TOTAL QUALITY MANAGEMENT, VOL. 11, NO. 8, 2000, 1123± 1133
Quality management and business
performance in hospitals: A search for
success parameters
Paul Kunst1 & Jos Lemmink2
1
Maastricht Economic Research Institute on Innovation and Technology (MERIT), Maastricht
University, PO Box 616, 6200 MD Maastricht, The Netherlands & 2Faculty of Economics and
Business Administration, Maastricht University, The Netherlands
abstract This paper is based on the results of a European study aimed at identifying and exploring
success parameters of high (quality) performance and their possible interrelationships. The study was
conducted in three service sectors (the hospital, road freight transport and banking sectors) in three
European countries (Spain, UK and the Netherlands) early in 1995. In this paper we shall
concentrate on the hospital sector. Based on the hospital data, we examined if criteria other than
those used in the European Quality Assurance (EQA) model are more accurate in identifying quality
progress and business performance of hospitals. Our research shows that diVerent explanatory
variables are linked to progress in total quality management (TQM) and business performance.
Moreover, the sector involved in the study plays an important role. Our ® rst conclusion suggests that
the general application of the EQA model as an evaluation instrument is subject to debate. A second
conclusion is that there is a positive link between progress in TQM and perceived service quality by
customers. TQM improves perceived service quality. Progress in TQM and perceived service quality
by customers are positively, but only to a limited degree, linked to business performance. However,
this may be due to the general level of quality management in the sector studied. In general, we
conclude that progress in TQM leads to higher business performance of the hospital, indicating the
eYciency/cost eVect, and to a higher perceived service quality by patients, indicating the eVectiveness.
Quality awards
The rationale behind this study is to enhance our understanding of the relationship between
quality management, performance and customer satisfaction using the framework of the
European Quality Award (EQA), as well as a service quality model focusing on quality
perceived by customers. Quality award schemes are widely used as means for organizations’
self-assessment. They have been increasingly promoted by governments and a number of
private organizations with the intention of stimulating and motivating good quality management practice in their countries. Examples of prestigious quality awards are the Deming Prize
( Japan), the Malcolm Baldrige National Quality Award (USA) and the European Quality
Correspondence: P. Kunst, Maastricht Economic Research Institute on Innovation and Technology (MERIT),
Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands. Tel: + 31 43 3883881; Fax:
+ 31 43 3884905; E-mail: p.kunst@merit.unimaas.nl
ISSN 0954-4127 print/ISSN 1360-0613 online/00/081123-11
€ 2000 Taylor & Francis Ltd
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P. KUNST & J. LEMMINK
Figure 1. European Quality Award Model.
Award (EFQM, 1992). Quality awards have also been established at the national and regional
levels (Hardjono & Hes, 1993). Awards have in common that they provide a basic framework
for analysing diþ erent factors, such as processes, leadership, personnel management and
business results, which play a role in the functioning of organizations. The criteria cover a
wide range of subjects that are all relevant to quality performance in organizations (Dessler
& Farrow, 1990). Awards are indeed strongly based on the foundations of total quality
management (TQM) (Bemowski & Sullivan, 1992; Stauss, 1994). Although quality awards
were initially developed for pro® t organizations, the award models can also be applied, with
minor adjustments, to not-for-pro® t sectors.
The EQA model distinguishes nine criteria (see Fig. 1). These are:
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
leadership;
policy and strategy;
personnel management;
resource management;
process management;
employee satisfaction;
customer satisfaction;
eþ ect on society;
organizational results.
In the model the criteria are divided in two groups: enablers and results. The results aspect of
the awards are concerned with what the organization has achieved, while the enablers are
concerned with how the results are being achieved. Customer satisfaction, personnel satisfaction, impact on society and business results are achieved through leadership, driving policy
and strategy, personnel management, and the management of resources and processes. The
idea behind the nine categories is that a high quality standard will be attained if attention is
paid to these categories in a consistent manner.
This paper is related to one speci® c sector. Before we formulate the research questions,
we consider it useful to give a short overview of recent quality management developments in
hospitals.
