Assessing Total Quality Management (TQM) Effect on Hospital Performance in Ghana Using a Non-Probabilistic Approach: The Case of Greater Accra Regional Hospital (GARH)

Abstract

Background:

TQM has gained extensive prominence over the last few decades and continue to play a significant role in modern healthcare delivery.

Objectives:

The objective of this empirical inquiry is to explore the nexus between TQM critical success factors implementation and hospital performance by soliciting employee and patient’s views within the Ghanaian context, focusing on Greater Accra Regional Hospital, a prime provider of secondary public healthcare in Ghana.

Methods:

A cross-sectional approach (research design) was espoused for the study which made use of quantitative research techniques for its analysis. The study was based on self-answering structured (close-end) questionnaires completed by 250 respondents selected via convenient sampling. SPSS 25.0 was utilised for data analysis. Statistical analyses include descriptive statistics, principal component analyses, exploratory factor analyses with varimax rotation, reliability analyses, and multivariate regression analyses.

Results:

The study found significant positive relationships between all nine TQM constructs and hospital performance. Findings further revealed that the top management leadership construct contributed most to hospital performance, while training contributed least.

Conclusion:

The study made recommendations that have practical implications for hospital administrators/managers.

In this circumstance, findings/recommendations established, should be considered crucial for hospital administrators/managers and policy makers when dealing with decisions affecting TQM assessment by exploring the potential practicability of the nine TQM critical success factors utilised in this study as a pertinent contrivance for initiating continuous service improvement in GARH in particular and Ghana’s public healthcare sector in general.

Keywords

Ghana hospital performance service quality total quality management (TQM)

Background

The International Organization for Standardization (ISO) standard ISO 8402:1994 defines total quality management (TQM) as “A management approach of an organisation centred on quality, based on the participation of all its members and aiming at long term success through customer satisfaction and benefits to all members of the organisation and society.”¹ TQM has gained extensive prominence over the last few decades and continues to play a significant role in modern healthcare service delivery in view of the varied contributions its effective adoption and implementation bring. It is, therefore, seen as a means for improving service quality and for achieving organizational success. TQM infusion into the healthcare systems, which began in developed countries and shifted to developing countries, has been indorsed by WHO.² LDCs have commenced embracing canons for accreditation in healthcare so as to direct efforts towards healthcare standardization on a universal scale and to endeavour to offer their citizenry with healthcare delivery services of international repute.³

Consequently, over the last 30 years, numerous healthcare institutions have embraced TQM philosophy as a means of upgrading healthcare quality. The adoption of effective TQM principles has the advantage of aiding healthcare establishments to first of all identify patient’s needs, second, render accurate healthcare services, third, set yardsticks for best practices and, last, improve general medical processes.⁴ Ghana, a lower middle income developing country south of the Sahara, has now reached the TQM implementation stage in healthcare service delivery in view of the fact that its Ministry of Health (MoH) recognizes healthcare quality improvement as an integral part of the entire nation building process.

In literature, TQM is recognized as a worldwide strategic managerial principle, which has the advantage of resulting in enhanced customer satisfaction, superior employee focus and motivation, reduced operational waste, and improved overall firm performance.^5,6 It has, thus, evolved that TQM is seen as a means to enhance the efficacy and proficiency of public healthcare delivery functions worldwide. Numerous health centres are reverting to the adaptation and implementation of effective TQM principles for lowering operational costs and overall advancement in healthcare services delivery globally. Notwithstanding the fact that there exist some quality measurement mechanisms, many scholars are of the view that the quality measurement is not yet well conventionalized in the healthcare system.^7,8

Even though TQM has been widely researched for many years now, the focus has largely been centred on the manufacturing setting, leaving limited empirical research to be conducted in the service industry, specifically the healthcare industry and particularly in developing countries, Ghana inclusive.^9,5 As such, it is highly important that more scientific inquiries be conducted to ensure that the deployment and implementation of effective TQM practices is a valuable contribution to public healthcare delivery operations.

Objective of the Study

The novelty of this empirical inquiry is the investigation of the nexuses between TQM critical success factors (CSFs) implementation and hospital performance which is evolving in the Ghanaian healthcare delivery system. This is achieved by soliciting employee and patient’s views, focusing on Greater Accra Regional Hospital (GARH), a prime provider of secondary public healthcare in Ghana.

Related Literature Review

TQM Definitions

Worldwide, much research has been conducted in the field of TQM implementation. After a review of the extant relevant TQM literature, it has been found that different researchers adopted different TQM definitions and frameworks based on their own understanding of TQM and research objectives. Consequently, there is less consensus on what TQM is and what constitutes it. As noted by Moore and Brown,¹⁰ there are many definitions of TQM; interestingly, no single definition can express the whole picture. Dale et al.¹¹ described TQM as embody of concepts and ideas in various contexts related to the quality field. Mullins¹² defines TQM as a way of life for an organisation, committed to total customer satisfaction through continuous improvement and the contribution and involvement of people. Godfrey¹³ also defines it as a quality-centred, customer-focused, fact-based, team-driven, senior-management-led process to achieve an organization’s strategy imperative through continuous process improvement. Steingard and Fitzgibbons¹⁴ defined TQM as a set of techniques and procedures used to reduce or eliminate variation from a production process or service-delivery system in order to improve efficiency, reliability, and quality.

Figure 1.

Source: The author.

