Utilizing Multi-Criteria Decision Making to Evaluate the Quality of Healthcare Services

Abstract

Today’s patients are more informed and quality-conscious than ever before, which is crucial for healthcare practitioners as they interact with people’s lives daily. One of the most important challenges facing the healthcare sector worldwide concerns how to improve the overall quality of hospital care. As a result of the highly competitive nature of the economy in which healthcare services are offered, both public and private hospitals in Saudi Arabia must have their patient satisfaction rates assessed to help consumers make more informed decisions. As a result, we used the analytical hierarchy process (AHP) model to ascertain how patients in Saudi Arabia perceive the quality of the service that is provided by hospitals. The objective of the research work is to identify criteria for enhancing healthcare services using the analytic hierarchy process (AHP) technique to model the five SERVQUAL dimensions along with 2 dimensions and 31 sub-criteria. Three healthcare service organizations were selected for the study and evaluated based on their service quality performance. The AHP-based model has been demonstrated systematically for ranking the hospitals based on the healthcare system. It is observed that hospitals should concentrate the most on reliability, tangibles, and security and the least on consistency. In addition, according to the sub-criteria, the hospitals’ primary priority should be infection prevention and hygiene, with completeness receiving the least attention. Based on a survey of dimensions and their sub-criteria, the best hospital is Abha Private Hospital, followed by AHH, and then Asir General Hospital. Therefore, this study has implications for choices on the efficient monitoring of the overall health system to improve quality service delivery that would boost patient happiness, which is the goal of creating hospitals.

1. Introduction

The decision-making process in the complex service sector of healthcare necessitates the participation of several stakeholders with varying interests and values [1,2]. In the past few decades, researchers have used a variety of multi-criteria decision making (MCDM) techniques, such as the analytic hierarchy method (AHP) and hybrid methods [3], to handle real-time issues in the healthcare system. The bulk of prior research has concentrated on integrating multiple MCDM approaches to discover the optimal solutions [4]. Most present MCDM techniques provide conclusions based on a single stakeholder group’s perspective. However, integrating stakeholders in the decision-making process is vital for the healthcare industry, even though their diverse opinions might make reaching a consensus challenging. In fact, a lack of agreement among stakeholders leads to a number of solutions reached through the process of collaborative decision making ultimately being unsustainable [5]. Recently various studies have been carried out. For instance, Dezert et al. [6] created the rank reversal-free stable preference ordering towards an ideal solution approach (SPOTIS). The determination of the attribute weights plays a crucial role in various MCDM techniques, as shown by Kizielewicz et al. [7] in their study. A framework for performance evaluation was created by Khan et al. [8]. Fartaj et al. [9] coupled BWM with rough strength relation to anticipate transportation disruption issues, allowing managers to focus on the specific issue rather than attempting to handle all of the connected aspects. The major obstacle to implementing Industry 4.0 in the leather industry, according to Moktadir et al. [10], was a “lack of technical infrastructure.” However, the BWM has consistency issues [11]. To overcome this constraint and reach a consensus solution across stakeholders, researchers have employed multi-objective linear programming (MOLP) [12]. MOLP can be carried out with the use of a tool known as sequential interactive modelling for urban systems (SIMUS), which has a long history in the decision-making sector [13].