Quality management in hospitals
Quality management has become an important issue in hospitals since the 1980s (Kunst
et al., 1996). This is valid for each of the three countries in this study. The increasing
QUALITY MANAGEMENT IN HOSPITALS
1125
attention to quality is due to government in¯ uence, in¯ uence of customers and other
stakeholders, and hospital management initiatives.
In recent years, the role of governments as the main provider of health-care services has
changed. Initially, governments mainly provided funding, but now they increasingly focus on
issues of organization, management and quality in hospitals. Governments have developed
various initiatives to promote and improve quality management.
Additionally, the health-care market itself is changing from a seller-oriented to a buyeroriented market due to the increasing in¯ uence of consumer organizations, insurance
companies and public pressure. As a consequence, the patient is becoming a customer.
Apart from governmental in¯ uences and the changing attitude of stakeholders, another
in¯ uential factor is related to hospital management. Several trends can be distinguished in
management thinking concerning quality. Traditionally, much interest was paid by hospital
management to professional quality, including peer review, which is inherently monodisciplinary, certi® cation of professional training programmes and education, mapping of
care processes, development of new quality standards and guidelines. As a result of smaller
budgets and increased professional standards of management, organizational or managerial
quality has received increased attention since the 1980s. Processes other than primary healthcare processes, such as the `hotel function’ of hospitals, are reconsidered. In addition,
technological developments, raising technological as well as quality standards, have had an
important impact on medical care, surgical techniques, drugs, equipment and the organization
and delivery of health care. Finally, assessing and satisfying the needs of the population in a
buyers market, caused by the previously mentioned changed health-care market, has become
prevalent. Managers of hospitals start to think in terms of care systems, with an increasingly
important role for customers or patients. Hayes (1994) concludes that eþ ort must be devoted
to skills necessary for determining customer wishes and needs in the context of TQM.
Research questions
Our research questions are supposed to contribute to our understanding of the relationship
between quality management, customer satisfaction and performance. Related to this speci® c
context, and to the speci® c models we used, we formulated ® ve research questions. The
research questions concerning success parameters and customer-perceived quality are as
follows:
(1a)
(1b)
(1c)
(2a)
What are the success parameters of quality management in hospitals?
How well do these success parameters indicate achievements in quality management?
How well do these success parameters indicate business performance?
What is the relationship between quality management and customer perceived
quality?
(2b) What is the relationship between customer-perceived quality and business
performance?
Research method
Two diþ erent methods were used to gather data on quality management in hospitals: a
written survey and in-depth interviews with quality managers. The latter were carried out to
validate the questionnaire and to gain more in-depth insights in quality practices of hospitals.
The questionnaire was set up in accordance with the EQA criteria in order to be able to
compute quality scores for hospitals. For each criterion several questions were selected to
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P. KUNST & J. LEMMINK
obtain a valid representation of each individual criterion. A total of 36 items was used to
measure all of the criteria. With respect to patients’ perceptions of service quality, opinions
of hospital managers were used. Schneider et al. (1980) conclude that perceptions of managers
can be a reliable proxy of the actual perceived service quality of customers. We agree with
Schneider et al. as to broad categories of services characteristics as they have been used in
this study. For a more detailed analysis of processes, customers are indispensable, and
management is frequently unaware of real problems. However, since we measure broad
categories, we feel we can use the perceptions of managers. We measured these perceptions
using ® ve items related to the ® ve dimensions of the SERVQUAL measurement instrument:
tangibles, reliability, responsiveness, assurance and empathy (Parasuraman et al., 1988).
Table 1 gives an overview of the criteria used in the model and the operationalization of the
criteria.
Response
For our empirical research we selected hospitals (general and university hospitals) in Spain,
the UK and the Netherlands. Questionnaires were sent to a total of 850 hospitals. The
response rate was 27% (227). The response rates were 45% (56) in the Netherlands, 11%
(46) in Spain and 39% (125) in the UK, respectively. The sample of hospitals in the UK
re¯ ects their special situation, that is, they are divided into National Health Service (NHS)
hospitals and private hospitals, corresponding to the two existing health-care systems in the
UK. In the UK questionnaires were sent to a sample of 204 NHS hospitals and 119 private
hospitals. Response rates were 40% for NHS hospitals and 36% for private hospitals,
respectively. Respondents were mainly general managers (in smaller hospitals) and quality
managers (in larger hospitals).
