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Weekly UpdatesEXECUTIVE SUMMARY
In an emerging competitive market such as healthcare, managers should focus on achieving excellent ratings to distinguish their organization from others. When it comes to customer loyalty, "excellent" has a different meaning. Customers who are merely satisfied often do not come back. The purpose of this study was to find out what influences adult patients to rate their overall experience as "excellent." The study used patient satisfaction data collected from one major academic hospital and four community hospitals.
After conducting a multiple logistic regression analysis, certain attributes were shown to be more likely than others to influence patients to rate their experiences as excellent. The study revealed that staff care is the most influential attribute, followed by nursing care. These two attributes are distinctively stronger drivers of overall satisfaction than are the other attributes studied (i.e., physician care, admission process, room, and food). Staff care and nursing care are under the control of healthcare managers. If improvements are needed, they can be accomplished through training programs such as total quality management or continuous quality improvement, through which staff employees and nurses learn to be sensitive to patients' needs. Satisfying patients' needs is the first step toward having loyal patients, so hospitals that strive to ensure their patients are completely satisfied are more likely to prosper.
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Most patient satisfaction studies use a Likert-type scale, with 5 indicating "excellent," 4 "very good," 3 "good," 2 "fair," and 1 "poor." This type of scale is often assumed to be an equal-interval scale, where "excellent" is one unit better than "very good," "very good" is one unit better than "good," and so forth. Many managers may think a "very good" rating is good enough. They may think the cost of improving the rating to "excellent" is too high. They may also think it is more cost effective to focus on unsatisfied patients. However, when it comes to customer loyalty, "excellent" has a different meaning from the other rating categories. Customers who are merely satisfied often do not come back (Jones and Sasser 1995; Stewart 1997; Cart 1999). In an emerging competitive market such as healthcare, managers should focus on achieving excellent ratings to distinguish their organization from others. The long-term survival of hospitals depends on loyal patients who come back or recommend the hospital to others.
Only patients who mark "excellent" are loyal patients and will support the long-term survival of the hospitals. Patients who are merely satisfied will move to another provider when they have an opportunity (Jones and Sasser 1995). Even though the cost of switching hospitals is quite high, patients have more choices now than they did in previous eras. Many patients are better educated and have access to more information via the Internet. The increasingly competitive nature of the healthcare market makes it more important than ever for healthcare organizations to focus on "excellent" patient satisfaction ratings.
Few studies specifically investigate "excellent" ratings in healthcare, despite the fact that there have been many patient satisfaction studies. First-generation patient satisfaction studies were aimed at identifying the demographic variables associated with patient satisfaction (Dansky and Brannon 1996). They analyzed patients' demographic backgrounds--such as age, gender, race, and education--and found correlations between these variables and patient satisfaction. Conflicting findings regarding these relationships have been observed, however. In addition, these variables are not modifiable, so healthcare managers could not use the findings to improve patient satisfaction. The next generation of studies focused on multidimensional constructs of patient satisfaction (Ware, Davies-Avery, and Stewart 1978; Ware, Snyder, and Wright 1976). They identified significant healthcare attributes related to overall patient satisfaction, including accessibility, availability of resources, continuity of care, efficacy of care, finances, humaneness, information giving or gathering, pleasantness of surroundings, and competence of providers. Subsequent studies used this multidimensional perspective and found that some healthcare attributes were stronger than others in increasing patient satisfaction. Thus, the authors of the studies argued that to increase overall patient satisfaction, healthcare providers should focus on improving the attributes that showed a strong rather than a weak influence.
Other researchers focused on measurement tools and used sophisticated statistical analyses to investigate the validity and reliability of patient satisfaction questionnaires. These studies analyzed widely used Consumer Assessment of Health Plans (CAHPS[R]) data sets and confirmed their validity and reliability. However, because patients who completed the survey had not been randomly assigned to health plans or providers, study authors claimed that it was not reasonable to compare satisfaction levels across healthcare plans or providers without adjustment on patients' case mix (Marshall et al. 2001; Zaslavsky et al. 2000).
