health-care quality management using the mbhcp excellence model

Health-care quality management using the MBHCP excellencemodel

Sang M. Leea, DonHee Leeb∗ and David L. Olsona

aDepartment of Management, University of Nebraska-Lincoln, Lincoln 68588-0491, NE, USA;bBK21, Sogang Business School, Sogang University, Seoul 121-742, South Korea

To publicise the quality of care they provide, health-care providers strive to have theirmanagement achievements recognised by such global evaluators as the MalcolmBaldrige National Quality Award (MBNQA), European Foundation for QualityManagement Excellence Model, and Joint Commission Model of Accreditation. Thisstudy developed a research model to examine the relationships among the sevencategories of MBNQA in the health-care industry. The proposed model, usingstructural equation modelling (SEM), tested hypotheses based on the data collectedfrom 254 hospitals. The results of the study indicate that the seven categories of careand service processes are positively associated with each category of MBNQA in thehealth-care industry. Also, MBNQA can play a role as an appropriate framework ofinternational standards criteria for quality improvement in the global health-careindustry. To alleviate the limitations of the study, future research needs to includecomparative studies of international standards/criteria and/or awards, cross-cultureanalysis of health-care providers in different countries, and a longitudinalinvestigation of the quality criteria and their impact on organisational performance.Also, moderating effects by SEM could be indicated.

Keywords: Malcolm Baldrige Health Care Criteria for Performance ExcellenceModel; quality management; health care; structural equation modelling

1. Introduction

Health-care organisations strive to improve the quality of care and safety for patients in an

environment where there are often constraints imposed by government regulations, human

resources, finances, medical technology, and the like. A variety of quality models such as

the Malcolm Baldrige Health Care Criteria for Performance (MBHCP) Excellence Model,

European Foundation for Quality Management (EFQM) Excellence Model, and Joint

Commission Model of Accreditation (JCA) have been introduced as primary tools to

recognise quality excellence in health care (Bou-Llusar, Escrig-Tena, Roca-Puig, &

Beltran-Martın, 2009; Garengo, 2009; Sanguesa, Mateo, & Ilzarbe, 2007). According to

the National Institute of Standards and Technology (NIST, 2008), which manages the

Malcolm Baldrige National Quality Award (MBNQA), more than 40 US states and 45

countries worldwide have implemented quality programmes based on the Baldrige

criteria.

MBNQA has been recognised as a valuable award demonstrating service quality excel-

lence in the health-care industry since 1999. The 2011 MBNQA recipients were selected

from a pool of 69 applicant organisations. Among the 69 applications filed, 40 were from

the health-care industry, 6 of the 11 site visits were conducted in hospitals, and 3 of the

eventual four awards were presented to hospitals (NIST, 2012). These facts show that

# 2013 Taylor & Francis

∗Corresponding author. Email: [email protected]

Total Quality Management, 2013

Vol. 24, No. 2, 119–137, http://dx.doi.org/10.1080/14783363.2012.728853

the medical industry has been striving to improve quality of care and safety, reduce

medical errors and costs, and improve performance.

The goals of quality management (QM) in the health-care system are to improve the

quality of care and service and operational efficiency, and eventually provide superior

organisational performance (OP) (Evans, 2010; Goldstein & Schweikhart, 2002; He,

Hill, Wang, & Yue, 2011; Lee, Lee, & Kang, 2012; Lee, Lee, & Schniederjans, 2011;

Meyer & Collier, 2001; Minkman, Ahaus, & Huijsman, 2007; Stankard & Snell, 2007;

van Matre & Koch, 2009). Figure 1 shows the process of care and service in the health-

care system, which includes two major actors: suppliers and customers. Hospitals

provide actual or required quality of care and service to patients. When patients and

their family members choose a hospital, they have certain expectations about the

quality of care and service offered by the hospital because they directly or indirectly

have prior knowledge about the hospital. Herzlinger (2006) suggested that patients

enjoy sharing their experience of, and information about, treatment with other people.

For example, positive word of mouth from satisfied patients can create opportunities for

potential customers to use the hospital service, which results in the improved performance

of the hospital. Quality in the service industry is challenging because the customer evalu-

ates experiences based on their expectations vis-a-vis the actual quality of service. Fundin

and Bergman (2003) suggested a positive expectation of customers could be accomplished

by using customers’ feedback including even their complaints. Therefore, quality of care

plays a role as a moderator between customers and hospitals and is a critical success factor

(CFS) for improving customer satisfaction as a high quality of care and service leads to a

higher level of customer satisfaction.

Previous research on QM in health care has focused mainly on quality of care using

the quality models (e.g. MBHCP, EFQM, JCA, and ISO 9000 series) to examine

relationships among quality-related constructs (Chong, Calingo, Reynolds, & Fisher,

2003; Goldstein & Schweikhart, 2002; Jayamaha, Grigg, & Mann, 2008; Lee, Rho, &

Lee, 2003; Meyer & Collier, 2001; Wilson & Collier, 2000). Although the MBHCP

criteria measure the data and information at a hospital, quality results based on

patient treatment would come from activities (e.g. leadership, patient and workforce

focus, process management, etc.) provided by organisational support (Meyer &

Collier, 2001).

The purpose of this study is to empirically test the relationships among the seven cat-

egories of care and service process for improving quality outcomes in the health-care

Figure 1. Care and service process chain in the health-care system.

120 S.M. Lee et al.

industry. Most of previous studies used the original Baldrige criteria applied to manufac-

turing to evaluate these relationships. Even though the health-care system used Baldrige

criteria (Meyer and Collier (2001) used the 1995 MBNQA Health Care Pilot Criteria

Model), the framework has changed over the years based on the global environment.

Therefore, the research model proposed in this study is based on the 2010 MBHCP

Model and previous studies. Data are collected from the QM department in selected hos-

pitals. The proposed research model is tested using the structural equation modelling

(SEM) approach. The rest of this paper is organised as follows: Section 2 presents a

review of previous studies and proposes a research model and hypotheses; Section 3

shows a research methodology; Section 4 reports the result of the model; and Section 5,

the conclusion and limitation of the study.