Empirical results
The ® rst three research questions were:
(1a) What are the success parameters of quality management in hospitals?
(1b) How well do these success parameters indicate achievements in quality management?
(1c) How well do these success parameters indicate business performance?
For these questions we used the following analyses. We followed a two-step approach with
regard to the analysis of the data (see Table 2). First, we carried out a factor analysis on all
items of the award criteria to explore the underlying structure and to detect possible
relationships and interdependencies of criteria. This resulted in an alternative set of independent parameters for hospitals. Second, the criteria and the newly developed parameters were
used to assess quality performance. This speci® c analysis was carried out in two ways. First,
we calculated the criterion and parameter scores for the high-performing hospitals and the
low-performing hospitals in order to explore diþ erences. Second, we tried to assess the
importance of each criterion or parameter by a regression analysis of the criteria and the new
factor analysed parameters, respectively, as explanatory variables for quality performance.
This enabled us to compare the outcomes. Table 2 gives an overview of the comparisons
made in the analysis of the data.
The factor analysis of the items led to a ® ve-factor solution (principal components,
varimax rotation) based on the scree plot which showed a steep descent after extraction of
the ® fth factor (eigenvalues for the ® rst six factors were 36.51, 6.82, 5.04, 4.30, 4.22 and
QUALITY MANAGEMENT IN HOSPITALS
1127
Table 1. Operationalization of the Quality Award criteria
Criteria (number of items)
Description of items
Leadership (3)
·
Appreciation eþ orts of personnel to improve service quality
Informs itself about patients’ /clients’ desires
· Management is the driving force behind increasing quality level
·
·
Policy and strategy (6)
Special attention for patient care
Taking into account opinions or desires of stakeholders (number of
stakeholders)
Use of information sources in formulating and evaluating strategy
(number of information sources)
Strategic policy translated into departments
Management pays attention to clarifying expectations of patients/
clients
Strategic policy periodically evaluated and adjusted
·
·
·
·
·
·
Personnel (5)
Competencies and responsibilities are written down
Competencies and responsibilities at lowest possible level in
organization
· Very clear competencies for personnel do not result in con¯ icts
· Improving level of expertise (average of recruitment, training, career
development, supervision and peer review)
· Open communication in organization
·
·
Resource management (4)
Suý cient support for personnel and professionals
Measurement of costs of achieving quality targets
· Usage of modern technology to achieve constant level of care and
service
· Technological developments result in innovations in products and
services
·
·
Process management (9)
·
Processes that are important for high degree of patient/client
satisfaction have been identi® ed
Measures are taken to identify needs and wishes of patients/clients
Information on care and service delivery processes is gathered in
order
to evaluate and improve processes
Assurance of service delivery processes by means of performance
measures
Working procedures and norms/protocols are available for all positions
Improvement of care and service processes takes place by comparison
with other organizations
Guidelines and procedures for dealing with complaints exist
Information from complaints is used to improve care or service
delivery processes
Changes in care and service delivery are evaluated
·
·
·
·
·
·
·
·
Customer satisfaction (2)
Patient/client satisfaction is measured periodically
Number of diþ erent ways of measuring patient/client satisfaction
(surveys, consultations, visits, complaints, interviews)
·
·
Employee satisfaction (2)
Satisfaction of personnel and professionals is measured periodically
Number of ways employee/professional satisfaction is measured
(complaints, evaluations, surveys, informal contacts)
·
Eþ ect on society (5)
·
Social issues of interest for the organization (average score of
environment, safety, well-being, employment and working conditions)
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P. KUNST & J. LEMMINK
Table 2. Overview of the analysis of the data from hospitals
Analysis of the data
Diþ erences between high and low performers
Importance assessment of criteria and parameters
EQA criteria
3
3
Parameters for
hospitals based on
factor analysis
3
3
3.68, respectively). The ® ve factors accounted for 56.9% of the variance. The resulting
factors could be labelled as follows (see Table 3):
(1)
(2)
(3)
(4)
(5)
Leadership and strategy;
External process management;
Internal process management;
Eþ ect on society;
Technology use.
