia (n 2013=313; n 2016=312). The assessment tool used was the Corporate Osakidetza Satisfaction Survey, based on the EFQM Excellence Model, developed and validated by the Basque Health Service for the evaluation and improvement of people’s job satisfaction in public utility companies. Predictive variables were socio-demographic characteristics and professionals ratio with excellent perception of the organizational variables that define Job Satisfaction. Outcome variable was high job satisfaction, defined as a score ≥ 75th percentile. The association between variables was quantified by Odds Ratio. Results: Mean job satisfaction was 7 in both studies, being a poor indicator of change. The highest rated aspects in both surveys were healthcare quality and relationship with supervisor, and the worst were hospital management perception and recognition. In the stratified analysis, socio-demographic variables had little significance, while an excellent perception in some of the considered dimensions, and were associated with high job satisfaction. The most strongly associated aspects were communication, working environment and training. In the comparative study, indicators based on individual dimensions detected changes better than the assessment of overall satisfaction. Conclusions: Job satisfaction surveys are a useful tool to evaluate the perception of professionals and to detect improvement areas. The choice of appropriate indicators optimizes the information obtained through these surveys. According to our results, graphical representation of the percentage of satisfied professionals for each of the analyzed dimensions is the best indicator to detecting changes and detected differences that were not evident in the rest of indicators analyzed.