The Certified Manager of Quality/Organizational Excellence Handbook¹⁵ also defines TQM as a management approach to long-term success through customer satisfaction. The Chartered Quality Institute¹⁶ also defines TQM as a philosophy for managing an organization in a way which enables it to meet stakeholder needs and expectations efficiently and effectively, without compromising ethical values. The United States Department of Defense¹⁷ defines TQM as “a strategy for continuously improving performance at every level, and in all areas of responsibility. From the above-mentioned varied definitions, it is evident that the concept of TQM bothers on continuous improvement on quality issues with the involvement of all culminating in customer satisfaction and overall firm performance.

Theoretical Literature

The theory of quality management has been developed from three different perspectives: First, contributions from quality leaders/experts/gurus,^18–24 second, formal quality award models (Malcolm Baldrige National Quality Award [MBNQA]; European Quality Award [EQA]; The Deming Prize; Kanji Business Excellence Model, the Australian Business Excellence Framework, the 4 P Model among others), and, third, varied measurement studies.

Theories of TQM (Evolution of TQM)

The fruition of TQM into a universal management principle originated through the works of quality gurus.^18–24 Reed et al.²⁵ scientifically reviewed the central concepts of these TQM gurus and revealed the common similarities on TQM elements. Notwithstanding the fact that, there are some variances of views, they all somewhat settled on the significance of the following assessment tools or CSFs: customer focus, continuous improvement, the culture of teamwork and the scientific approach. These critical success elements are the underpinning for changing orientation to develop a sustainable improvement culture for competitive advantage on a continual basis via what has come to be known as the “Joiner Triangle” (continuous improvement, teamwork, and the scientific approach)

Quality Award Models

Worldwide, there are several quality awards, such as the Deming Prize in Japan (1996), the EQA in Europe (1994), the MBNQA in the USA (1999), Kanji Business Excellence Model, the Australian Business Excellence Framework, the 4 P Model among others. With the exception of Kanji Business Excellence Model, all other models are national quality award winning models. The broad aims of these awards are described by Ghobadian²⁶ as follows:

Increase awareness of TQM because of its important contribution to superior competitiveness;

Encourage systematic self-assessment against established criteria and market awareness simultaneously;

Stimulate sharing and dissemination of information on successfully deployed quality strategies and on benefits derived from implementing these strategies;

Promote understanding of the requirements for the attainment of quality excellence and successful deployment of TQM;

Encourage firms to introduce a continuous improvement process.

Principles of TQM

The idea is to state that Researcher/Scholars have not come to a consensus (agreement) on the quantum or number of TQM CSFs as to whether the number is 5, 10 or 15 etc.^27,28 Different researchers settle on their own numbers based on their individual perspective.

These TQM CSFs include principles associated with top management leadership, quality policies, role of quality department, training, employee involvement/relations, teamwork, customer focus, quality information and analysis, process management, continuous improvement, supplier quality management, strategy quality planning, benchmarking, product and service design, social responsibility, employee satisfaction and organizational culture.^29,30 Institutions need to adopt and implement the CSFs effectively if they are to achieve business successes.

Research Model (Theoretical/Conceptual Framework) and Hypotheses

This current empirical inquiry adopts Saraph et al.³¹ model which identified eight CSFs and is slightly modified based on the extant literature¹¹ to nine CSFs to fit more closely to conditions at GARH. The eight-factor Saraph et al. (1989) model includes the role of top management, role of the quality department, training, product design, supplier quality management, process management, quality data, and employee relations. This model is adopted and replicated in view of the recommendations given by most researchers who have utilised the model in different countries and have found the model to be reliable, valid, and replicable in the healthcare sectors^9,32–37 (Motwani and associates replicated the model in India; Badri and associates as well as Danny and Vincent all used the model in United Arab Emirate; Dilber and associates utilised it in Turkey; Macinati in 2008 utilised the model in Italy; Miller and associates utilised it in USA; Alolayyan and associates utilised the model in Jordan). The nine TQM CSFs utilised in this current empirical study are top management leadership (TML), quality policy (QP), quality department role (QDR), supplier quality management (SQM), process management (PM), customer focus (CF), quality information analysis (QIA), employee relations (ER), and training (T).

Evidence from the extant literature^18,11,19 indicates that TQM CSFs have positive impact on firm performance and as such this study expect all nine TQM CSFs to influence hospital performance (both hospital performance [HP] and non-hospital performance [NHP]) positively.

Hypothesis 1 (H₁) : Top management leadership (TML) positively and significantly contributes to the hospital performance.

Hypothesis 2 (H₂) : Quality policy (QP) positively and significantly contributes to the hospital performance.

Hypothesis 3 (H₃) : Quality department role (QDR) positively and significantly contributes to the hospital performance.

Hypothesis 4 (H₄) : Supplier quality management (SQM) positively and significantly contributes to the hospital performance.

Hypothesis 5 (H₅) : Quality department role (QDR) positively and significantly contributes to the hospital performance.

Hypothesis 6 (H₆) : Process management (PM) positively and significantly contributes to the hospital performance.

Hypothesis 7 (H₇) : Customer focus (CF) positively and significantly contributes to the hospital performance.

Hypothesis 8 (H₈) : Employee relation (ER) positively and significantly contributes to the hospital performance.

Hypothesis 9 (H₉) : Training (T) positively and significantly contributes to the hospital performance.