Remarkably, technology use emerges as a separate factor. Moreover, personnel management
does not emerge in the factor solution. This implies that hospitals cannot be diþ erentiated
on the basis of `personnel’. A logical explanation for this could be that personnel in hospitals
have experienced a large standardization of skills outside their present job and standardization
of work on the job (Mintzberg, 1989). Therefore, there are no clear distinctions between
hospitals in this respect. Furthermore, there are close interrelationships between employee
satisfaction and service processes within the parameter external process management on the
one hand, and patient satisfaction and service processes within the parameter internal process
management on the other. This results in a distinction between the internal (employee) side
of processes and the external (patient) side of processes, suggesting that the traditional
categorization into technical quality (processes and procedures) and functional quality
(perceived quality) as introduced by GroÈnroos (1984) might be less valid in hospitals.
Examples of internal processes are the staý ng, hiring and retaining of high-quality employees
or evaluation and rewarding of superior performance. Examples of external processes are
complaint handling and procedures to collect policy-relevant information from customers.
Both have a bearing on the way the processes have to be improved. These ® ndings were
acknowledged in a study by Brogowicz et al. (1990). They concluded that although there was
a technical service gap and a functional service quality gap, in both cases the antecedents in
the organization consisted of factors related to human resources and physical resources.
Internal process management relates to technical knowledge and ability (human resources)
and machines, materials, facilities and technologies (technical resources). External processes
relate to service-minded behaviour and employee availability (human resources) and appearance and accessibility (technical resources). This study con® rms the distinction between
internal and external made by Borgowicz et al. The further distinction in technical and
functional elements is not argued, but cannot be derived from our data.
The next step is comparing high performers and low performers. We used two diþ erent
conceptualizations of performance, progress in total quality management (PTQM) on a 1± 10
scale and business performance (BP) of the hospitals in terms of occupation rate, ® nancial
business result (budget) and market share (average of three 1± 5 scales). Low performers had
a score of 0± 4 on the PTQM scale, and high performers scored 8± 10. This selection resulted
in 46 low-performing hospitals and 46 high-performing hospitals (out of a total of 223). The
BP score consisted of an average of three items. Low performers (51) were identi® ed by a
score of 1± 3.9, high performers (73) by a score of 4.5± 5 out of a total of 223 hospitals.
QUALITY MANAGEMENT IN HOSPITALS
1129
Table 3. Results of principal component analysis of EQA items: varimax rotated component matrix with factor
loadings ( factor loadings <0.5 omitted)
Item in questionnaire
Management pays attention to
patients’ expectations
Management appreciates eþ orts
Translation strategy in departments
Evaluation of policy
Management is driving force in
quality initiatives
Number of opinions for formulating
strategy (5)
Number of information sources (5)
Quality in objectives
Identi® cation of key customer
processes
Usage patient complaints
information
Guidelines for dealing with
complaints
Gathering of information on service
Measurement of patient satisfaction
Identi® cation of needs and wishes of
patients
Evaluation of service delivery
processes
Management seeks information on
patients’ wishes
Number of ways of employee
satisfaction measures
Measurement of employee
satisfaction
Measurement of costs of quality
Assurance of care and delivery
processes
Society: environment
Society: work conditions
Society: employment
Society: safety
Society: well-being
Innovative technological
developments
Modern technology is used
a
EQA
criteriona
External Internal
Leader- process process
ship and manage- managestrategy
ment
ment
P&S
Leadership
P&S
P&S
0.71
0.67
0.66
0.64
Leadership
0.59
P&S
P&S
P&S
0.58
0.55
0.54
Process
0.53
Technology
use
0.51
Process
0.70
Process
Process
Customer
0.68
0.66
0.61
Process
0.60
Process
0.56
Leadership
0.55
Employee
0.77
Employee
Resource
0.73
0.60
Process
Society
Society
Society
Society
Society
0.50
Resource
Resource
Eþ ect
on
society
0.78
0.67
0.64
0.63
0.59
0.77
0.75
P & S, Policy and strategy.
High and low PTQM performers
Table 4 contains the average scores of low PTQM and high PTQM performers on the quality
award criteria (average scores) and the ® ve new factor-analysed parameters (average scores).
