[Patient satisfaction in hemodialysis: a pilot cross-sectional analysis and a review].

BACKGROUND: Assessment of patient satisfaction is not performed routinely in many healthcare institutions. In this review, we discuss methodological aspects of assessment of patient satisfaction in hemodialysis. We also present a pilot study conducted in the Gambro Healthcare Italy dialysis clinics network. METHODS: Patient satisfaction was assessed in a network of hemodialysis units by using an internally validated Italian translation of the Choices for Healthy Outcomes in Caring for ESRD (CHOICE) questionnaire. A cross-sectional analytic study design was used and data analysed with univariate and multivariate hierarchical logistic regression to explore correlates of the risk of being unsatisfied with dialysis treatment. Covariates which were considered include a series of over 20 clinical, demographic, organizational and structural aspects. In addition, unexplained inter-centre residual variability due to 'case-mix' was explored and plotted. RESULTS: Seventeen dialysis units participated in this cross-sectional analysis and 758/1001 (75.7%) provided answers to the questionnaires. There was a statistically significant association on multivariate hierarchical analysis between the risk of being unsatisfied with dialysis treatment and interdialysis body weight gain (unit of increase: 1 kg, p=0.004). On the contrary, the risk of unsatisfaction with dialysis treatment was significantly lower in patients with higher dry weight (unit of increase: 1 kg, p=0.002). Our multivariate hierarchical analysis identified some residual variability between dialysis units (n=6 outliers) which may not be explained by any of over 20 potential confounding covariates which were explored. CONCLUSIONS: Assessment of ''customer satisfaction'' is standard practice in private for profit product companies in general but needs to be increasingly recognized as a standard in both public and private providers of healthcare services. Social research methods, which are used for this type of analysis, need to be fine tuned and actively implemented in order to better understand how we may influence the quality of service we provide to our patients and the level at which they rate it.