Methods

This current empirical inquiry was carried out at GARH, a secondary public health facility situate in the heart of Accra, Ghana’s capital, within the Osu Klottey sub Metropolis. GARH has among others, an ultra-modern 420-bed capacity, a comprehensive diagnostic and treatment block with 24-hour surgery department, delivering unit, accident and emergency unit, pharmacy, a logistic building, a 42accommodation facility for staff, a school of anaesthesia, a mortuary, and a staff strength of about 400. As regional hospital for the Greater Accra Region, its catchment area is the whole of the region with an estimated population of about 4,283,322 inhabitants, which makes it the 11th largest metro area in Africa.³⁸ Broadly the hospital provides the following services: surgery, medicine, obstetrics and gynaecology, new-born and paediatrics, accident and emergency, and radiology and pharmacy. The hospital also provides teaching and training services for undergraduates and postgraduates as well as continuing professional development (CPDs) for staff.

The research design espoused for this empirical inquiry is cross-sectional design employing quantitative research techniques for its analysis. The study population comprised all employees as well as patients of GARH. However, for the purpose of the study, an accessible population comprised hospital staff, and in-patient and out-patient clients of GARH. This empirical inquiry deployed the use of self-answering questionnaires which were administered on hospital staff and patients of GARH.

The questionnaires were designed and categorized into three sections. The first section gathered sociodemographic information (sex, age, education, and work experience). The second section was structured (closed-end) survey questionnaire on TQM constructs and their corresponding items (used as explanatory variables). The third section was on performance constructs and their respective items (dependent variables).

This empirical inquiry adopted Saraph et al. (1989) model which was slightly modified based on the extant literature³¹, etc. to fit more closely to the situation at GARH. The resultant model was made up of nine (9) constructs and thirty-six (36) items, and their definitions are provided in Appendix 1. The TQM constructs included top management leadership, quality policy, quality department role, supplier quality management, process management, customer focus, quality information analysis, employee relations and training. The performance constructs were grouped into two: HP and NHP all having three items each. All the 42 questions utilised to assess the impact of TQM on hospital performance from the view point of hospital staff and patients were captured on a five-point Likert scale as follows: Strongly Disagree (SD) = 1; Disagree (D) = 2; Undecided (U) = 3; Agree (A) = 4; Strongly Agree (SA) = 5.

Survey questionnaires were pretested (pilot-tested) using 10 patients to ensure the questionnaires were understood and to ensure high internal consistency. A nonprobability sampling technique (convenience sampling) was used to select a sample size of 250 respondents comprising 90 in-patient clients, 100 out-patient clients, 60 hospital staff (doctors—8, nurses—8, pharmacist—8, laboratory technicians—8, radiologist—8, administrators/managers—11, record keeping officials—8, counsellor —1) and all survey participants were made to understand that strict confidentiality and anonymity would be adhered to. The sample size was determined through the formula of standard error of the mean³⁹ as follows:

\begin{matrix} n = \underset{─}{{(S D)}^{2} \times Z^{2}} = \underset{─}{{0.4033517424}^{2} ({1.96}^{2})} = 250 \\ D^{2} {0.05}^{2} \end{matrix}

(Where n stands for sample size, SD for standard deviation [approx = 0.40], Z is standardized error associated with a 95% confidence level which corresponds to 1.96 on the z-table and D is the level of precision/accuracy or acceptable sample error [0.05].)

Written or verbal (oral) informed consents, where applicable, were obtained from the respondents for voluntary participation before administering the questionnaires. Convenient sampling is the technique most often used with inquiries such as this, because only the target hospital patients and employees who were present at the time of the data collection and willing and able (considering patient’s morbidity status) to participate in the study were sampled (inclusion and exclusion criterion). The researcher with the aid of five research assistants, who were trained to understand the questionnaire, administered the resultant questionnaires following purification of the scales to the respondents from 25th November 2019 to 28th February 2020, during working hours. The trained research assistants had a good grasp of the commonly spoken local Ghanaian languages (i.e., Twi, Ga, and Ewe) and could effectively communicate with the respondents. On the average, it took between 15 and 20 minutes for a questionnaire to be administered. Clearance was sort from hospital administrators before conducting the survey. The researcher noted the risk of allowing respondents to take the survey questionnaires home and as such deployed on the spot data collection technique. A total of 275 respondents were sampled, a final Figure 1 of 250 were deemed usable after the researcher had removed those questionnaires that had logic errors or missing values, giving a 91 per cent response rate.

The data collected from the respondents were coded and entered in SPSS version 25.0 for analysis. Respondent’s sociodemographic information/data was analysed using descriptive statistics such as frequency tables. Exploratory factor analysis (EFA) was carried out in order to determine the TQM constructs and their corresponding items. To do this, principal component analysis (PCA) with varimax rotation was utilised as a means of reducing the dataset. EFA was then performed on 36 items and the results are depicted in Table 2.

As a precedence to deploying the EFA, the researcher examined the data’s sampling adequacy and factorability in order to meet all assumptions both statistical and conceptual, necessary and required for the EFA. The researcher then examined the factorability of the data and sampling adequacy, by performing Bartlett’s test of sphericity and the Kaiser-Meyer-Olkin (KMO). Bartlett’s test of sphericity obtained was very significant (p = 0.000). It also had a KMO value of 0.91 which indorsed its (dataset) appropriateness and suitability for FA. All construct with a more than 1.00 eigenvalue as well as items with more than 0.4 loadings and items with less than 0.4 cross-loadings relevant to the other constructs were used for the analysis.²¹ In order to test and ascertain the reliability of the items in each construct, the researcher calculated Cronbach’s α coefficient; values of 0.6 and above were obtained for the items in each construct.²¹ Thereafter, a multivariate linear regression was performed to ascertain the impact of constructs and their predictive potency as explanatory variables on hospital performance (both HP and NHP) being the dependent variables.