High-performing hospitals have higher scores on all criteria and parameters simultaneously.
The results suggest that there is no natural, logical order in which higher levels of TQM can
1130
P. KUNST & J. LEMMINK
Table 4. Average scores of low and high PTQM performers and importance weights
Low PTQM
performers
(n 5 46)
High PTQM
performers
(n 5 46)
Importance
(b estimate)
Quality award criteria
Leadership
Strategy
Personnel
Resources
Process management
Customers
Employees
Social eþ ects
3.37
3.27
3.10
2.84
3.09
2.88
1.51
3.73
4.39
4.34
3.93
3.83
4.19
4.13
2.89
4.27
n.s.a
n.s.
0.41 (2)
n.s.
0.67 (1)
0.26 (3)
n.s.
n.s.
Factor-analysed parameters
Leadership and strategy
External process management
Internal process management
Social eþ ects
Technology
3.25
3.43
1.77
3.73
3.21
4.33
4.51
3.29
4.27
3.91
0.79 (1)
0.52 (2)
0.46 (3)
n.s.
n.s.
a
n.s., not signi® cant.
be achieved. One might argue of course that we do not measure the process of attaining a
high level of quality management, but only the results of these processes. It is possible
therefore that during the process of attaining higher levels of quality management a logical
order exists. Here we only study diþ erences after a certain level has been reached, compared
to hospitals that have failed to reach these levels.
In addition to the diþ erences, we calculated the importance of each criterion by
regression analysis. In this way we were able to explain 48.2% of the variance in PTQM
(F 5 23.8, p< 0.0001). Process management is the most important explanatory factor,
followed by personnel management. This underlines the pivotal role of employees (doctors,
nurses) and procedures in attempts to implement TQM in hospitals. The new factor-analysed
parameters account for 46.8% of the variance (F 5 36.4, p < 0.0001). Here, leadership and
strategy, external and internal process management are the most important criteria. Internal
and external process management consists largely of items derived from the criteria process
management, personnel and customers of the EQA model. Therefore, the new model explains
a slightly lower variance with fewer (® ve) explanatory variables, and adds the importance of
leadership and strategy as an explanatory factor for TQM progress in hospitals.
High and low BP
Table 5 shows the average scores of low BPs and high BPs on the quality award criteria
(average scores) and the ® ve new factor-analysed parameters (average scores). Once again,
we calculated the importance of each criterion by regression analysis. Based on the EQA
model we were able to explain 18.0% of the variance in BP (F 5 5.7, p< 0.0001). Strategy
and resource management seem to be the most important drivers of business results of
hospitals. Again, the new factor-analysed criteria account for 18.0% of the variance (F 5 9.2,
p < 0.001). These parameters show the importance of the use of technology, in addition to
internal process management, leadership and strategy.
QUALITY MANAGEMENT IN HOSPITALS
1131
Table 5. Average scores of low and high BPs and importance weights
Low BP
performers
(n 5 51)
High BP
performers
(n 5 73)
Importance
(b estimate)
Quality award criteria
Leadership
Strategy
Personnel
Resources
Process management
Customers
Employees
Social eþ ects
3.53
3.38
3.27
2.94
3.33
3.44
1.65
3.74
4.25
4.10
3.68
3.67
3.93
3.96
2.76
4.24
n.s.a
0.30 (1)
n.s.
0.21 (2)
n.s.
n.s.
n.s.
n.s.
Factor-analysed parameters
Leadership and strategy
External process management
Internal process management
Societal eþ ects
Technology
3.38
3.73
2.02
3.74
3.19
4.11
4.27
3.07
4.24
3.90
0.23 (1)
n.s.
0.20 (2)
n.s.
0.16 (3)
a
n.s., not signi® cant.
Patient perceptions related to achievements in TQM and BP of hospitals
Finally, our goal was to assess the relationship between patients’ quality perceptions and
achievements in TQM and BP of hospitals. This goal was re¯ ected in research questions 2a
and 2b:
(2a) What is the relation between quality management and customer perceived quality?
(2b) What is the relation between customer perceived quality and business performance?