2. Literature review

QM is an organisational effort to achieve quality products and services, performance, and

a greater market share. A variety of QM practices based on MBNQA, EFQM, ISO 9000,

Six Sigma, total quality management (TQM), quality control, benchmarking, zero-defects

management, and quality function deployment have been developed and applied in many

organisations throughout the world.

Originally, QM began its implementation in manufacturing and thus previous studies

on MBNQA were primarily in the related industries. As shown in Figure 2, the number of

applications for MBNQA in the manufacturing industry from 1988 to 1997 decreased sig-

nificantly and more steadily from 2005 to 2011.

The health-care industry, on the other hand, has seen a dramatic increase in the number

of MBNQA applications, quite a contrast from manufacturing industries. Although the

number of health-care applicants is down to 40 in 2011 from 54 in 2010, three of the

four 2011 MBNQA winners were health-care organisations. There appear to be some

Figure 2. MBNQA applications’ 1988–2011.Source: Fact sheets from NIST (2012).

Total Quality Management 121

reasons for the reduced number of applications from the manufacturing sector; it takes a

long period of time and an enormous amount of effort to prepare the MBNQA application,

the preparation process is too complex, and it requires high cost and manpower. Conse-

quently, when an organisation contemplates applying for MBNQA, it must consider the

opportunity cost. The firm can invest the same amount of funds in R&D for possibly a

greater benefit than in preparing for the MBNQA application. Thus, potential applicants

now carefully evaluate the cost-benefit of the application process according to previous

winners of MBNQA.

2.1 Health-care studies on MBNQA

Health-care has become a critical global issue with the increased concerns for care

quality and patient safety in recent years (DeJong, 2009; Goldstein & Schweikhart,

2002; Manjunath, Metri, & Ramachandran, 2007; Meyer & Collier, 2001; Minkman

et al., 2007; van Matre & Koch, 2009). Also, health-care costs are skyrocketing around

the world, and not always with improved quality. Thus, health-care needs to be examined

through an operations lens to improve efficiency and effectiveness. Various methods and

tools (e.g. MBHCP, EFQM, Six Sigma, TQM, etc.) are being used by medical administra-

tors and researchers in an effort to find more effective approaches for solving these

problems in the health-care system (Chong et al., 2003; Goldstein & Schweikhart,

2002; Halpin & Shaw, 1999; Meyer & Collier, 2001; Moeller, 2001; Nabitz, Jansen,

van der Voet, & van den Brink, 2009).

Meyer and Collier (2001) and Goldstein and Schweikhart (2002) empirically tested

the Baldrige health-care model for QM and proved causal relationships among the

criteria constructs. The study showed that all relationships between the six criteria

categories were statistically significant and suggested that the Baldrige health-care

QM model would be a valuable framework for improving quality of care and

service and improving OP (Chong et al., 2003; Goldstein & Schweikhart, 2002;

Manjunath et al., 2007; Minkman et al., 2007). Goonan and Stoltz (2004) reported

that systematic quality improvements (QIs) are impacted by organisational efforts

based on the Baldrige health-care model. Saint Luke’s Hospital, which received the

MBNQA in 2003, has continued to use the Baldrige health-care model, which

showed that seven criteria categories play the role of CFSs for QI in the hospital

(DeJong, 2009).

The criteria of MBNQA have been designed and simplified to enable any organisation

of all types and sizes to apply for improving QM practices and OP. MBNQA has expanded

from the manufacturing sector to service and small business and now to nonprofit,

education, and the health-care industry. Also, the MBNQA criteria have been updated

to include emerging and relevant issues (Evans, 2010). One of the former chairs of

Baldrige Panel of Judges reported that the criteria of MBNQA represent ‘the leading

edge of validated management practice’ (Evans, 2010).

The MBHCP excellence model was introduced in 1995 as the MBNQA1995

health-care pilot programme. The generally recognised seven criteria of the MBHCP

excellence model are shown in Figure 3. The MBHCP criteria have been updated

annually based on the changing global environment for the quality of care and per-

formance. While keeping the original seven categories in MBHCP, sub-categories

and points have been re-designed to reflect current issues biennially. Therefore, the

award is one of the most prestigious awards for OP excellence in the world (Evans,

2010).

122 S.M. Lee et al.

2.2 Seven categories

MBHCP consist of seven categories: leadership; strategic planning; customer focus;

measurement, analysis, and knowledge management (MAKM); workforce focus;

process management; and OP results. These seven categories form a logical and effective

approach to organising the activities of any successful hospital or department. These

categories are congruent with the emphasis on full alignment and integration throughout

the organisation for QI (NIST, 2009).

Leadership ensures that the organisation has a definite vision, communicates direc-

tions, and makes continuous improvement towards that vision. The leadership examines

how senior leaders’ personal actions guide and sustain the organisation, how the organis-

ation fulfils legal and societal responsibilities, and how it supports key communities

(NIST, 2009).

Strategic planning is a key component for the alignment of strategic planning through-

out the organisation. The strategic planning category examines ‘how the organization

develops strategic objectives and action plans, how they are deployed and changed, and

how progress is measured’ (NIST, 2009).

Customer focus places an emphasis on systematically identifying customers,

determining what is important to them, and consistently applying a process improvement

model to enhance the things that are important to customers. The customer focus

examines ‘how the organization engages its patients and stakeholders for long-term

marketplace success, how the organization listens to the voice of its customers, and

how to use this information to improve and identify opportunities for innovation’

(NIST, 2009).

MAKM are related to how well information is used and shared throughout the organ-

isation. Organisations with well-defined systems that easily share best practices and

lessons learned are most successful. Health-care organisations are not always consistent

with this approach, and personal experiences and traditions often dictate how things are

done. The category of MAKM examines ‘how the organisation selects, gathers, analyzes,

manages, and improves its data, information, and knowledge assets, how it manages its

information technology, and how the organization reviews and uses it to improve its

performance’ (NIST, 2009).

Figure 3. MBHCP Excellence Model.Source: NIST (2009).