Results

Sociodemographic Characteristics of Respondents

250 respondents participated in the survey. More than half (130) constituting 52% were males and the remaining 120 (48%) were females. Majority, 115, representing 46% were in the age range of 21–40 years. Next, 75, constituting 30% were in age range 41–59. Persons of 60 years and above were 40, representing 16%. The lowest 20, constituting 8%, were in the age range 16–20. Majority of the respondents 140 (56%) were diploma holders. 60 of the respondents, representing 24%, were graduates whilst 30, constituting 12%, held postgraduate degrees. The remaining 20 (8%) were student at the basic level. In view of the nature of TQM and performance questionnaires, the study sampled patient respondents who were 16 years and above in order to obtain a cautious yet accurate assessment.

Majority of the respondents, 145 (58%), had worked less than 10 years. 65 of the respondents, constituting 26%, had work experience between 10 and 19 years, whilst 20 (8%) had worked for more than 20 years. It must be noted that, the heterogeneity in the profile of the patients (both in house and OPD) did not account for any variations in the results and as such the research findings are considered reliable. The demographic data of the respondents is presented in Table 1.

Table 1.

The Sociodemographic Data of the Respondents

Variable	Number	Percentage
Sex
Male	130	52
Female	120	48
Age
16–20	20	8
21–40	115	46
41–59	75	30
Above 60	40	16
Education
Basic school students	20	8
Diploma	140	56
First degree	30	12
Postgraduate	20	8
Work Experience
Students	20	8
< 10 years	145	58
10–19 years	65	26
Above 20 years	20	8

Source: Field data compiled by the author.

TQM Constructs and Hospital Performance

A total of 36 items were captured onto nine TQM constructs and six items were captured on two performance constructs (HP and NHP) to test the TQM–performance nexus. The researcher performed EFA in order to bring out appropriate constructs as good explanatory estimators of hospital performance. In ensuring the factorability of the dataset, PCA with varimax rotation was performed and the results are presented in Table 2. The researcher initially extracted 13 constructs having eigenvalue greater than 1; and all 13 factors together accounted for 70.3 percent of the hospital performance (both HP and NHP) total variance. As recommended by researchers such as Feigenbaum,²¹ this extracted structure was not used in view of the fact that some of the items had low-factor loadings and some items had higher cross-loadings. To obtain acceptable structures which are significant statistically, all items having higher than 0.4 cross-loadings and constructs with less than 0.4 loadings were deleted.

Table 2.

TQM Constructs and Their Corresponding Items of Descriptive Statistics

Factors/Constructs	Items	Mean	SD	Loadings	Eigenvalues	% of Variance Extracted	Cronbach Alpha
Top mgt leadership (1)	1 A	4.35	0.87	0.98	12.9	17.9	0.91
	1B	4.15	0.98	0.88
	1C	4.06	0.76	0.99
	1D	4.27	0.79	0.97
Quality policy (2)	2 A	4.23	0.64	0.87	4.5	12.5	0.87
	2B	4.36	0.98	0.79
	2C	3.89	0.75	0.97
	2D	3.56	0.69	0.95
Quality dept role (3)	3 A	3.36	0.81	0.88	3.07	9.5	0.85
	3B	3.27	1.03	0.86
	3C	3.45	0.94	0.94
	3D	3.02	0.86	0.91
Supplier quality mgt (4)	4 A	3.66	0.79	0.87	2.92	7.2	0.94
	4B	3.48	0.93	0.77
	4C	3.99	0.78	0.79
	4D	4.02	0.87	0.93
Process mgt (5)	5 A	3.37	0.84	0.86	1.75	5.8	0.88
	5B	3.54	0.65	0.97
	5C	3.97	0.93	0.88
	5D	3.92	1.15	0.97
Customer focus (6)	6 A	4.15	0.97	0.79	1.55	5.5	0.79
	6B	3.99	0.83	0.94
	6C	3.87	0.76	0.78
	6D	4.08	0.91	0.92
Quality info and analysis (7)	7 A	3.18	0.73	0.91	1.46	4.5	0.93
	7B	3.02	0.82	0.83
	7C	4.05	0.84	0.76
	7D	3.55	1.02	0.98
Employee relations (8)	8 A	3.98	0.76	0.94	1.38	3.9	0.84
	8B	3.41	0.89	0.87
	8C	4.16	0.98	0.78
	8D	3.78	0.78	0.96
Training (9)	9 A	3.65	0.86	0.84	1.15	3.5	0.702
	9B	3.87	0.93	0.95
	9C	3.75	0.78	0.78
	9D	3.42	0.81	0.91
Total						70.3

Source: Field data compiled and analysed using SPSS 25.0 by the author.

Constructs such as teamwork, employee involvement, and employee relations were merged to form a construct named “employee relations,” knowledge management and training constructs were also merged and named “training,” and finally strategy quality planning and top management leadership were merged as one construct named “top management leadership” based upon the strong correlation, and EFA was repeated.

