Description
For most health care organizations, the customer is the patient. Like other businesses, health care organizations are evaluated by many of the usual measures of customer satisfaction (e.g., convenience of location, ease of getting the appointment, waiting time, price, etc.). Unlike most businesses, health care organizations are also judged by patient outcomes. What the “customer” wants and what the “patient” needs may occasionally be in conflict, even though the “customer” and “patient” is the same person. This is one reason customer satisfaction for health care organizations can seem to be an elusive goal.
To prepare for this Discussion:
- Review this week’s Learning Resources.
- Locate and read a scholarly article that identifies factors that influence patient/customer satisfaction in a health care setting.
Post a brief description of and a link to the scholarly article. Then, identify and discuss what you believe is the most important factor that influences patient/customer satisfaction positively and negatively in health care. Finally, justify why those factors are important and address how the article you cited supports or refutes your opinion.
Support your work with specific citations from this week’s Learning Resources and/or additional sources as appropriate. Your citations must be in APA format.
Marketing Plan Components/Marketing Assessment
A health care organization’s marketing plan is a blueprint for how that organization intends to
achieve important goals and objectives, as specified in its strategic plan. In the course of
developing its marketing plan, the health care institution must evaluate its market, analyze its
product, and assess its competitors to identify where gaps, discrepancies, or market opportunities
may exist.
There is no single way to write a marketing plan; however, Philip Kotler, an academic and
marketing consultant, identifies eight components that a marketing plan should include
regardless of the industry (Fortenberry, 2010, pp. 266–271):
Executive Summary and Table of Contents (Content Page)
Current Marketing Situation
Opportunity and Issue, Analysis
Objectives (Goals)
Marketing Strategy
Action Programs
Financial Projections (Budget)
Implementation Controls
This week, you will examine more closely the elements of a health care organization’s marketing
plan and the role and importance of patient/customer satisfaction.
Fortenberry, J. L. (2010). Health care marketing: Tools and techniques. Sudbury, MA: Jones and
Bartlett Publishers.
•
•
•
Learning Objectives
Students will:
Define the elements of a marketing plan
Analyze a marketing plan for a health care organization
Describe factors that influence patient satisfaction
Patient Satisfaction:
Focusing on “Excellent”
Koichiro Otani, PhD, associate professor, Division of Public and Environmental
Affairs, Indiana University-Purdue University, Fort Wayne; Brian Waterman, director
of performance analytics, BJG Healthcare, St. Louis, Missouri; Kelly M. Faulkner,
performance research analyst, BJC HealthCare; Sarah Boslaugh, PhD, performance
research analyst, BJC HealthCare; Thomas E. Burroughs, PhD, executive director,
SLUCOR (Center for Outcomes Research), and professor of internal medicine and
health management and policy. Saint Louis University School of Medicine; and
W. Claiborne Dunagan, MD, vice president of system quality, BJC HealthCare
EXECUTIVE
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.
For more information on the concepts in this article, please contact Dr. Otani
at otanik@ipfw.edu. This study has been approved by the Institutional Review
Board at Purdue University, Ref. #0710005884.
93
JOURNAL OF HEALTHCARE MANAGEMENT 54:2
MARCH/APRIL 2009
M
ost 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;
Carr 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.
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, Confiicting findings regarding
these relationships have been observed,
however, Jn 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 ofthe studies
argued that to increase overall patient
satisfaction, healthcare providers should
focus on improving the attributes that
showed a strong rather than a weak
inñuence.
Other researchers focused on measurement tools and used sophisticated
statistical analyses to investigate the
validity and reliability of patient satis-
Only patients who mark “excellent”
are loyal patients and will support the
long-term survival ofthe 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.
94
PATIENT SATISFACTION: FOCUSING ON “EXCELLENT”
Because ofthe 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.
faction questionnaires. These studies
analyzed widely used Consumer Assessment of Health Plans (CAHPS®) 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).
