Koichiro Otani

Patient ratings of inpatient stay have been the focus of prior research since better patient satisfaction results in a financial benefit to hospitals and are associated with better patient health care outcomes. However, studies that simultaneously account for within- and between-hospital effects are uncommon. We constructed a multilevel structural equation model to identify predictors of patients’ willingness to recommend a hospital at both within-hospital and between-hospital levels. We used data from 60 U.S. general medical and surgical hospitals and 12,115 patients. Multilevel structural equation modeling reported that patient ratings on the overall quality of care significantly affect the willingness to recommend within hospitals. Also, patients’ perspectives on the hospital environment and nursing are the significant factors that predict the patient ratings on the overall quality of care. Overall patient satisfaction significantly predicts the willingness to recommend at the between-hospital level, whereas hospital size and location have marginal impacts.

Patient satisfaction studies have gained more and more attention, and there are many patient satisfaction studies. These studies assume that patients were selected randomly and independently, but patient satisfaction surveys are described as a multistage or hierarchically structured sample. Thus, there is a need to conduct a hierarchical linear model (HLM) analysis with a large number of hospitals. This study utilized an HLM to investigate both the individual patient-level effect on the overall satisfaction rating and the effect of hospital characteristics on the combining process of patient’s overall satisfaction rating. This study used patient satisfaction data collected from 100 hospitals with the sample size of 85 766. The hospital-level characteristics include total expense per personnel, payroll expense per personnel, number of staffed beds per personnel, and number of admission per personnel. This study found that hospital characteristics influence overall rating of the hospital through the doctor, staff, and room attributes. When considering the complex nature of the overall patient rating process of hospitals, it makes more sense to analyze hospital characteristics that are interacting with attributes rather than treat hospital characteristics as independent of these factors.

Patient satisfaction and how it is measured is an important field of study in healthcare. Consequently, there have been many patient satisfaction studies. However, there is a lack of studies that focused on how male and female patients perceive, or weigh, their overall satisfaction. Determining the weights of these attributes by gender is an important outcome to determine overall patient satisfaction and quality of care. Data were collected by applying the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey instrument to record regular patient experience at 70 United States hospitals. The data were collected between July 1, 2011 and June 30, 2012, and there are 43,938 cases in the data set. This study found that all five of the attributes (Nursing Care, Physician Care, Staff Care, Room, and Help) had an association with patient satisfaction. Among them, nursing Care had the largest influence on patient satisfaction of all of the five attributes. This study also showed a statistically significant interaction effect by gender for the interaction between Nursing care x Gender, Physician care x Gender, and Help x Gender. Female patients rated their relationship with their nurses as being more important to their overall satisfaction, while male patients rated their relationship with their doctor as being more important to overall satisfaction. Male patients also rated their relationship with help as being more important to overall satisfaction when compared with the results from female patients. Suggestions to healthcare managers are also discussed.

EXECUTIVE SUMMARY The purpose of this study was to investigate how patients’ self-rated health status (SRHS) is associated with their attribute reaction integration process and, in turn, their overall ratings of hospitals. We collected patient satisfaction data from 70 hospitals by means of a patient satisfaction questionnaire. The sample included patients who were 18 years or older and discharged from the hospital from July 1, 2011, through June 30, 2012. Data for 36,528 patients were available for analysis. We conducted multiple linear regression analysis with patients’ SRHS and interaction effects with nursing care, physician care, staff care, and room, while controlling for age, gender, race, and education. Study findings showed an association between SRHS levels and the patient’s overall rating of the hospital; they also revealed interaction effects with nursing care, physician care, and staff care variables in the model. The statistically significant interaction effects indicate that for patients whose SRHS was less than excellent, physician care became more important and nursing care and staff care became less important compared with patients whose SRHS was excellent. When we consider the nature of medical care, this transition seems reasonable. We also found that it is reasonable to categorize patients into two groups: those whose SRHS is excellent and those whose SRHS is less than excellent (i.e., very good, good, fair, or poor). As the study findings show, these two groups of patients combined their attribute reactions differently.

The authors evaluated whether a patient's perceived pain control influenced the relationships between four attributes (nursing, physician, staff, and environment) and patient satisfaction. Multiple linear regression analyses were conducted to examine overall satisfaction and intention to recommend, controlling for race, gender, age, and education. The authors found that no matter the level of pain control, nursing was always the most influential attribute in patient satisfaction. The influence of the other attributes varied, depending on the patients’ pain control. Hospital managers may improve patient satisfaction by focusing on pain management nursing care.

Context: Health care environments have been changing rapidly, and one of the changes is to emphasize patient satisfaction. However, most studies assume that all patients integrate their health care attribute reactions in the same way to arrive at their satisfaction. Objective: The objective of this study is to investigate how patients’ experience of pain influences their attribute reaction integration process and their overall rating of the hospital. Design: Patient satisfaction data were collected using a mailed questionnaire. Multiple linear regression analyses with a dichotomous (yes/no) pain variable and its interaction effects with nursing care, physician care, staff care, and hospital room were conducted with control variables. Main Outcome Measures: The pain variable was statistically significant and also revealed interaction effects with the physician care and the staff care variables in the model. Patients who needed medicine for pain showed lower overall rating of the hospitals than patients who did not need medicine. Results: The statistically significant interaction effects indicate that for patients who needed medicine for pain, staff care becomes more important and physician care becomes less important compared to patients who do not need medicine for pain. All 4 attributes (nursing care, physician care, staff care, and hospital room) are not equally influential. Conclusion: Implementing policies and procedures related to these interaction effects would lead to the most efficient and effective improvement outcomes. These findings suggest that future policies should be modified to enhance nursing and staff care to provide more direct care for patients with pain.

Most patient satisfaction studies put an emphasis on finding key drivers (attribute) to increase overall patient satisfaction. However, it is not clear how much health care managers need to improve certain attributes to attain the target overall patient satisfaction level. The study aims at finding not only what attributes, but also how much these attributes need to be improved to attain the target levels of patient satisfaction. The study uses an ordinal logistic regression model to analyze attribute reactions to salient drivers. This approach would significantly enhance health care managers' capabilities to develop a strategic plan to improve their patient satisfaction levels.

With increasing emphasis in healthcare on patient satisfaction, many patient satisfaction studies have been administered. Most assume that all patients combine their healthcare experiences (such as nursing care, physician care, etc.) in the same way to arrive at their satisfaction; however, no research has been conducted prior to the present study to investigate how patients' health conditions influence the way they combine their healthcare experiences. This study aims to determine how seriously ill patients differ from less seriously ill patients during their combining process. Data were collected from five large hospitals in the St. Louis area by administering a patient satisfaction questionnaire. Multiple linear regression analyses with a scatter term, a severity measure, and interaction effects of the severity measure were conducted while controlling for age, gender, and race. Two models (overall quality of care and willingness to recommend to others) were analyzed, and the severity of illness variable revealed interaction effects with physician care, staff care, food, and scatter term variables in the willingness to recommend model (six attributes were analyzed: admission process, nursing care, physician care, staff care, food, and room). With more seriously ill patients, physician care becomes more important and staff care becomes less important, and seriously ill patients are proportionately more likely to combine their attribute reactions only in the willingness to recommend model. All six attributes are not equally influential. Nursing care and staff care show consistent influence in both models. These findings show that if healthcare managers want to increase their patient satisfaction, they should enhance nursing care and staff care first to experience the most improvement.

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.