Now, nine factors have been formed for TQM, which accounted for 70.3 percent of the total variance in TQM and deemed higher than the recommended level of 60 percent by Hair et al.⁴⁰ All factor loadings in this FA exhibited statistically significant values of higher than 0.7, which was higher than the recommendation value indorsed by Hair et al.⁴³ TQM constructs having lower (below 0.4) cross-loadings between them depict satisfactory unidimensionality.⁴³

All nine TQM constructs had four items each, whilst performance constructs (HP and NHP) had three items each. Factor I measured top management leadership which produced the most variation explanation having an eigenvalue of 12.9, representing 17.9% of the total variance. Factor II was named quality policy, accounted for an eigenvalue of 4.50, representing 12.5% of the total variance. Factor III was named quality department role, which accounted for a 3.07 eigenvalue, representing 9.5% of the total variance. Factor IV was named supplier quality management, which accounted for a 2.92 eigenvalue, representing 7.20% of the total variance. Factor V was named process management, which accounted for a 1.75 eigenvalue, representing 5.8% of the total variance. Factor VI was named customer focus, which accounted for a 1.55 eigenvalue, representing 5.50% of the total variance. Factor VII was named quality information and analysis, which accounted for a 1.46 eigenvalue, representing 4.50% of the total variance.

Factor VII was named employee relations, which accounted for a 1.38 eigenvalue, representing 3.90% of the total variance. Factor IX was named training, which accounted for a 1.15 eigenvalue, representing 3.50% of the total variance.

In order to test and ascertain the reliability of the items in each construct, Cronbach’s α coefficient was calculated for the constructs and their values swung from 0.702 to 0.940.

Cronbach’s α coefficient value for the overall items of the TQM was 0.858, and it is deemed greater than the value recommended by Hair et al.⁴³ As such the TQM instrument is deemed to have the required reliability and stability.

Hypothesis Testing—Predictors of TQM Constructs on Hospital Performance

To ascertain the impact of all nine TQM CSFs on hospital performance (both HP and NHP), two separate multivariate/multiple linear regressions were run to assess the explanatory potency of the nine extracted TQM constructs, namely top management leadership (TML), quality policy (QP), quality department role (QDR), supplier quality management (SQM), process management (PM), customer focus (CF), quality information and analysis (QIA), employee relations (ER), and training (T) used as predictive/explanatory/independent variables on HP and NHP used as dependent variables with a p < 0.05 set as a statistical standard. The regression models produced adjusted R² values of 0.66 and 0.65 for HP and NHP, respectively, meaning the regression models explained 66% and 65%, respectively, of the variations in the TQM constructs on hospital performance. This indicates that all the nine variables were good explanatory variables of hospital performance and their t-values indicated that these constructs are strong predictors of hospital performance. The notion is to indicate that top management leadership being one of the TQM CSFs as an explanatory variable was the highest contributor or predictor to firm performance (dependent variable) as it recorded the highest beta values of 0.856 and 0.757 for HP and NHP, respectively. The beta values ranks all the explanatory variables with respect to its contribution or predictive potency to the dependent variable. The higher the beta value the better the predictive power. Furthermore, quality policy, quality department role, supplier quality management, process management, customer focus, quality information and analysis, employee relations, and training are significantly good TQM predictors of hospital performance.

An analysis of the explanatory variables (TQM constructs) in terms of their predictive power is ascertained by the standardized β values (the higher the β value, the more important the construct is) that are essential for relating regression coefficients vis-a-vis their impact on the dependent variable. A comparative analysis from the results in Table 3 shows that the most important predictor of the hospital performance was top management leadership, having β values of 0.856 and 0.757 for HP and NHP, respectively, and statistically significant at p = 0.000 ˂ 0.05 for HP and p = 0.001 for NHP; followed by quality policy with β values of 0.318 for HP and 0.405 for NHP, and statistically significant at p = 0.010 ˂ 0.05 for HP and p = 0.003 for NHP. Quality department role was the third best predictor of hospital performance, having β values of 0.26 for HP and 0.259 for NHP, and statistically significant at p = 0.001 ˂ 0.05 for HP and p = 0.002 for NHP. Supplier quality management with β values of 0.180 for HP and 0.189 for NHP, and statistically significant at p = 0.003 ˂ 0.05 for HP and p = 0.003 ˂ 0.05 for NHP was the fourth best predictor of hospital performance.

Process management was the fifth best predictor of hospital performance with β values of 0.170 for HP and 0.165 for NHP, and statistically significant at p = 0.001 ˂ 0.05 for HP and p = 0.010 for NHP. Customer focus was the sixth best predictor of hospital performance with β values of 0.161 for HP and 0.158 for NHP, and significant statistically at p = 0.010 < 0.05 for HP and p = 0.002 for NHP. Quality information analysis was the seventh best predictor of hospital performance with β values of 0.145 for HP and 0.140 for NHP and significant statistically at p = 0.003 < 0.05 for both HP and NHP. Employee relations was the eighth best predictor of hospital performance with β values of 0.140 for HP and 0.135 for NHP, and significant statistically at p = 0.002 < 0.05 for HP and p = 0.001 for NHP.

The last predictor of hospital performance was training having β values of 0.120 for HP and 0.115 for NHP and statistically significant at p = 0.003 ˂ 0.05 for HP and p = 0.010 for NHP.

The standardized regression models are as follows:

HP = β₀ + (0.856 × TML) + (0.318 × QP) + (0.260 × QDR) + (0.180 × SQM) + (0.170 × PM) + (0.161 x CF) + (0.145 × QIA) + (0.140 × ER) + (0.120 × T) + ℓ.

