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Patient experience has been one of many significant drivers in determining hospitals' performance. Multivariate logistic regression was used to investigate the factors that impacted patients' likelihood to give top ratings for the overall hospital experience. Large hospitals with a lower percentage of Medicare/Medicaid patients and existing electronic health record system were more likely to receive top ratings. White, female patients with lower education levels were more likely to give top ratings for all quality domains (nurse, doctor, staff, and environment). All quality domains had positive impacts on patient experience, with the nursing domain being the most influential factor.

This article presents the rationale for using multilevel analysis to address the broad environmental contexts in patient satisfaction research. This study utilized patient satisfaction data and the American Hospital Association Hospital Guide Book (2004). This study found significant contributions of individual patient attribute reactions (nursing care, physician care, etc.), and also clearly demonstrated hospital-level effects and cross-level interactions on patient satisfaction. Thus, it is clear that patient satisfaction is not solely explained by patients' attribute reactions and their demographic variables, but is also explained by patients' hospital levels. This approach would offer additional understanding in patient satisfaction research.

Health-care managers have to address many aspects of the organization, and patient satisfaction is clearly one of the critical aspects for managers. To respond to the need of health-care managers, there have been many patient satisfaction studies. However, these studies focus on which attributes (factors such as nursing care and physician care) are more influential; they do not provide specific aspects for each attribute. In order to develop an effective intervention programme to improve patient satisfaction, more specific research outcomes are needed. This study utilized data collected between January 2007 and June 2008 from 32 hospitals representing a large, national private not-for-profit hospital system. The patient satisfaction survey included the Consumer Assessment of Healthcare Providers and Systems, Hospital version questionnaire items, and there are 31,471 cases. Two-stage multiple linear regression analyses were conducted with control variables (age, gender, perceived health, education and race). It was found that patients' highest priority is to be treated with courtesy and respect by nurses and physicians. An effective intervention programme to improve patient satisfaction would include a training programme, where care providers understand that patients want them to show courtesy and respect. Then, well-trained and empathetic nurses and staff members can comfort patients, and consequently improve patient satisfaction.

Background: Satisfaction with health care is one of the most widely assessed measures of hospital care quality, yet studies that account for clustering effects are uncommon. We constructed a multilevel model to identify predictors of willingness to recommend while controlling for clustering effects due to hospital and care unit. We also examined differences in predictors by care unit., Purpose: The aim of this study was to identify factors that both influence patient perceptions of care and are potentially modifiable by the hospital delivering care., Methodology: Our sample includes Hospital Consumer Assessment of Healthcare Providers and Systems survey data collected between July 1, 2007, and June 30, 2008, for 131 hospitals and 33,445 patients. The primary outcome was willingness to recommend the hospital to family and friends. Variables were collected at three levels: patient (Hospital Consumer Assessment of Healthcare Providers and Systems survey item responses and demographics), care unit, and hospital. Data were analyzed using multilevel modeling. We also ran a series of two-level models to explore differences in predictors by care type., Findings: The strongest predictors of willingness to recommend, controlling for clustering effects, were items that generally reflected interpersonal aspects of care such as nursing and physician behaviors. In the two-level models, predictors of willingness to recommend overlapped across care units, but important differences were noted., Practice Implications: Our results suggest that hospitals that wish to improve their performance would benefit most from focusing on interpersonal aspects of care. Hospitals that focus resources on improving in these areas, that assess care units separately, and that investigate the meaning and context of survey responses will be most likely to see improvements in satisfaction scores.

Background: Patient satisfaction studies have received strong attention from both health care managers and researchers. Many of them investigate how patients combine their health care attribute reactions to arrive at their overall satisfaction. These studies, however, did not specifically investigate a possible different combining process among different racial groups. Thus, these minority populations were statistically marginalized in the outcomes of the analyses. It means that parameter estimates of the attributes were assumed to be the same for all racial groups., Purpose: This study investigated a possible different combining process between Caucasian and African American patients. The objective of this study was to discover how differently Caucasian and African American patients combine their attribute reactions to arrive at their overall satisfaction., Methodology/approach: Data used for this analysis were collected from 32 hospitals by using a patient satisfaction questionnaire, the Consumer Assessment of Healthcare Providers and Systems, Hospital version. There were 29,684 cases. A multiple linear regression analysis with a scatter term was conducted while controlling for age, gender, perceived health, and educational attainment., Findings: Caucasian and African American patients recognize the same four attribute reactions (nursing care, staff care, physician care, and environment). However, when paying attention to the sizes of the parameter estimates (weights), these two groups show a clear difference. It is also found that Caucasian patients are risk averse. On the other hand, African American patients are likely to average out their attributes reactions proportionately., Practice Implications: The critical differences found in this study provide a very important implication for health care managers developing an intervention program to improve patient satisfaction. A one-size-fits-all strategy would not work for all patients. Caucasian and African American patients are different, and each requires a different intervention program to improve their overall evaluation of their hospital stay.

Healthcare costs in the U.S. are the highest in the world and are increasing rapidly. With increasing costs, employers and health insurance companies are trying to contain the cost of healthcare. This study aims at developing a predictive model relating enrollees' healthcare insurance claims to their health risks while controlling for gender, age, and their previous year's claims. Our study findings suggest that age, gender, and a previous year's healthcare expenditure are strong predictors of healthcare cost and that none of the six biomarkers was a significant predictor. Even though these biomarkers failed to contribute to the predictive model, they are, nonetheless, important predictors of future chronic diseases, many of which are leading causes of death in the U.S.