Workforce focus examines

how the organization engages, manages, and develops workforce to utilise its full potential inalignment with the organization’s overall mission, strategy, and action plans, and how theorganization’s ability to assess workforce capability and capacity needs and to build a work-force environment conducive to high performance. (NIST, 2009)

Process management refers to the manner in which continuous process improvement is

pursued. The category of process management examines

how the organization designs its work system, how it designs, manages, and improves its keyprocesses for implementing those work systems to deliver value to patients and stakeholdersand achieve organizational success and sustainability, and how the organization is ready foremergencies. (NIST, 2009)

Organizational performance results are contingent on the outcomes achieved from the

first six steps. The category of results examines ‘the organization’s performance and

improvement in all key areas (e.g. health-care outcomes, customer-focused outcomes,

financial and market outcomes, workforce-focused outcomes, process effectiveness out-

comes, and leadership outcomes), and performance levels of competitors and other

organizations with similar health-care service offerings’ (NIST, 2009).

2.3 MBHCP causal model and hypotheses

The NIST 1995 framework of MBNQA states that ‘leadership drives system which creates

result’. Meyer and Collier (2001) suggested that leadership impacts each of the com-

ponents. Unlike the NIST 1995 framework of MBNQA, which presented three basic

elements: leadership, system and results, and the 2002 model, which included organis-

ational profile and system, the MBNQA framework from 2003 to 2010 provides three

basic elements: the organisational profile, the system operations, and the system foun-

dation. Here, system operations include six categories and divided two triads: leadership

which ‘emphasizes the importance of a leadership focus on strategy and customers’ and

results that ‘focuses on workforce and key processes that accomplish the work of the

organisation that yields overall performance results’. The system foundation is composed

of MAKM. MAKM ‘serve as a foundation for the performance management system’

(NIST, 2009). This study used the NIST 2010 framework of MBHCP. Figure 4 shows

the proposed research model.

Figure 4. The proposed research model.

124 S.M. Lee et al.

Since the MBNQA criteria framework and categories including subcategories, have

changed, the proposed hypotheses are based on the 2002, and later MBNQA criteria fra-

meworks (NIST 2010 MBHCP, Badri et al. (2006), and Jayamaha et al. (2008)) and pre-

vious studies. Many previous studies used the MBNQA criteria framework prior to 2003;

Wilson and Collier (2000) and Meyer and Collier (2001) used the 1995 MBNQA criteria

framework, Lee et al. (2003) tested the 2001 model. Based on previous studies (Goldstein

& Schweikhart, 2002; Jayamaha et al., 2008; Lee et al., 2003; Meyer & Collier, 2001;

Winn & Cameron, 1998), the relationships among the seven categories of MBHCP can

be explained as follows. Leadership has an indirect effect on OP results through system

operations (defined as strategic planning, customer focus, workforce focus, and customer

focus) constructs. According to previous studies (Goldstein & Schweikhart, 2002; Meyer

& Collier, 2001; Shortell et al., 1995; Wilson & Collier, 2000) using the Baldrige criteria

in hospitals, leadership has positive relationships with strategic planning, customer focus,

and MAKM. Leadership develops value and useful strategies for patient focus and

supports employees for work efficiency. Leadership plays a role as an overall driver in

the organisation (Meyer & Collier, 2001). Therefore, leadership affects OP indirectly

via strategic planning, customer focus, and MAKM (H1–H3).

As shown in the 2010 framework, MAKM is ‘critical to a fact-based, knowledge-

driven system for improving performance and competitiveness’. MAKM is to drive

overall performance within an organisational system for effective use of measurement,

information, and data (Meyer & Collier, 2001). Each department in a hospital needs a

significant amount of useful information to make correct decisions and to provide

quality care service. Consequently, MAKM is an exception in this category of factors

in that it not only directly affects strategic planning, customer focus, workforce focus,

and process management, but it also has an indirect effect on OP results (H4–H7).

Since hospitals must face a variety of logistical uncertainties, leaders or managers must

consider the risks within individual departments as well as the organisation as a whole. If

hospitals try to reduce uncertainty through strategic planning, they must develop policies

that provide support to customers and employees. Thus, strategic planning affects the

customer focus, workforce focus, and process management (H8 and H10).

Hospitals determine the needs of patients to meet or exceed customer expectations by

provided services. Based on customer demands, hospitals build human resource and con-

sistently apply process improvements to enhance or phase out certain processes. There-

fore, customer focus affects the workforce focus and process management (H11 and H12).

If an employee is fully engaged and motivated, he/she will take pride in doing quality

work and strive to find ways to improve OP. As the health-care industry is a labor-

intensive industry, organisation leaders and managers should focus on maximising the

effectiveness of their human resource by providing effective work processes. Workforce

has been recognised as a critical factor which influences OP (Delaney & Huselid, 1996;

Bowen & Ostroff, 2004). Thus, workforce focus affects process management and OP

results (H13 and H14).

Effective and suitable processes in work stations are operated and managed by

employees for improving performance (e.g. improving service quality, customer/

employee satisfaction, OP). Based on the Baldrige seven categories, processes change

belongs to a process advisor or manager to achieve organisational goals and continually

improve processes. Therefore, efforts of successful process design or management will

improve performance. Thus, process management affects OP results (H15). Therefore,

the following hypotheses are proposed:


H1: Leadership has a positive effect on strategic planning.H2: Leadership has a positive effect on MAKM.H3: Leadership has a positive effect on customer focus.H4: MAKM has a positive effect on strategic planning.H5: MAKM has a positive effect on workforce focus.H6: MAKM has a positive effect on process management.H7: MAKM has a positive effect on customer focus.H8: Strategic planning has a positive effect on customer focus.H9: Strategic planning has a positive effect on workforce focus.H10: Strategic planning has a positive effect on process management.H11: Customer focus has a positive effect on workforce focus.H12: Customer focus has a positive effect on process management.H13: Workforce focus has a positive effect on process management.H14: Workforce focus has a positive effect on organisational performance results.H15: Process management has a positive effect on organisational performance results.

In this study, measurements of seven categories of MBHCP are adopted with modifi-

cation, based on the measurements suggested by Meyer and Collier (2001), Goldstein and

Schweikhart (2002), and NIST (2009).

3. Research methodology

3.1 Data collection

Data for this research were collected from 254 hospitals in South Korea. One survey of

international patients who visited Korea for medical tourism in 2008 showed that

48.4% cited ‘the quality of medical service and technology’ as the reason for choosing

Korea for their medical needs (Korea Tourism Organization, 2009). Korean hospitals

are chosen for data collection in this study for the following reasons.