NHP = β₀ + (0.757 × TML) + (0.405 × QP) + (0.259 × QDR) + (0.189 × SQM) + (0.165 × PM) + (0.158 × CF) + (0.140 × QIA) + (0.135 × ER) + (0.115 × T) + ℓ

Here, β0 and ℓ represent the intercept (constant) and stochastic disturbance term, respectively.

It is evident that TML, QP, QDR, SQM, PM, CF, QIA, ER, and T positively and significantly predict hospital performance both HP and NHP. The hypotheses stands accepted as impact is positive and significant (evident by the β_{(1, 2, 3, …, 9)} and p_{(1, 2, 3, …, 9)} values exhibited in Tables 3 and 4).

Table 3.

A Multiple Linear Regression of TQM Dimensions on Hospital Performance

Predictors	B		SE		β		t-value		Sig
Predictors	HP	NHP	HP	NHP	HP	NHP	HP	NHP	HP	NHP
Constant/Intercept	1.055	1.765	1.115	1.097	7.154	6.356	6.4161	5.876	0.435^*	0.438^*
Top mgt leadership	0.266	0.298	0.189	0.190	0.856	0.757	4.529	3.984	0.000^*	0.001^*
Quality policy	0.185	0.123	0.095	0.099	0.318	0.405	3.347	4.091	0.010^*	0.003^*
Role of quality dept.	0.315	0.468	0.089	0.090	0.260	0.259	2.921	2.878	0.001^*	0.002^*
Supplier quality mgt	0.155	0.109	0.079	0.080	0.180	0.189	2.278	2.360	0.003^*	0.003^*
Process mgt	0.316	0.309	0.039	0.039	0.170	0.165	4.359	4.231	0.001^*	0.010^*
Customer focus	0.175	0.155	0.059	0.060	0.161	0.158	2.729	2.633	0.010^*	0.002^*
Quality info and analysis	0.240	0.299	0.050	0.052	0.145	0.140	2.900	2.692	0.003^*	0.003^*
Employee relations	0.257	0.375	0.051	0.055	0.140	0.135	2.745	2.455	0.002^*	0.001^*
Training	0.198	0.177	0.049	0.050	0.120	0.115	2.449	2.300	0.003^*	0.010^*

Source: Author’s compilation and processing of field data (2020) using SPSS 25.0.

Notes: HP R² = 0.67; adjusted R² = 0.66; F-value = 26.15; p = 0.000, p < 0.05

NHP R² = 0.66; adjusted R² = 0.65; F-value= 26.15; p = 0.000, p < 0.05

* Significant at 5% (0.05).

Table 4.

Chi-square Test for Hypothesis Results

Sl no. Hypothesis Significant Level (HP) Significant Level (NHP) Result

1 Hypothesis 1 *0.000 *0.001 Significant

2 Hypothesis 2 *0.010 *0.003 Significant

3 Hypothesis 3 *0.001 *0.002 Significant

4 Hypothesis 4 *0.003 *0.003 Significant

5 Hypothesis 5 *0.001 *0.010 Significant

6 Hypothesis 6 *0.010 *0.002 Significant

7 Hypothesis 7 *0.003 *0.003 Significant

8 Hypothesis 8 *0.002 *0.001 Significant

9 Hypothesis 9 *0.003 *0.010 Significant

Source: Compiled by author’s own calculation.

Note: *Significant at the level 0.05.

Discussion

This empirical inquiry sought to examine TQM CSFs, and their implementation and impact on hospital performance. There were some form of quality management systems being implemented at GARH. It is evident from this study that GARH has embraced the TQM philosophy led by its TML by sensitizing employees, both medical staff and non-medical staff, from departmental heads, down to the ordinary employees through continuous improvement of quality healthcare service delivery. This is seen in the organization formulating and implementing a policy on “quality” and also establishing an entire quality department. This speaks volumes about the importance GARH attaches to quality issues.

This is reflected in the positive and significant influence of factors such as TML, QP, QDR on hospital performance factors such as improved level of medical quality and quick turnaround bed cycle as evident in the beta coefficients result obtained from the regression analysis in Table 3. This is how constructs like TML recorded the highest β of 0.856 for HP and 0.757 for NHP, QP followed with a β of 0.318 for HP and 0.405 for NHP, and QDR with a β of 0.260 for HP and 0.259 for NHP.

It is also obvious that GARH is managing its relationship with its selected dependable suppliers of drugs and other medical supplies as well as other logistics pretty well, as information gathered from the respondents indicates that GARH places much emphasis on quality rather than cost (price) when it comes to procurement of supplies. Information obtained from the respondents revealed that GARH provides certification to its suppliers and routine audit takes place to maintain the quality of product standards, and regularly takes feedback so as to maintain quality standards. This is reflected in the positive and significant impact of supply quality management factor on hospital performance, recording a β of 0.18 for HP and 0.189 for NHP.

With respect to hospital PM, which deals with conformance to patients’ requirements by means of improving hospital key processes, the information gathered from respondents revealed that GARH has performed averagely. Notwithstanding the fact that there is clarity of process ownership, boundaries, and steps, and that procedural activities are well outlined, defined, and communicated to employees to understand, information gathered from respondents revealed that managers and supervisors do not frequently undertake inspection of service quality and processes to improve hospital services. Inspections are done once in a blue moon. Also, there are no programs to find wasted time and costs in all internal processes. This is why the hospital recorded a β of 0.170 for HP and 0.165 for NHP.