MCDM in Healthcare SYSTEM

In the healthcare and medical sector, there are numerous methods for making decisions regarding how to evaluate service quality. For instance, Hsu and Pan [14] investigated the quality structure of dental services and accurately determined the ranking of the key qualities using AHP and Monte Carlo techniques. Shieh et al. [15] created and assessed hospital service quality standards utilizing the DEMATEL method to identify the critical success factors for such an assessment. To evaluate the provided service quality model, Büyüközkan et al. [16] used a fuzzy AHP technique. To rank service quality factors, Altuntas et al. [17] combined AHP and ANP methodologies. In order to construct an objective and high-quality index of physical treatments and conduct a systematic analysis and innovation plan application for the hospital’s services, S.-F. Lee and Lee [18] employed ANP and DEMATEL methodologies. To determine the significant weights of evaluation criteria for service quality performance and to analyze the caliber of services provided in private hospitals, Chang [19] used the fuzzy VIKOR technique. In order to determine the most significant indicators that may be utilized for quality assessment of Iranian health facilities, Moslehi et al. [20] employed the AHP and Delphi approaches to compute the weights of quality management indicators. The fuzzy AHP and TOPSIS approaches were used by Shafii et al. [21] to assess the service quality of a teaching hospital in Yazd, Iran. In order to evaluate the service quality in the context of healthcare, La Fata et al. [22] introduced a unique technique based on fuzzy ELECTRE III and importance-performance analysis (IPA) among various MCDM techniques used in the healthcare system. In AHP, each element of the hierarchy is given a numerical weight or priority, which enables varied and sometimes incomparable items to be compared to one another in a fair and consistent manner. The AHP stands apart from other methods of decision-making because of this feature.

The present research deals with selecting healthcare organizations that would provide a high-quality healthcare system using the AHP technique based on surveys from stakeholders involved in the healthcare system. One of the most significant aspects of healthcare quality is the level of patient satisfaction. Analysis of healthcare service quality from the patient’s point of view has beneficial implications for a hospital, including helping to devise quality improvement strategies [23]. In today’s competitive environment, providing health services that fulfill patients’ needs and expectations improves an organization’s chance of survival [24]. To date, various definitions of healthcare quality have been employed. According to the British National Health Service (NHS), healthcare quality is described as providing the appropriate services to the right people at the right time, with the right approach, and within population affordability [25]. Gronroos [26] developed a two-dimensional quality model that includes both technical and functional criteria; patients tend to have difficulty recognizing technical quality, although they can quickly evaluate functional aspects [27]. Several methods have been developed to assess the quality of healthcare services, which are frequently subject to uncertainty [28]. Thomas L. Saaty developed AHP in the 1980s as a structured technique for analyzing complex problems based on mathematics and psychology. Those who use the AHP method first divide their chosen problem into a hierarchy of better-understood subproblems, each of which may be examined separately. When the hierarchy is established, the factors are thoroughly assessed by comparing their impact on an element above them [16].

Healthcare is entirely a professional service [29] and considers the patient’s perception as a yardstick for enhancing the quality of service [30]. These days, most hospitals assess patients’ perception of healthcare SERVQUAL and make an electronic record of their medical history and satisfaction on a perception scale apart from paper-based records [31].

In assessing the quality of an organization’s services, it is necessary to be aware of advancements in the documented literature, which necessitates conducting a comprehensive literature review. As a result, an up-to-date literature review was conducted to ascertain the gaps in the existing body of knowledge regarding hospital health services. This research then attempts to fill in some of the gaps in the existing literature. It also aims to identify how hospital management can enhance patient satisfaction by improving and boosting their services to the patients.

Any organization with good strategies in place can gain a sustainable competitive advantage; therefore, it is essential to make the right choices, and as the organizational environment evolves, it is necessary to continuously adjust or optimize the options that have been chosen. This will eventually lead to an optimal decision. Process improvement techniques such as Six Sigma, Lean Six Sigma, Kaizen, and others prioritize judgments based on the analytic hierarchy process (AHP). They have proven to be helpful because they take both concrete and intangible variables into account.

The following are the primary goals of this study:

• To provide a comprehensive assessment of the literature on service quality and a foundation for future study in this area.
• To demonstrate the significance of the identified elements and dimensions in analyzing and measuring the quality of healthcare services.
• To create an AHP-based hierarchical model to prioritize SRVQUAL dimensions as well as two extra dimensions and sub-criteria.
• Utilizing the AHP technique for selecting the healthcare services that offer the best overall value from among the available options.

The rest of the paper is organized as follows: Section 2 provides an in-depth, categorized literature review on service quality; the service quality dimension and sub-criteria; Section 3 concentrates on research design; AHP methodology; and how the model was developed; and highlights the prioritization of dimension and sub-criteria of SERVQUAL. Section 4 presents a detailed discussion about results analysis, and finally, the paper ends with Section 5 conclusions and, Section 6 future scope in the area of service quality assessment.