1. Following the lead of advanced countries like the USA and UK, South Korea has

introduced a National Policy of Hospital Evaluation Programme (HEP). The evalu-

ation criteria of HEP are designed in three dimensions: ‘patient rights and conven-

ience’, ‘quality of medical procedures and performance’, and ‘structure of the care

in terms of human resources and facilities’.

2. South Korea has become the world leader in Information and Communication

Technologies (ICTs) (Lee, 2003). Based on the world-class ICT infrastructure, effi-

cient and high-quality health-care information systems have been developed and

used in most departments of hospitals (e.g. one-stop service). Korea offers

advanced high-tech medical services by combining advanced ICT and biotech,

and continues to make significant progress in the field.

3. Korea has two kinds of medical systems, western and oriental medical care.

Hospitals can choose either oriental or western medical care or a combined

western/oriental medical system.

The data collection method used in this study was the survey questionnaire. This

method was chosen in order to get the most accurate information possible, given the

time and distance constraints. Also, due to the characteristics of survey hospital par-

ameters, it was difficult to meet care team members during working hours for data

collection. Consequently, the survey questionnaire was sent to the selected Korean

hospitals by mail.

Respondents of the questionnaire included the director of quality, vice president of

quality, or quality manager in the QI department. If a hospital had no QI department,

the questionnaire was answered by a related QI worker. This study included Korean

126 S.M. Lee et al.

hospitals with more than 100 beds, to ensure that participating hospitals would have a

distinct QI department.

The survey used the double translation protocol. The questionnaire was first developed

in English and then translated into Korean by operations management faculty in South

Korea. The Korean version was translated back into English by American operations

management experts who are bilingual. The two English versions of the questionnaire

had no significant difference.

The goals of QI are to provide excellent quality care, increase patient satisfaction,

identify concurrent risk, decrease the infection rate, improve documentation, analyse

cost effect, and implement appropriate resource allocation in hospitals. An initial

questionnaire was tested in a pilot survey involving 35 participating hospitals in South

Korea. Participation in this survey was totally voluntary. In the pilot survey, three of

six measurement items of OP results – outcomes of process effectiveness, financial and

market, and leadership – were eliminated as suggested by managers of the QI department

because those constructs are difficult to measure precisely through the questionnaire. Also,

some questionnaire items were dropped from the original version to improve reliability in

constructs.

There are more than 2300 hospitals in South Korea as of April 2009. As hospitals are

complex organisations, the Baldrige criteria must account for a broad range of issues

(Goldstein & Schweikhart, 2002). Thus, this study randomly selected hospitals with

more than 100 beds because ‘small hospitals often do not share the complexity issues

of large hospitals and may not have developed extensive quality management systems’

(Goldstein & Schweikhart, 2002). Tan (2002) proposed that directors or managers were

more objective and knowledgeable with respect to their organisations’ operations. Respon-

dents for this study should be able to answer related Baldrige criteria questions, especially

about OP. Thus, following Tan’s suggestion, a manager of a quality-related department in

each hospital was chosen as the subject to minimise respondent variance (Lee et al., 2011;

Tan, 2002).

Questionnaires were sent to the director of quality, vice president of quality, or quality

manager at 750 randomly selected hospitals with more than 100 beds. The survey ques-

tionnaires from 254 hospitals (33.9%) were collected. The low response rate is probably

because respondents are in charge of quality-related tasks or organisation performance

in each hospital. Managers of small-sized hospitals tend to serve dual jobs, for example,

in both the nursing and QI teams. Accordingly, they have heavy workloads, which

might cause them not to respond to the survey. We found no reason to expect that those

who did respond were not representative of the overall population. Goldstein and Schwei-

khart (2002) used 220 US hospitals as a sample to examine the relationship among seven

categories as 19 dimensions of MBHCP. Consequently, 254 respondents (one from each

hospital) from whom we collected data are considered adequate to analyse and test our

research model.

The participating hospitals’ characteristics and respondents’ demographic information

are summarised in Table 1. The types of hospitals in the sample are teaching (5.5%), foun-

dation (35.8%), public (20.9%), and private (37.8%). The classifications of hospital are

general (60.2%), secondary (27.6%), and tertiary (12.2%). The number of beds ranged

from more than 100 to more than 1000.

The respondents’ positions in the QI department are managers (46.5%) and directors

(53.5%). Although the questionnaires were sent to the director of quality, vice president

of quality, or quality manager, the questionnaires were returned from the QI department

(46.5%), nursing (29.5%), administration (23.2%), and medical team (.8%). The reason


seems that small-sized hospitals with more than 100 but less than 200 beds do not have a

designated department responsible for QM.

3.2 Model variables, reliability, and validity

The questionnaire utilised a five-point Likert scale to measure the main constructs. Scales

to measure each of the constructs were developed based on prior studies as much as

possible. Some measures were modified to adapt to this research. Table 3 shows mean

values and standard deviations of each of the study variables.

Reliability represents the variance of measurement values resulting from a repeat

measurement of the same concept. It is related to non-systematic error that can be

expressed as stability, consistency, predictability, and accuracy. Reliability was tested

based upon Cronbach’s alpha values, all of the coefficients of reliability measures for

the constructs exceeded the threshold value of 0.70 for exploratory constructs in basic

research (Nunnally, 1978). The Cronbach’s alpha value for customer focus was the

highest (0.868), and OP results the lowest (0.715). All the Cronbach’s alpha values for

the seven latent variables were significant at p , 0.05.

Validity refers to the accuracy of a measure. The purpose of principal component

analysis (PCA) is to identify the most meaningful basis and to express similarities and

differences on the data. Also, confirmatory factor analysis (CFA) is a way of testing

how well measured variables represent the constructs. This model consists of seven

Table 1. Hospital characteristics and respondents’ demographics.

Hospitals’ characteristics Frequency Percent

Hospital typeTeaching 14 5.5Foundation 91 35.8Public 53 20.9Private 96 37.8

Classification of hospitalTertiary (3 degree) 31 12.2Secondary (2 degree) 70 27.6General hospital 153 60.2

Number of bedsMore than 1000 6 2.3501–1000 53 20.9201–500 81 31.9100–200 114 44.9

Respondents’ demographics Frequency PercentGender

Male 106 41.7Female 148 58.3

DepartmentQI 118 46.5Nursing 75 29.5Administration 59 23.2Medical team 2 0.8

PositionManager 118 46.5Director 136 53.5

Total respondents ¼ 254

128 S.M. Lee et al.

major components: leadership, strategic planning, customer focus, MAKM, workforce

focus, process management, and OP results.