Nelson et al. (1992) concluded that hospital quality accounted for 17± 27% of hospital
earnings. We therefore suggest a positive relationship between quality perceptions in hospitals
and hospital performance. We investigated the relationships between PTQM, quality perceptions and BP, using the perceptions of hospital managers with regard to the ® ve SERVQUAL
dimensions (Parasuraman et al., 1988). As stated previously, Schneider et al. (1980) concluded
that there is a close relationship between the employee-perceived quality in banks and the
actual service quality perceived by bank clients. In this case we assume that management
perceptions are a valid proxy of the customer-perceived quality. We tested the hypotheses
using regression analysis.
This analysis shows that 13.5% of the variance in perceived service quality could be
explained (F 5 33.6, p < 0.0001, b 5 0.37) by progress in TQM. Less variance in BP could
be explained. Only 7.1% (F 5 3.05, p 5 0.011) could be explained by customer-perceived
service quality. Additional explanatory power was found by adding progress in TQM to
customer-perceived quality. In total, 12.3% (F 5 4.5 with p< 0.0001) of BP could be
explained by customer-perceived quality (b 5 0.22, p < 0.001) and progress in TQM
(b 5 0.23, p < 0.001) (see Fig. 2). These outcomes suggest that there is a clear relationship
between progress made in TQM and perceived service quality (eVectiveness in Fig. 2). Progress
made in TQM and perceived service quality are linked to BP only to a limited degree, in
which both are equally important. The eþ ect of progress made in TQM on perceived service
quality might be viewed as eþ ectiveness of such programmes. Subsequently, the eþ ect of
progress in TQM on BP might be seen as eý ciency, related to the managerial and cost-
1132
P. KUNST & J. LEMMINK
Figure 2. Explanatory power of progress in TQM and patients’ perceived service quality in relation to business
performance (b estimates).
related variables. First, BP may be dependent on the stage of TQM of the hospitals in this
survey. Improvements may have an eþ ect on perceived service quality, but in this stage do
not result in cost reductions. Second, compared to Nelson et al., our results suggest diþ erences
between the US and the European approach to TQM. In trying to improve the perceived
service quality the focus of European hospitals may be on cost reduction, while the focus of
US hospitals may be more on competition and patients.
Conclusions
Models to measure and implement TQM are fashionable. Clearly there is a need to be able
to assess progress and achievements in this area. However, our research shows that there are
severe limitations. First, models should be used in the context in which they are developed.
Measurement of BP diþ ers from the measurement of progress in TQM. If we look for progress
in TQM there are diþ erent explanatory variables as compared to business performance (see
Table 6). Second, the object of measurement (e.g. the sector studied) also in¯ uences the
models to be used. Our factor analysis shows diþ erences in explanatory variables (see also
Table 6). For instance, for hospitals a role for technology use emerges.
Patients’ quality perception scores are an important factor in the relations between TQM
and BP in hospitals (Babakus & Mangold, 1992; Peyrot et al., 1993). Our research showed
that TQM in¯ uences perceived service quality by patients and, to a lesser degree, BP. This
suggests that hospitals achieve better BP with patient-oriented strategies. In this respect our
research con® rms previous research. However, there are diþ erences between the US and
Europe. TQM in US hospitals is probably more patient-oriented and eþ ective than in
European hospitals.
Table 6. Importance ranking of explanator y variables for progress in TQM and BP
Progress in total quality
management
EQA model
1. Process management
2. Personnel
3. Customers
Parameters/based on factor analysis 1. Leadership and strategy
2. External process management
3. Internal process management
Business performance
1. Strategy
2. Resources
1. Leadership and strategy
2. Internal process management
3. Technology use
QUALITY MANAGEMENT IN HOSPITALS
1133
Acknowledgements
This study was ® nanced within the context of the European Innovation Monitoring Initiative
(EIMS) and as part of the Strategic Programme for Innovation and Technology Transfer
(SPRINT) of the EC Directorate-General on Information Technologies and Industries, and
Telecommunications (DG-XIII). We thank Tacho Ru® no Rus, Fernando Craio (University
of Seville), Barrie Dale, Barbara Lewis (UMIST, Manchester) and Ruth Prins (Libertel,
Maastricht) for their advice and assistance in collecting the Spanish, UK and Dutch data.
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