Recently, a new group of patient satisfaction studies has emerged. These studies combined psychological theories and quantitative models in patient satisfaction studies and found that patients do not simply average out their attribute reactions with weights to form their overall satisfaction. Rather, they are disproportionately influenced by a weaker attribute reaction (Otani et al. 2003; Otani, Harris, and Tierney 2003;
Otani and Kurz 2004; Otani and Harris 2004; Otani, Kurz, and Harris 2005). Findings from these studies would allow healthcare managers to increase patients' satisfaction levels efficiently by identifying the specific attributes on which they should focus. However, simply increasing patient satisfaction levels is not the same as having patients mark "excellent."
Of course, one of the reasons for conducting patient satisfaction studies is that satisfied patients will likely come back (Ford, Bach, and Fottler 1997). However, there are other important reasons. First, satisfied patients tend to comply with prescribed medical treatments (Ford, Bach, and Fottler 1997; Eisenberg 1997; Williams 1994). Because of the increase of chronic diseases, patients must adhere to the treatment regimen prescribed. Second, satisfied patients are less likely to "doctor shop" and will instead stay with the same provider (Ford, Bach, and Fottler 1997; Eisenberg 1997). When a patient changes physicians, he or she may be required to retake tests, which increases the patient's costs and may hurt the patient.
Third, patient satisfaction is now considered a key part of the healthcare quality improvement initiative (Nelson and Niederberger 1990; Shortell and Kaluzny 2000). While healthcare quality was once evaluated only by professionals, patient satisfaction (along with mortality, morbidity, and other factors) is now part of the healthcare outcomes dimension. Even though patient satisfaction is a subjective judgment, it is nonetheless a critical component in healthcare outcomes. Fourth, many managed care organizations use patient satisfaction data to determine reimbursement rates to healthcare providers, and many leading companies will not contract with health plans that do not require a patient satisfaction survey. Providers with positive patient satisfaction survey results may receive more financial incentives than providers with poor patient satisfaction survey results (Kongstvedt 2001).
METHODOLOGY
Data Collection
Data sets used in the study were provided by BJC HealthCare, a regional, integrated healthcare delivery system serving the St. Louis metropolitan area as well as mid-Missouri and southern Illinois. Thirteen hospitals comprise the system, and five of these hospitals were included in this study. The eight excluded hospitals are different in size and location and do not maintain patients' demographic data for analysis. The Children's Hospital is a pediatric hospital and was excluded because most patients are younger than 20 years. The five hospitals included were one major academic hospital and four large community hospitals.
This study utilized a telephone-based survey of discharged patients. A national telephone survey company that specializes in patient satisfaction measurement conducted all interviews. For each hospital, the company drew a stratified random sample of patients from all candidate units. Patients were initially contacted 7 to 14 days post-discharge, and they were contacted until final disposition (e.g., completion, refusal, unable to reach) over the course of two weeks. Participants in the study (n = 14,432} were 20 years or older and were discharged from one of the five hospitals between January 2005 and November 2007. The response rate for the study period among the sample was 37 percent. Responders and nonresponders were compared regarding gender and age. No significant difference was found between the rates of male and female responders. Responders were older by 4.07 years than nonresponders, and it was statistically significant at [alpha] = 0.05. However, this statistical difference may be partly the result of the large sample size.
Variables and Analysis
The survey collected information about the patients' ratings of their care. The dependent variable was computed as a mean of three items: (1) Overall, how would you rate the quality of care and services received during this hospital stay? (2) How would you rate your willingness to recommend this hospital to family and friends? (3) How would you rate your willingness to return to this hospital? The answer choices for each item were "excellent," "very good," "good," "fair," and "poor." The coding in this survey was as follows: "excellent" = 5, "very good" = 4, "good" = 3, "fair" = 2, and "poor" = 1. After obtaining the mean score of the three items for each patient, the score of 5 was re-coded as 1 and all other scores were re-coded as 0. Thus, only cases where patients marked "excellent" on all three items were recoded as 1.
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