2. Theoretical Concepts

This section presents an extensive review of the literature which was carried out to gain insight into service quality. Accordingly, the literature is broadly classified into three main concepts: service quality; an overview of healthcare quality; and dimensions and sub-criteria of service quality.

2.1. Service Quality

The idea of quality has many facets, and it can mean different things to different people. The concept of service quality cannot be easily defined or quantified due to its intangible nature. A product or service is only considered to have value once a customer has purchased it. In most cases, patients purchase items and then rate them based on their personal experiences when using them. If customers have a good experience with a product and decide to repurchase it, they are more likely to speak of its benefits to their friends and family.

Consequently, the consumer’s use of a product, their evaluations of that product, and word-of-mouth promotion are all effective ways to build its image. As a direct consequence, the notion of service quality is vague and lacking in precision [32]. This makes it more challenging to evaluate and control the service.

Service quality can be considered an attitude resulting from a comparison of expectations with actual performance, which is comparable to but not the same as pleasure [32]. It is possible to define performance expectations of a product as a belief in its capability to deliver on the promises it has made. In healthcare, this is based on patients’ beliefs about the service’s performance and represents their aspirations and desires. Thus, service quality can be defined as the gap between client expectations and perceived service. When expectations exceed performance, perceived quality falls short of adequate, resulting in consumer discontent.

2.2. Healthcare Quality

Patients in Saudi Arabia are becoming more involved in their care and more likely to make detailed or individualized treatment requests due to this trend. They then rate the services provided; therefore, as a result, healthcare facilities must continue to monitor requests and pay close attention to how customers rank their services. Thus, hospitals must prioritize healthcare quality, caring for their customers, and offering a qualified perceived service. For this reason, service quality has become an essential commercial strategy for healthcare firms [33]. Numerous conceptual frameworks are presented in the research that has been carried out on the evaluation of healthcare quality. Lee et al. [34] found the dimensions of basic medical service and professionalism/skill to be an extra dimension to responsiveness, assurance, and confidence. These dimensions evaluate the professionals’ knowledge, technical expertise, training, and experience. Choi, Hanjoon, Chankon, and Sunhee [35] proposed a four-factor framework, which incorporates physician anxiety, staff concern, ease of the process of care, and tangible things, which show physical, functional, environmental, and administration quality.

In a similar manner, Dagger et al. [33] conducted an in-depth investigation of the quality of healthcare services and developed a scale comprising quality in terms of interpersonal interactions, specialized expertise, ecological sensitivity, and administrative competence, which are all critical. They found that customers’ perceptions of interpersonal quality comprise three primary themes: manner, communication, and relationship, with expertise and outcome being two key factors influencing customers’ judgments of technical quality. The primary aspects underpinning customers’ environmental quality assessments were atmosphere and tangibles. Finally, customers’ evaluations of administrative excellence were divided into three categories: punctuality, operation, and support [33].

Kalaja et al. [36] assessed the quality of services in the Durres public regional hospital in Albania and found no significant difference between the perceptions and expectations of patients. Izadi et al. [37] analyzed the healthcare service using SERVQUAL to measure patients’ expectations and perceptions of performance in Iran and found a significant gap between the two. Pekkaya et al. [38] also used the SERVQUAL model to monitor healthcare quality at a hospital in the UAE and found that the hospital scored highly on the SERVQUAL scale in terms of tangible dimensions. Riono and Ahmadi [39] analyzed the healthcare quality in an Indonesian hospital. They suggested that the results of the study could assist the management in determining policy strategy by prioritizing attributes that have a big gap to improve the quality of its services.

Abbasi-Moghaddam et al. [40] evaluated the SERVQUAL of a clinic at a teaching hospital in Iran. They found that out of eight SERVQUAL dimensions, the patients were satisfied with physician consultation, admission process, and service cost only. Schrimmer et al. [41] discussed the development of a healthcare quality competency framework depicting eight dimensions required for success in healthcare.

