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Rev. méd. Chile ; 135(6): 696-701, jun. 2007. tab
Article in Spanish | LILACS | ID: lil-459571

ABSTRACT

Background: Client satisfaction is an important indicator of the quality of services, and health care is not an exemption. Aim: To explore and establish the predictors that exert the greater influence on the level of satisfaction with the service offered in a University Hospital. Material and method: The source of the study is a data base, obtained from a survery made to 355 patients of the Hospital Clínico de la Pontificia Universidad Católica de Chile prior to discharge. A multiple regression analysis was used to determine the relative importance of the different factors in the quality of service. The regression variables were reduced to a number of factors, obtained of Factorial Analysis and a Varimax rotation, allowing them to clarify their relations. Results: After performing the main components analysis, seven factors or dimensions that explained a 69 percent of the total variance were obtained. The predictive model explains up to 40 percent of the criterion variable (Global Satisfaction during the hospitalization). The factor with the greatest predictive power was the relationship between the patients and nursing staff. Other factors that emerged as important were communication, medical attention and room conditions. Conclusions: Perceptive type components had the greater relative weight to determine the level of patient satisfaction in this survey.


Subject(s)
Adolescent , Adult , Humans , Middle Aged , Delivery of Health Care/statistics & numerical data , Hospitalization/statistics & numerical data , Patient Satisfaction/statistics & numerical data , Quality Assurance, Health Care/standards , Quality Indicators, Health Care/standards , Analysis of Variance , Chile , Delivery of Health Care/standards , Health Care Surveys , Hospitals, University , Professional-Patient Relations , Quality Assurance, Health Care/statistics & numerical data , Quality Indicators, Health Care/statistics & numerical data , Regression Analysis
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