GARH is a secondary public health facility established to provide medical care for the Greater Accra Region populace and beyond as well as to handle referral cases from the primary healthcare facilities, and as such its main customers are its patients. The hospital is there to serve the general public and as such medical personnel try to deliver their very best to their clientele base. This notwithstanding, the hospital faces the challenge of a number of customer dissatisfaction issues some of which are patients having to wait for long hours in long queues before receiving medical care, emergencies are not attended to promptly, unfriendliness on the part of some medical personnel, patients receives no feedbacks on their complaints, etc. Information collected from respondents revealed that the sited issues were some of the challenges that confront GARH. In addition, the hospital does not conduct any customer satisfaction survey on a regular basis so as to be in the know about such customer satisfaction issues for them to be attended to. This is reflected in the hospital recording a β of 0.161 for HP and 0.158 for NHP.

With respect to QIA, which deals with the availability of reliable, adequate, timely. and relevant data/information for all key users to improve healthcare quality, information retrieved from participants indicated that GARH has a system of providing such information to the general public but it operate with issues. For instance, the hospital operates an active website for the provision of such information but most often it is not updated or is temporarily out of order. Information about patient–doctor appointment booking procedures is not clear, among other issues. This is reflected in the hospital recording a β of 0.145 for HP and 0.140 for NHP.

Employee relations (ER) falls under Human Resource Management (HRM) issues as a bigger umbrella concept. Information gathered from respondents revealed that GARH has a system that takes care of HR issues such as staff remuneration, housing facilities, study leaves, shift systems, and transportation allowances.

It should be noted that a well satisfied employee with respect to his/her job generates self-motivation, high labour productivity—achieved through teamwork, employee involvement, excellent self-initiative taking, which culminate into higher overall organizational performance.

Information obtained from the respondents revealed that hospital staff have concerns with their welfare issues and if these concerns are not handled swiftly, they may affect worker productivity negatively. The employee relations issues is reflected in the hospital recording a β of 0.140 for HP and 0.135 for NHP. Information obtained from respondents indicated that GARH has schemes for the provision of quality-related training including quality concepts and quality improvement techniques for the staff of GARH, but medical staff do not go for such training regularly in view of the fact that resources are not made available for medical practitioners to take advantage of such training schemes. In addition, some medical personnel were of the view that employee training selection procedures are unfair, not open, and ambiguous. This is reflected in the hospital recording a β value of 0.120 for HP and 0.115 for NHP.

Conclusion

This current empirical inquiry examined the effect of TQM CSFs implementation on hospital performance by exploring employee and patient’s views within the Ghanaian context, focusing on GARH, a prime provider of secondary healthcare. The study found positive and significant relationships between all nine TQM factors and hospital performance. The study further revealed that some TQM CSFs such as top management leadership, quality policy, and quality department role contributed more to hospital performance than others such as training, employee relations, quality information analysis, and customer focus.

Managerial Consideration

This scientific inquiry recommends the following:

Managers of hospitals in general and GARH in particular should conventionalize TQM surveys, using the nine TQM constructs utilised in this study, that is, top management leadership, quality policy, role of quality department, supplier quality management, process management, customer focus, quality information and analysis, employee relations, and training to track hospital performance on a periodic basis; medical staff will be in a position to benefit immensely from such TQM evaluation mechanism as this will result in performance improvement and overall improvement in healthcare delivery functions. Again, the nine TQM constructs should be given utmost attention in an attempt to improve organizational performance.

GARH in particular and healthcare institutions in general should deepen their sensitisation and training of staff policies so that their staff be in the full know about whatever TQM policies the institution embarks on as the study noted that some staff members were unaware of some of the TQM policies ongoing in the very institution they work.

Top management leadership require the technical and analytical acumen to systematically access quality management alternatives as the success of every TQM policy very much depends on quality information analysis, that is, the flow of vital information from the top management level to every member of the organization and the receiving of feedbacks by the top management.

The government should dialogue with hospital staff with respect to their welfare concerns in the area of remunerations, housing facilities, study leaves, shift systems, transportation allowances, etc., in order to motivate medical practitioners to give their best and increase health worker productivity with the overall effect of increasing hospital performance.

Managers and administrators of GARH in particular and healthcare institutions in general should adopt and implement the customer orientation philosophy by directing all efforts, time, and resources towards not only satisfying their customers (patients) but also moving a step forward to delighting them as the success, survival, and continuity of every business entity (including healthcare institutions notwithstanding the fact that healthcare service provision is a necessary need) very much depends on the customer.

Limitations and Future Research

The use of non-probabilistic or non-random sampling technique (such as convenience sampling, purposive sampling, quota sampling, judgemental sampling, and snowball sampling) as a means of obtaining the sample size in any scientific inquiry weakens the predictive/forecasting power of the research and hence renders the research nonrepresentative, that is, it does not allow the study findings to be generalized from the sample to the entire population. This is because the chance of a respondent being included in the sample is unknown. This is a huge limitation of such scientific inquiries. But as explained earlier, the nature of the study is such that it does not allow the researcher full access to the entire population from whom the sample can be drawn and this is the reason why such a technique was utilised.

In addition, the research gathered information from survey participants on TQM issues and hospital performance measures, and it is highly likely that some participants may provide information that might portray good image of the very institution in which they work (an occurrence that is referred to as “desirability” in scientific inquiries lexicon) rather than what actually pertains on the ground. This may affect the quality of the research findings and jeopardize the entire research exercise.