The percentages of variance explained were 60 or higher for each of the constructs on

statistics of PCA as shown in Table 2. Statistics of CFA are given in Table 3. The standar-

dised factor loadings and t values for measurement variables on SEM analysis using the

AMOS program are presented in Table 3. All variables proposed in the study were statisti-

cally significant at the 0.05 level.

The Just-identified (or calling saturated) model, which has an equal number of knowns

and unknowns, connects every exogenous variable to every possible endogenous variable

and should have the GFI value of 1 and x2 value of zero (Brown, 2006). The test of ade-

quacy for measurement model is meaningless here because the model has zero degree of

freedom and GFI value of 1. As shown in Table 3, there are three Just-identified models:

MAKM, workforce focus, and OP results.

4. Results

This section presents the results of hypotheses testing, including the standardised coeffi-

cient of each path in the research model. The results of goodness of fit test for the

model, summarised in Table 4, showed the value of chi-square (x2) of 608.2, degrees of

freedom 260 x2/df 2.34, GFI 0.893, CFI 0.908, and the p-value of 0.000. Compared

with the recommended values for the goodness of fit tests, in this model the values of

CFI (0.908), RMR (0.049), RMSEA (0.073), x2 (608.2), and the p-value (0.000) were

satisfactory, but GFI (0.893) was not.

SEM was used to test the hypotheses. AMOS 5.0 was chosen for this study by virtue of

its powerful graphic representations and easy-to-use interfaces. The results of significance

tests for paths of the model are shown in Table 5 and Figure 5. The lines in Figure 5 indi-

cate only the significant paths among the latent variables.

For the H1 test, the standardised path coefficient between leadership and strategic

planning was 0.334 and statistically significant at the 0.05 level. Thus, H1 was supported.

When an organisation wants to encourage and lead its employees, it should place priority on

strategic planning by a senior leader. For the H2 test, the standardised path coefficients

between leadership and the MAKM focus was 0.512 and statistically significant at the

0.05 level. H2 was supported. For the H3 test, the standardised path coefficients between

leadership and the customer focus was 0.246 and statistically significant at the 0.05 level.

H3 was also supported. Leadership affects customer focus to provide quality care to patients

and potential customers. It means that leadership for patients and potential customers

affects employees’ motivation to improve quality of care and service through employee

activities. Therefore, H1, H2 and H3 tests show similar results to those of previous

studies (Goldstein & Schweikhart, 2002; Jayamaha et al., 2008; Lee et al., 2003; Meyer

& Collier, 2001) conforming that top management support creates QM (Juran, 1993).

For the H4, H5, and H7 tests, the standardised path coefficients between MAKM and

strategic planning, workforce focus, and customer focus were 0.446, 0.204, and 0.460, all

statistically significant at the 0.05 level. Thus H4, H5, and H7 were supported. However,

the standardised path coefficient between MAKM and process management (H6) was

0.017 and statistically not significant. H6 was not supported. While the collected data

and information are used and shared throughout the organisation, medical staff might

not consistently use them, since patients have different symptoms for similar diseases.

Although the process management that provides actual organisational support to employ-

ees for improving their work is important in the work place, especially within the medical


Table 2. Mean and PCA on measurement items.

ConstructsVariable (Likert type five-point Scale,

1 ¼ Very bad; 5 ¼ Very good) M SD

Percent ofvariance

explained

Leadership Organisational vision and values (L1) 3.83 0.947Create and promote a culture of patient safety

(L2)3.78 0.965

Create an environment for innovation,strategic objectives (L3)

3.90 0.931 66.47

Public responsibility and citizenship (L4) 3.72 0.875Strategic

planningDevelops strategic processes for quality of

health-care services (S1)3.61 0.908

Analysis of patients’ needs and competitionin developing (S2)

3.85 0.846

Strategies/plans are clearly communicated toall employees (S3)

3.53 0.878 65.87

Develops strategic deployment for humanrecourse to efficiency (S4)

3.64 0.873

Customer focus Innovate health-care service offerings to meetthe requirements and exceed (P1)

3.94 0.909

Opportunities for expanding relationshipswith existing patients (P2)

3.97 0.833

Listens to patients’ voices for feedback (P3) 3.92 0.892 71.73Efforts to improve the satisfaction of patients

(P4)4.00 0.812

MAKM Performance measurement: select, collect,and integrate data and information (MK1)

3.77 0.918

Use these data and information to improveperformance (MK2)

3.60 0.887 78.27

Accuracy, integrity and reliability, security,and user friendly of IT (MK3)

3.79 0.834

Workforcefocus

Create workforce engagement (W1) 3.83 0.848

Open communication (W2) 3.49 0.936 73.74Compensation, reward, recognition, and

incentive (W3)3.83 0.887

Processmanagement

Developed and innovated the overall worksystem (PM1)

4.24 0.586

Creates and innovates work processes to meetrequirement (PM2)

3.91 0.829

Design prevents rework and errors (PM3) 4.07 0.819 70.63Care/service design processes are well-

integrated to ensure efficiency (PM4)3.80 0.750

OP ResultsHealth-care (HC)

Patient length of stay for care in hospital(HC1)

3.84 0.867

Recover functional status of patients aftertreatments (HC2)

3.96 0.825

Patient compliance with standard carepatterns (HC3)

3.87 0.904

The contribution to community healthprogrammes (HC4)

3.56 0.882

Mean of items 3.81 0.870Customer-focused (CF)

(Continued)

130 S.M. Lee et al.

industry, H6 was not supported in this study. Therefore, hospitals with well-defined

systems that promote sharing the best practices and lessons learned are the most successful

by correction and reviewing. This study has results similar to those of previous studies

(Jayamaha et al., 2008; Lee et al., 2003; Meyer & Collier, 2001).