Third, patient satisfaction is now
considered a key part ofthe 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
(Kongstvedt2001).
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).
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
95
JOURNAL OF HEALTHCARE MANAGEMENT 54:2
MARCH/APRIL 2009
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 pédiatrie
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.
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 ofthe 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.
This study utilized a telephonebased 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 postdischarge, and they were contacted until
final disposition (e.g., completion, reftisal, 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 a = 0.05. However,
this statistical difference may be partly
the result of the large sample size.
The independent variables describe
six attribute reactions to care: admission
process, nursing care, physician care,
staff care, food, and room. Each of the
six construct variables included multiple
questionnaire items in the survey that
measured the same construct variable
with the five-point, Likert-type scale.
The reliability and validity ofthe survey
instrument were evaluated and found
to be quite strong in numerous studies
that used a combination of principal
component analysis, confirmatory factor
analysis, and structural equation analysis (Burroughs et al. 1999; 2001). For
each of the six independent variables,
a composite index was created as the
arithmetic mean of all items measuring
the attribute. The descriptions, numbers
of respondents, mean scores, and standard deviations ofthe items are shown
in Table 1. The Cronbach’s coefficient
alpha was estimated to test the internal consistency of the items for each
Variables and Analysis
The survey collected information about
the patients’ ratings of their care. The
96
PATIENT SATISFACTION: FOCUSING ON “EXCELLI-NT’
TABLE 1
Descriptive Statistics of Survey Items and Composite Indexes
N
Mean
S.D.
4.08
1.01
Description
Admission Process
1
13,930
Promptness and efficiency of the admission or
registration
2
C.I.
13,990
4.27
.87
Courtesy and helpfulness at admission or registration
14,169
4.17
.87
Composite index: Cronbach’s a = .8165
Nursing Care
3
14,024
3.98
1.12
4
13,831
4.23
.98
Helpfulness of the nurses to reduce or eliminate any pain
5
14,365
4.21
.97
Nurses’ ability to communicate with you
6
14,271
4.16
.99
Nurses’ ability to provide adequate instructions or
Responsiveness of the nurses when you cal led
explanations of your treatment or tests
C.I.
14,425
4.14
.90
Composite index: Cronbach’s a = .9098
Availability of your doctor when needed
Physician Care
7
13,948
4.17
1.02
8
14,314
4.31
.94
Doctor’s ability to communicate with you
9
14,279
4.30
.93
Doctor’s ability to provide adequate instructions or
10
14,174
4.31
.93
Doctor’s involvement of you in decisions about your care
CI.
14,409
4.26
.87
Composite index: Cronbach’s a = .9284
4.19
.95
Staffs willingness to help if you had a question or
explanations of your treatment or tests
Staff Care
11
14,239
concern
12
14,246
4.09
1.01
13
14,360
4.23
.93
Courtesy and helpfulness of the staff
14
14,366
4.27
.92
Amount of dignity and respect shown by the staff
15
13,914
4.11
1.02
16
14,081
4.15
C.I.
14,294
4.17
.84
17
13,470
3.38
1.10
18
13,488
4.11
.94
C.I.
13,660
3.74
Responsiveness of the staff to your requests
Clear and complete explanation provided by the staff
about your medications and their side effects
.98
Clear and complete explanation provided by the staff
about how to care for yourself at home
Composite index: Cronbach’s a = .9300
Food
Rate the food that was delivered to your room
Rate the courtesy and helpfulness of the staff serving the
food
.92
Composite index: Cronbach’s a = .6147
continued
97
JOURNAL OF HEALTHCARE MANAGEMENT
TABLE 1
54 :2
MARCH/APRIL
2009
continued
N
Mean
19
14,364
4.00
1.04
20
13,131
4.10
.96
Description
S.D.
