The importance of patient preferences in the measurement of health care satisfaction.
The idea that patients will be more satisfied with health care services that are delivered to meet their preferences is central to the concept of health care marketing. Health care providers increasingly use market segmentation and target marketing to optimize the fit between their services and the consumers who receive them. This study evaluates one model for incorporation of patient preferences into the measurement of satisfaction. Using multiple regression analysis, evaluations of three dimensions of health care satisfaction, interpersonal care, technical quality, access to care accounted for 63% of the variance in overall satisfaction. Inclusion of preferences, defined as importance ranks of each dimension, did not improve ability to predict satisfaction. Four preference segments were identified: interpersonal care seekers, access/quality seekers, access seekers and quality seekers. These four subgroups differed significantly on a number of sociodemographic, health status and health service use characteristics but no significant differences were found in satisfaction between preference segments. Patient satisfaction can best be measured as quality evaluations of dimensions without regard to preferences. In considering the merits of market segmentation and target marketing, alternative satisfaction models that link preferences to health care satisfaction or the possibility that preference targeting does not lead to greater satisfaction should be evaluated.
Ross
C K
CK
Department of Veterans Affairs, West Side Medical Center, Chicago, IL.
Steward
C A
CA
Sinacore
J M
JM
D003258:Consumer Behavior; D006304:Health Status; D006786:Hospitals, Urban / Q000592:standards / Q000706:statistics & numerical data; D006787:Hospitals, Veterans / Q000592:standards* / Q000706:statistics & numerical data; D006801:Humans; D008389:Marketing of Health Services; D008960:Models, Psychological; D017060:Patient Satisfaction / Q000706:statistics & numerical data*; D012044:Regression Analysis; D014481:United States