For the H8 and H10 tests, the standardised path coefficients between strategic planning

and the customer focus and process management were 0.200 and 0.264 and statistically

significant at the 0.05 level. H8 and H10 were supported. This study has a result similar

to that of previous studies (Goldstein & Schweikhart, 2002; Jayamaha et al., 2008; Lee

et al., 2003). However, the standardised path coefficient between strategic planning and

workforce focus (H9) was 0.037 and statistically not significant. H9 was not supported

as reported by previous studies that strategic planning does not have positive relationships

among the Baldrige categories (Calem & Rizzo, 1995; Lee et al., 2003; Meyer & Collier,

2001). However, Goldstein (2003) showed the importance of employee development

through the strategy planning/design to manage service encounters in hospitals.

For H11and H12, the standardised path coefficients between customer focus and work

force focus and process management were 0.726 and 0.511 and statistically significant at

the 0.05 level. H11 and H12 were supported. The study has a similar result to those of pre-

vious studies (Goldstein & Schweikhart, 2002; Jayamaha et al., 2008; Lee et al., 2003). As

customer focus emphasises a systematic approach to customers and consistent processes to

enhance customer expectation, organisations have to manage workforce capability and

capacity needs for a better workforce environment.

For the H13 and H14 tests, the standardised path coefficients between workforce focus

and process management and OP results were 0.546 and 0.993 and statistically significant.

H13 and H14 were supported. Meyer and Collier (2001) concluded that human resources

management is related to customer satisfaction in the health-care system. That would

mean that workforce focus plays a key role in the health-care environment to improve

customer satisfaction and OP.

For the H15 test, the standardised path coefficient between process management and

OP results was 0.113, statistically significant at the 0.05 level. H15 was supported. The

Table 2. Continued.

ConstructsVariable (Likert type five-point Scale,

1 ¼ Very bad; 5 ¼ Very good) M SD

Percent ofvariance

explained

Overall patient satisfaction (PF1) 3.57 0.884Over all patient engagement (PF2) 3.45 0.905Number of patients who return for future

visits (PF3)3.24 0.871 72.81

Relationship between patient and theorganisation (PF4)

3.87 0.862

Mean of items 3.53 0.880Work-focused (WF)

Workforce satisfaction (WF1) 3.24 0.879Workforce engagement (WF2) 3.14 0.954Environment of workforce safety, security,

and service (WF3)3.87 0.754

Appropriated environment of the workplace(WF4)

3.56 0.733

Mean of items 3.45 0.830


Table 3. Results of reliability and confirmatory factor analysis.

Constructs Model goodness-of-fit statistics VariablesStandardised

loading t-value p-value Cronbach’s alpha

x2 2.75x2/Degree of freedom (df) 1.37 L1 0.835 –

Leadership Comparative fit index (CFI) 0.989 L2 0.831 14.327 0.000Goodness-of-Fit Index (GFI) 0.978 L3 0.763 13.044 0.000 0.830Root Mean Square Error of Approximation (RMSEA) 0.000 L4 0.567 9.104 0.000Root Mean Square Residual (RMR) 0.003

MK1 0.860 –MAKM GFI 1.00 MK2 0.783 14.136 0.000 0.860

MK3 0.820 14.996 0.000Strategic planning x2 3.54

x2/df 1.77 S1 0.798 –CFI 0.996 S2 0.776 12.315 0.000GFI 0.993 S3 0.739 11.711 0.000 0.827RMSEA 0.055 S4 0.636 9.941 0.000RMR 0.013

Customer Focus x2 2.05x2/df 1.03 P1 0.807 12.718 0.000CFI 1.00 P2 0.777 12.219 0.000 0.868GFI 0.996 P3 0.822 12.959 0.000RMSEA 0.010 P4 0.738 –RMR 0.008

W1 0.709 –Workforce focus GFI 1.00 W2 0.723 10.985 0.000 0.821

W3 0.790 11.985 0.000x2 5.75x2/df 2.87 PM1 0.777 10.998 0.000

Process management CFI 0.992 PM2 0.739 10.528 0.000 0.854GFI 0.989 PM3 0.935 12.155RMSEA 0.086 PM4 0.672 – 0.000RMR 0.009

HC 0.703 12.476OP Results GFI 1.00 CF 0.829 – 0.000 0.808

WF 0.789 14.669 0.000

13

2S

.M.

Lee

etal.

Table 4. Results of goodness-of-fit test.

Model x2 x2/df p CFI GFI RMR RMSEA

Model 608.2 2.34 0.000 0.908 0.893 0.049 0.073Recommended value ≤3.0 ≥0.9 ≥0.9 ≤0.05 ≤0.08

Table 5. Results of significance test for paths of the model.

PathPath

coefficient SEt-

value p-value

Leadership � strategic planning (H1) 0.334 0.069 4.423 0.000∗∗∗

Leadership � MAKM (H2) 0.512 0.064 7.246 0.000∗∗∗

Leadership � customer focus (H3) 0.246 0.054 3.479 0.000∗∗∗

MAKM � strategic planning (H4) 0.446 0.078 5.773 0.000∗∗∗

MAKM � workforce focus (H5) 0.204 0.060 2.824 0.005∗∗

MAKM � process management (H6) 0.017 0.088 0.136 0.682MAKM � customer focus (H7) 0.460 0.068 5.669 0.000∗∗∗

Strategic planning � customer focus (H8) 0.200 0.068 2.447 0.014∗

Strategic planning � workforce focus (H9) 0.037 0.052 0.587 0.557Strategic planning � process management

(H10)0.264 0.074 2.498 0.013∗

Customer focus � workforce focus (H11) 0.726 0.094 7.702 0.000∗∗∗

Customer focus � process management(H12)

0.511 0.203 2.120 0.034∗

Workforce focus � process management(H13)

0.546 0.219 2.089 0.037∗

Workforce focus � OP results (H14) 0.993 0.100 12.462 0.000∗∗∗

Processmanagement

� OP results (H15) 0.113 0.068 2.482 0.013∗

∗p , 0.05.∗∗p , 0.01.∗∗∗p , 0.001.

Figure 5. Significant path coefficients in the model. ∗p , 0.05, ∗∗p , 0.01, ∗∗∗p , 0.001.


study has a result similar to those of previous studies (Goldstein & Schweikhart, 2002;

Jayamaha et al., 2008; Lee et al., 2003; Meyer & Collier, 2001). As process management

enables work systems to deliver value to customers, processes management can improve

the goals of meeting customer requirements and OP.