Room
Rate the cleanliness of your room
Rate the courtesy and helpfulness of the staff who
cleaned your room
C.L
13,644
4.03
.96
Composite index: Cronbach’s a = .8663
14,395
4.16
.98
Overall, rate the quality of care and services received
during this hospital stay
14,350
4.32
.97
Rate your willingness to recommend this hospital to
Dependent Variables
family and friends
C.I.
14,299
4.34
1.00
Rate your willingness to return to this hospital again
14,428
4.27
0.90
Composite index: Cronbach’s a = .9002
6,356 male patients and 8,076 female
patients. The race composition was
white: 9,055 or 73.91 percent, African American: 2,933 or 23.94 percent,
Hispanic: 26 or 0.21 percent, Asian: 51
or 0.42 percent, and others: 187 or 1.53
percent.
For the logistic regression analysis,
there were 5,532 patients in the “excellent” overall experience category and
8,896 patients in the “other” category.
The logistic regression analysis was
performed to measure the predictability
ofthe “excellent” rating, controlling for
age, gender, and race. A stepwise procedure was applied with a standard 0.05
entry criterion. The result ofthe multiple logistic regression analysis is shown
in Table 2.
The logistic regression analysis with
stepwise procedure selected admission process, nursing care, physician
care, staff care, food, room, and age as
attribute. These results are also shown in
Table 1.
The larger value ofthe alpha indicates that the items contribute to a reliable scale. Except for the food attribute,
which only contained two items, all
computed Cronbach’s alpha values for
this data set were larger than 0.80. This
indicates good internal consistency. The
control variables considered for analysis
included age, gender, and race. Because
the purpose ofthis study was to find
patients who report only “excellent, ”
multiple logistic regression analysis was
used. The data were analyzed to predict
which patients would potentially report
their overall experience as “excellent. ”
RESULTS
The analysis of the five-hospital data set
included 14,432 cases. The mean age
was 58.29 years old, and the standard
deviation was 17.21 years. There were
98
PATIENT SATISFACTION: FOCUSINC ON “EXCELLENT”
TABLE 2
Result of Multiple Logistic Regression Analysis witti Dictiotomous Overall Satisfaction as
Dependent Variable
Independent
Variable
Intercept
Admission
Nursing care
Physician care
Estimate
p Value
Odds Ratio
1,0653
< ,0001
< ,0001
< ,0001
N/A
1,627
2,902
-16.6235
0,4864
Odds Ratio
(95% CI)
N/A
1,507, 1.755
2,582,3,261
1,606, 1,930
0,5657
Purchase answer to see full
attachment
A health care organization’s marketing plan is a blueprint for how that organization intends to
achieve important goals and objectives, as specified in its strategic plan. In the course of
developing its marketing plan, the health care institution must evaluate its market, analyze its
product, and assess its competitors to identify where gaps, discrepancies, or market opportunities
may exist.
There is no single way to write a marketing plan; however, Philip Kotler, an academic and
marketing consultant, identifies eight components that a marketing plan should include
regardless of the industry (Fortenberry, 2010, pp. 266–271):
Executive Summary and Table of Contents (Content Page)
Current Marketing Situation
Opportunity and Issue, Analysis
Objectives (Goals)
Marketing Strategy
Action Programs
Financial Projections (Budget)
Implementation Controls
This week, you will examine more closely the elements of a health care organization’s marketing
plan and the role and importance of patient/customer satisfaction.
Fortenberry, J. L. (2010). Health care marketing: Tools and techniques. Sudbury, MA: Jones and
Bartlett Publishers.