Future studies in this area should consider broadening the database by including more hospitals to have a feel of the bigger picture in Ghana as well as considering the possible practicability of deploying a probabilistic or random sampling technique (simple random, systematic sampling, stratified sampling, cluster sampling, multi-stage sampling, etc.) in arriving at the sample size.

Footnotes

Acknowledgements

I would like to acknowledge and extend my heartfelt gratitude to the management of GARH for granting me the opportunity to use their organization and giving me the necessary information and contacts to the key staff and patients for the study. I am also grateful to all the participants of the study for taking time to participate in the survey. Special thanks goes to the five research assistants who assisted in the data collection and interview process.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

Appendix

Appendix 1.

TQM Constructs and Their Corresponding Items Definitions

Factors/Dimensions	Definitions
Top mgt leadership (1)	The vital role played by top hospital managers and administrators in driving TQM agenda and issues at GARH
	1 A = Top mgt. is actively involved in communication and planning of organizational goals
	1B = Top mgt. provide significant means (resources) to improve and maintain quality
	1C = Top mgt. take quality as their responsibility
	1D = Top mgt. anticipate changes and makes plans to accommodate it
Quality policy (2)	Assessing the formulation and implementation of quality strategies and goals of GARH
	2 A = GARH has a written policy document on quality principles
	2B = Quality issues is given the utmost priority by GARH
	2C = GARH does not compromise on quality principles
	2D = Any deviation from the laid down quality strategies and policies of the hospital is punished
Quality dept. role (3)	The visibility, autonomy and coordination ability of the quality dept. in achieving TQM goals of GARH.
	3 A = The quality dept. of GARH is clearly visible and all staff can attest to their key functions and roles
	3B = The work of the quality dept. of GARH is independent and are highly autonomous devoid of top mgt. influences
	3C = The quality dept. of GARH coordinates efficiently and effectively with all the other depts. of GARH.
	3D = The quality dept. of GARH’s work is satisfactory
Supplier quality mgt. (4)	Assessing the effectiveness and long-term cooperation with fewer dependable suppliers to improve quality. The extent to which purchasing policy emphasizes quality rather than cost
	4 A = GARH regards the quality of medical supplies more importantly than cost considerations before selection a supplier
	4B = GARH has provided certification to its suppliers and routine audit takes place to maintain the quality of product standards
	4C = GARH has detailed information about its suppliers and their respective performances.
	4D = GARH suppliers regularly takes feedback so as to maintain quality standards.
Process mgt. (5)	Conformance to patients’ requirements by means of improving hospital key processes. Clarity of process ownership, boundaries and steps
	5 A = There is a program to find wasted time and costs in all internal processes
	5B = There is frequent inspection of service quality and processes to improve hospital services duly takes place.
	5C = Procedural activities are well outlined, defined and communicated to and understood by all
	5D = GARH employs the 7-tools of quality to plan, control and improvement of processes.
Customer focus (6)	The degree with which GARH serves its clients’ needs and expectations. The extent to which GARH implements the customer orientation philosophy by directing all its resources including all staff efforts on its customers
	6 A = Summaries of customer complaints are given to departmental heads i.e. Ward Manager/Head of OPD/Charge Nurses/Charge Doctor etc.
	6B = Quality-related customer complaints are treated with top priority
	6C = Customers’ requirement is used as the basis for measuring quality.
	6D = The hospital conducts a customer satisfaction survey on a regular basis
Quality info and analysis (7)	Assessment of how GARH Mangers and Administrators ensure the availability of reliable, adequate, timely and relevant data and information for all key users to improve healthcare quality
	7 A = Hospital website is active and periodically updated with requisite, relevant and adequate data for public consumption
	7B = There is readily available information as to patient-doctor appointment booking procedures
	7C = Information on directions to various depts., lavatories, canteens etc. can be visible seen on hospital premises
	7D = Information on hospital directives, safety and emergency precautionary measures such as fire outbreaks can be visible seen on hospital premises
Employee relations (8)	A general component that encompasses a variety of human resource mgt practices for the success of TQM in GARH, such as employee involvement, empowerment, recognition, teamwork etc.
	8 A = Employees are very committed to the success of the hospital - Employee Involvement
	8B = Employees are empowered to take direct action whenever it is likely to affect quality - Organisational Culture
	8C = We often work in teams, with members from a variety of departments – Teamwork
	8D= Recruitment procedures are such that “right persons are selected for the right jobs/positions” - HRM
Training (9)	Provision of quality-associated capacity building including quality concepts, quality improvement techniques for the staff of GARH
	9 A = Employee training is provided in quality principles
	9B = Resources are available for employee quality training
	9C = Employee training selection procedures are fair, open and devoid of favouritism and nepotism
	9D = Employee training on quality principles are undertaken frequently and regularly
Healthcare performance	These are performance parameters that are directly related to healthcare service measures
	HP1 = Level of medical quality
	HP2 = Patients level of stay for medical care hospital
	HP3 = Bed cycle time
Non-healthcare performance	These are performance parameters that are subjective in nature and indirectly related to healthcare service measures
	NHP1 = Customer satisfaction level
	NHP2 = Financial benefits and market development (respondent perceptions on revenue and profitability)
	NHP3 = Reputation among major customer segment (I have a very high regard for the superior health service provided)

Source: Adopted from Saraph et al. (1989) model and modified to suit the Ghanaian context.

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