5. Conclusion and limitation

This study proposed a research model to describe the relationships among the seven cat-

egories of MBHCP. This model with fifteen hypotheses was tested using data collected

from QI and related departments in 254 hospitals in South Korea.

One of the findings of the study is that OP results are associated with workforce focus

(0.993) and process management (0.113). These results indicate that the effectiveness of

medical and non-medical work processes are important to patient satisfaction (Meyer &

Collier, 2001; Lee et al., 2012). This seems to be reasonable in that all of the efforts to

improve quality of care and service are related to employees. The ‘service-profit chain’

was used to explain the interaction between employees and customers. Since employees

are the direct contact point with customers, they directly affect quality of service. Internal

quality is thus the way to improve quality of the work environment, which in turn impacts

on employee satisfaction (Heskett, Sasser, & Schlesinger, 2003; Heskett, Thomas,

Loveman, Sasser, & Schlesinger, 1994). Internal quality is explained by perceptions

such as feelings of employees leading to improved work by their organisation and thus

to employee attitudes and behaviour which lead to employee satisfaction (Heskett

et al., 1994, 2003). Thus, it is critical for health-care organisations to improve their

employees’ satisfaction by providing sufficient support for their work through communi-

cation, engagement, and compensation. Also, hospitals should develop and undertake

innovations on their existing work systems and processes to improve employees’ task

efficiency.

Leadership and MAKM are important at the first and later stages for delivering quality

of care and safety, which in turn enhance patient satisfaction. Leadership can create and

promote a culture of patient safety and innovation in the competitive environment.

Medical tourism is one of the fastest growing areas of health-care. Many customers

seek safer and more comfortable environments with high quality care, a variety of

medical procedures, excellent facilities, and unique destinations (Ellin, 2009). Improve-

ment of the global-class health-care environment is furthered through international stan-

dard criteria (e.g. MBHCP, EFQM, JCA, and ISO 9000 series, etc.) in the prevention

and treatments of diseases.

MAKM play a role as a CFS for QI in hospitals through the collected data and

information to improve performance for prevention and correction of errors, and

support strategy. Satisfied patients positively impact OP through higher quality of care

and service, based on their perceived expectations. Therefore, health-care organisations

need to continuously develop and undertake innovations on work processes using

MAKM for patient and workforce satisfaction.

The study did not show a statistically significant relationship between MAKM and

process management (H6), and strategic planning and workforce focus (H9). The

reason for this result could be that some hospitals do not have sufficient workforce strength

to develop strategic planning to improve QM. Thus, hospitals should develop effective

management policies in order to fully utilise insufficient human recourses, especially in

small-sized hospitals. Also, proper process management should be developed to support

employees in improving their work, which in turn affects their sense of engagement.

134 S.M. Lee et al.

As this study provides empirical support for the Baldrige National Quality framework

in hospitals, these results could provide hospital leaders and/or managers with new insights

for quality excellence and OP. Since quality plays an important role in enhancing patient

satisfaction, leaders or managers need to support their employees based on seven cat-

egories of MBHCP in an effort to improve quality of care service. In addition, the

number of organisations that apply for MBNQA or JCI has increased dramatically over

the past decades. It shows that the health-care market is becoming more global rather

than national. Thus, countries that are willing to compete in the global health-care

market or explore medical tourism should consider the necessary international standard

criteria (e.g. JCI, MBHCP, or EFQM) and their relationships.

There are some limitations of the study. First, this study used only three of the original

seven items of OP results to collect data as the remaining four items were excluded after

the pilot study. Second, the data used in this study were collected from hospitals in South

Korea. Third, this study did not compare OP results before and after the intervention of

implementing the standard criteria. Finally, this study did not consider whether or not

selected hospitals actually apply international standard criteria for care and treatment ser-

vices. Thus, the generalizability of this study’s results is limited. Additionally, structural

equation models assume one-way causality, when the reality may be more complex.

Future research should consider our limitations mentioned above: pre- and post-appli-

cation of international standard criteria, cross-cultural analysis, and longitudinal studies of

OP results based on QM. The investigation of the role of each category of MBHCP

between different-sized hospitals (e.g. small and medium versus large) can be considered

for future research. Also, we should further explore for the most appropriate method for

quality medical care through a comparative study of international standard criteria and/

or awards. This study presents interesting findings in the health-care industry, but QM

practices for OP excellence in a country might be different from other countries due to cul-

tural differences (Evans, 2010; He et al., 2011). Thus, cross-cultural study can be a good

candidate for future research. This study adopted a mail survey method to collect data from

a manager in each hospital. Since the collected data for the study had a low response rate,

an interview might be a more appropriate tool in view of the respondents’ heavy work-

loads, to increase the response rate and reduce potential bias.

References

Badri, M., Selim, H., Alshare, K., Grandon, E., Younis, H., & Abdulla, M. (2006). The Baldrige edu-cation criteria for performance excellence framework: Empirical test and validation.International Journal of Quality & Reliability Management, 23(9), 1118–1157.

Bou-Llusar, J., Escrig-Tena, A., Roca-Puig, V., & Beltran-Martın, I. (2009). An empirical assess-ment of the EFQM excellence model: Evaluation as a TQM framework relative to theMBNQA model. Journal of Operations Management, 27(1), 1–22.

Bowen, D., & Ostroff, C. (2004). Understanding HRM-firm performance linkages: The role of the‘strength’ of the HRM system. Academy of Management Review, 29(2), 203–221.

Brown, T.A. (2006). Confirmatory factor analysis for applied research. New York: The GuilfordPress.

Calem, P., & Rizzo, J. (1995). Competition and specialization in the hospital industry. SouthernEconomic Journal, 61(4), 1182–1198.

Chong, P., Calingo, L., Reynolds, G., & Fisher, D. (2003). Using an innovative approach to shortencoaching and assessment time when applying the Baldrige health care criteria for performanceexcellence in a substance abuse treatment setting. Total Quality Management & BusinessExcellence, 14(10), 947–955.

DeJong, D.J. (2009). Quality improvement using the Baldrige criteria for organizational perform-ance excellence. American Journal of Health-System Pharmacy, 66(1), 1031–1034.