•
•
•
Learning Objectives
Students will:
Define the elements of a marketing plan
Analyze a marketing plan for a health care organization
Describe factors that influence patient satisfaction
Patient Satisfaction:
Focusing on “Excellent”
Koichiro Otani, PhD, associate professor, Division of Public and Environmental
Affairs, Indiana University-Purdue University, Fort Wayne; Brian Waterman, director
of performance analytics, BJG Healthcare, St. Louis, Missouri; Kelly M. Faulkner,
performance research analyst, BJC HealthCare; Sarah Boslaugh, PhD, performance
research analyst, BJC HealthCare; Thomas E. Burroughs, PhD, executive director,
SLUCOR (Center for Outcomes Research), and professor of internal medicine and
health management and policy. Saint Louis University School of Medicine; and
W. Claiborne Dunagan, MD, vice president of system quality, BJC HealthCare
EXECUTIVE
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.
For more information on the concepts in this article, please contact Dr. Otani
at otanik@ipfw.edu. This study has been approved by the Institutional Review
Board at Purdue University, Ref. #0710005884.
93
JOURNAL OF HEALTHCARE MANAGEMENT 54:2
MARCH/APRIL 2009
M
ost 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;
Carr 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.
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, Confiicting findings regarding
these relationships have been observed,
however, Jn 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 ofthe studies
argued that to increase overall patient
satisfaction, healthcare providers should
focus on improving the attributes that
showed a strong rather than a weak
inñuence.
Other researchers focused on measurement tools and used sophisticated
statistical analyses to investigate the
validity and reliability of patient satis-
Only patients who mark “excellent”
are loyal patients and will support the
long-term survival ofthe 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.
94
PATIENT SATISFACTION: FOCUSING ON “EXCELLENT”
Because ofthe 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.
faction questionnaires. These studies
analyzed widely used Consumer Assessment of Health Plans (CAHPS®) 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).
Third, patient satisfaction is now
considered a key part ofthe 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
(Kongstvedt2001).
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).
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
95
JOURNAL OF HEALTHCARE MANAGEMENT 54:2
MARCH/APRIL 2009
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 pédiatrie
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.
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 ofthe 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.
This study utilized a telephonebased 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 postdischarge, and they were contacted until
final disposition (e.g., completion, reftisal, 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 a = 0.05. However,
this statistical difference may be partly
the result of the large sample size.
The independent variables describe
six attribute reactions to care: admission
process, nursing care, physician care,
staff care, food, and room. Each of the
six construct variables included multiple
questionnaire items in the survey that
measured the same construct variable
with the five-point, Likert-type scale.
The reliability and validity ofthe survey
instrument were evaluated and found
to be quite strong in numerous studies
that used a combination of principal
component analysis, confirmatory factor
analysis, and structural equation analysis (Burroughs et al. 1999; 2001). For
each of the six independent variables,
a composite index was created as the
arithmetic mean of all items measuring
the attribute. The descriptions, numbers
of respondents, mean scores, and standard deviations ofthe items are shown
in Table 1. The Cronbach’s coefficient
alpha was estimated to test the internal consistency of the items for each
Variables and Analysis
The survey collected information about
the patients’ ratings of their care. The
96
PATIENT SATISFACTION: FOCUSING ON “EXCELLI-NT’
TABLE 1
Descriptive Statistics of Survey Items and Composite Indexes
N
Mean
S.D.
4.08
1.01
Description
Admission Process
1
13,930
Promptness and efficiency of the admission or
registration
2
C.I.
13,990
4.27
.87
Courtesy and helpfulness at admission or registration
14,169
4.17
.87
Composite index: Cronbach’s a = .8165
Nursing Care
3
14,024
3.98
1.12
4
13,831
4.23
.98
Helpfulness of the nurses to reduce or eliminate any pain
5
14,365
4.21
.97
Nurses’ ability to communicate with you
6
14,271
4.16
.99
Nurses’ ability to provide adequate instructions or
Responsiveness of the nurses when you cal led
explanations of your treatment or tests
C.I.
14,425
4.14
.90
Composite index: Cronbach’s a = .9098
Availability of your doctor when needed
Physician Care
7
13,948
4.17
1.02
8
14,314
4.31
.94
Doctor’s ability to communicate with you
9
14,279
4.30
.93
Doctor’s ability to provide adequate instructions or
10
14,174
4.31
.93
Doctor’s involvement of you in decisions about your care
CI.
14,409
4.26
.87
Composite index: Cronbach’s a = .9284
4.19
.95
Staffs willingness to help if you had a question or
explanations of your treatment or tests
Staff Care
11
14,239
concern
12
14,246
4.09
1.01
13
14,360
4.23
.93
Courtesy and helpfulness of the staff
14
14,366
4.27
.92
Amount of dignity and respect shown by the staff
15
13,914
4.11
1.02
16
14,081
4.15
C.I.
14,294
4.17
.84
17
13,470
3.38
1.10
18
13,488
4.11
.94
C.I.
13,660
3.74
Responsiveness of the staff to your requests
Clear and complete explanation provided by the staff
about your medications and their side effects
.98
Clear and complete explanation provided by the staff
about how to care for yourself at home
Composite index: Cronbach’s a = .9300
Food
Rate the food that was delivered to your room
Rate the courtesy and helpfulness of the staff serving the
food
.92
Composite index: Cronbach’s a = .6147
continued
97
JOURNAL OF HEALTHCARE MANAGEMENT
TABLE 1
54 :2
MARCH/APRIL
2009
continued
N
Mean
19
14,364
4.00
1.04
20
13,131
4.10
.96
Description
S.D.
Room
Rate the cleanliness of your room
Rate the courtesy and helpfulness of the staff who
cleaned your room
C.L
13,644
4.03
.96
Composite index: Cronbach’s a = .8663
14,395
4.16
.98
Overall, rate the quality of care and services received
during this hospital stay
14,350
4.32
.97
Rate your willingness to recommend this hospital to
Dependent Variables
family and friends
C.I.
14,299
4.34
1.00
Rate your willingness to return to this hospital again
14,428
4.27
0.90
Composite index: Cronbach’s a = .9002
6,356 male patients and 8,076 female
patients. The race composition was
white: 9,055 or 73.91 percent, African American: 2,933 or 23.94 percent,
Hispanic: 26 or 0.21 percent, Asian: 51
or 0.42 percent, and others: 187 or 1.53
percent.
For the logistic regression analysis,
there were 5,532 patients in the “excellent” overall experience category and
8,896 patients in the “other” category.
The logistic regression analysis was
performed to measure the predictability
ofthe “excellent” rating, controlling for
age, gender, and race. A stepwise procedure was applied with a standard 0.05
entry criterion. The result ofthe multiple logistic regression analysis is shown
in Table 2.
The logistic regression analysis with
stepwise procedure selected admission process, nursing care, physician
care, staff care, food, room, and age as
attribute. These results are also shown in
Table 1.
The larger value ofthe alpha indicates that the items contribute to a reliable scale. Except for the food attribute,
which only contained two items, all
computed Cronbach’s alpha values for
this data set were larger than 0.80. This
indicates good internal consistency. The
control variables considered for analysis
included age, gender, and race. Because
the purpose ofthis study was to find
patients who report only “excellent, ”
multiple logistic regression analysis was
used. The data were analyzed to predict
which patients would potentially report
their overall experience as “excellent. ”
RESULTS
The analysis of the five-hospital data set
included 14,432 cases. The mean age
was 58.29 years old, and the standard
deviation was 17.21 years. There were
98
PATIENT SATISFACTION: FOCUSINC ON “EXCELLENT”
TABLE 2
Result of Multiple Logistic Regression Analysis witti Dictiotomous Overall Satisfaction as
Dependent Variable
Independent
Variable
Intercept
Admission
Nursing care
Physician care
Estimate
p Value
Odds Ratio
1,0653
< ,0001
< ,0001
< ,0001
N/A
1,627
2,902
-16.6235
0,4864
Odds Ratio
(95% CI)
N/A
1,507, 1.755
2,582,3,261
1,606, 1,930
0,5657
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