Delaney, J., & Huselid, M. (1996). The impact of human resource management practices on percep-tions of organizational performance. Academy of Management Journal, 39(4), 949–969.

Ellin, A. (2009). Health care goes global, pp. 112–118. Retrieved from http://deltaskymag.delta.com/

Evans, J. (2010). Organisational learning for performance excellence: A study of Branch-Smithprinting division. Total Quality Management & Business Excellence, 21(3), 225–243.

Fundin, A., & Bergman, B. (2003). Exploring the customer feedback process. Measuring BusinessExcellence, 7(2), 55–65.

Garengo, P. (2009). A performance measurement system for SMEs taking part in quality award pro-grammes. Total Quality Management & Business Excellence, 20(1), 91–105.

Goldstein, S. (2003). Employee development: An examination of service strategy in a high-contactservice environment. Production and Operations Management, 12(2), 186–203.

Goldstein, S., & Schweikhart, S. (2002). Empirical support for the Baldrige award framework in U.S.hospitals. Health Care Management Review, 27(1), 62–75.

Goonan, K., & Stoltz, P. (2004). Leadership and management principles for outcomes-orientedorganizations. Medical Care, 42(3), 31–38.

Halpin, M., & Shaw, C. (1999). Special report: European societies for quality in health care.International Journal of Quality in Health Care, 11(3), 263–265.

He, Z., Hill, J., Wang, P., & Yue, G. (2011). Validation of the theoretical model underlying theBaldrige criteria: Evidence from China. Total Quality Management & Business Excellence,22(2), 243–263.

Herzlinger, R. (2006). Innovating in health care-framework. Harvard Business Review, 9-306-342,pp. 1–54.

Heskett, J., Sasser, W., & Schlesinger, L. (2003). The value profit chain: Treat employees like cus-tomers and customers like employees. New York: The Free Press.

Heskett, J., Thomas, O., Loveman, G., Sasser, W., & Schlesinger, L. (1994). Putting the service-profit chain to work. Harvard Business Review, 72(2), 164–174.

Jayamaha, N., Grigg, N., & Mann, R. (2008). Empirical validity of Baldrige criteria: New Zealandevidence. International Journal of Quality & Reliability Management, 25(5), 477–493.

Juran, J. (1993). Why quality initiatives fail. Journal of Business Strategy, 14(4), 35–38.Korea Tourism Organization. 2009. Retrieved from http://english.visitkorea.or.kr/enu/index.ktoLee, S. (2003). Korea: From the land of morning calm to it hot bed. Academy of Management

Executive, 17(2), 7–18.Lee, S., Lee, D., & Kang, C. (2012). The impact of high-performance work systems in the health-

care industry: Employee reactions, service quality, customer satisfaction, and customerloyalty. The Service Industries Journal, 32(1), 17–36.

Lee, S., Lee, D., & Schniederjans, M. (2011). Supply chain innovation and organizational perform-ance in the healthcare industry. International Journal of Operations & ProductionManagement, 31(1), 1193–1214.

Lee, S.M., Rho, B., & Lee, S.K. (2003). Impact of Malcolm Baldrige National Quality Award criteriaon organizational quality performance. International Journal of Production Research, 41(9),2003–2020.

Manjunath, U., Metri, B., & Ramachandran, S. (2007). Quality management in a health care organ-isation: A case of South Indian hospital. Total Quality Management & Business Excellence,19(2), 129–139.

van Matre, J., & Koch, K. (2009). Understanding health care clinical process and outcome measuresand their use in the Baldrige Award application process. Quality Management Journal, 16(1),18–28.

Meyer, S., & Collier, D. (2001). An empirical test of the causal relationships in the Baldrige healthcare pilot criteria. Journal of Operations Management, 19(4), 403–425.

Minkman, M., Ahaus, K., & Huijsman, R. (2007). Performance improvement based on integratedquality management models: What evidence do we have? A systematic literature review.International Journal for Quality in Health Care, 19(2), 90–104.

Moeller, J. (2001). The EFQM excellence model: German experiences with the EFQM approach inhealth care. International Journal for Quality in Health Care, 13(1), 45–49.

Nabitz, U., Jansen, P., van der Voet, S., & van den Brink, W. (2009). Psychosocial work conditionsand work stress in an innovating addiction treatment centre: Consequences for the EFQMexcellence model. Total Quality Management & Business Excellence, 20(3), 267–281.

136 S.M. Lee et al.

http://deltaskymag.delta.com/

http://deltaskymag.delta.com/

http://english.visitkorea.or.kr/enu/index.kto

National Institute of Standards and Technology (NIST). (2008–2012). NIST. Retrieved from http://www.nist.gov/public_affairs/factsheet/nqa_appdata.cfm

Nunnally, J. (1978). Psychometric theory (2nd ed.). New York: McGraw Hill.Sanguesa, M., Mateo, R., & Ilzarbe, L. (2007). How hospitals choose a quality management system:

Relevant criteria in large Spanish hospital. Total Quality Management & Business Excellence,18(6), 613–630.

Shortell, S.M., O’Brien, J.L., Carman, J.M., Foster, R.W., Hughes, E.F., Boerstler, H., & O’Conn,E.J. (1995). Assessing the impact of continuous quality improvement/total quality manage-ment: Concept versus implementation. Health Services Research, 30(2), 277–401.

Stankard, M., & Snell, T. (2007). Designing a Baldrige-based service to improve business health.Total Quality Management & Business Excellence, 18(9), 1015–1022.

Tan, K. (2002). Supply chain management: Practices, concerns, and performance issues. Journal ofSupply Chain Management, 38(1), 42–53.

Wilson, D., & Collier, D. (2000). An empirical investigation of the Malcolm Baldrige national awardcausal model. Decision Sciences, 31(2), 361–390.

Winn, B., & Cameron, K. (1998). Organizational quality: An examination of the Malcolm Baldrigenational quality framework. Research in Higher Education, 21(8), 897–914.


http://www.nist.gov/public_affairs/factsheet/nqa_appdata.cfm

http://www.nist.gov/public_affairs/factsheet/nqa_appdata.cfm

health-care quality management using the mbhcp excellence model

Documents