2.3. Dimension and Sub-Criteria of Service Quality

Service quality has become an indispensable aspect of the success of an organization. An organization dealing with services is dealing with utmost care as it affects customer satisfaction in a big way. Many researchers have defined service quality; for example, Vargo and Lusch [42] define it as the use of specialized competencies (knowledge and skills), through actions, procedures, and performances, for the benefit of another entity or the entity itself, while Edvardsson et al. [43] define service as “connected activities and interactions that solve customer problems.” In both definitions, a service must have a beneficial consequence (benefits or solutions). In other words, services are exchanges between workers and consumers (service encounters or moments of truth) in which the favorable outcome is recognized as value-in-use. The seven dimensions of healthcare service quality are studied along with sub-criteria.

Table 1. Healthcare service quality evaluation criterion and criteria group.

Quality of Service Dimension	Criterion	Definition
Tangibles	Building layout	Conveniently located within the hospital, in addition to having an aesthetic appeal
	Equipment	Modern equipment
	Hygiene	Maintaining the cleanliness of both the facility and its staff
	Appearance	Cleanliness of the hospital
	Space	Freedom of movement allowed for patients and visitors inside the facility
Responsiveness	Timeliness	Completion of all operations as well as on-time delivery of the service promised
	Completeness	The ability of the medical center to deliver a diverse selection of services
	Willingness	Providing patients with willing assistance when required and actively listening to patients
	Accessibility	Easy access to hospital patient information
	Promptness	Providing patients with voluntary assistance
Reliability	Accuracy	Delivering services at the agreed-upon time and in the manner promised.
	Expertise	Authority of staff members ensuring dependability
	Image	Creating a positive image for the general population.
	Skills	Doctors’ knowledge and expertise
	Knowledge	Doctors and nurses addressing patients’ inquiries professionally.
Assurance	Effective	The hospital is equipped to handle the patients’ medical issues efficiently.
	Guarantee	The accomplishment of successful treatment
	Courtesy	The helpfulness of the employees, in addition to their capacity to inspire people to feel trust and confidence in themselves
	Compensation	Providing patients with some kind of assurance if something goes wrong.
Empathy	Helpful	Understanding patients’ specific needs
	Manner	Individualized care delivered in a pleasant manner
	Concern	Giving individual attention
	Understanding	Understanding needs and requirements
	Communication	Information shared between medical staff and patients, the degree of interaction between the two groups, and the degree of communication in both directions
Constancy	Skill	Staff ability and performance are being evaluated.
	Honesty	The credibility of the service provider
	Experience	Experience comes about gradually over time
	Innovation	Increasing hospital staff and services through training and new technology
Security	Confidentiality	Protection of the patient’s personal information
	Personal safety	Personal safety during patient service participation
	Hospital’s infection safety	Protection against infectious diseases

presents the seven dimensions of service quality along with the sub-criterion of each dimension considered for the present research with its definitions.

3. Research Design

According to research, tangibles, responsiveness, reliability, assurance, empathy and constancy, and security are used to evaluate healthcare service quality. These can include physical facilities and equipment, the usability of the hospital, and hygiene [44]. Lee and Yom [45] considered the design or layout of a hospital to be tangible, so they included it in the definition. Hospitals need to be easy for patients to get to. In addition to this, patients should know how to read the signs and symbols used in medical settings to feel at ease. Furthermore, the hospital also needs the right equipment to do a good job; this includes bed frames, surgery tools, medicines, etc.

One of the most important aspects of service quality is hygiene, in particular, how clean the people and the hospital are. Since hospitals are concerned with people’s health, they are considered a symbol of hygiene. To prevent the growth of diseases, surgical equipment, patients’ rooms, and the surrounding environment should be free of bacteria.

Responsiveness is the consistent eagerness to serve patients and provide timely, correct service. It involves timeliness [33], the ability to offer, and the capacity to deliver, operations and the promised service on time. Additionally, timeliness includes how simple it is to schedule medical appointments, the length of time the patient must wait to be seen, how simple it is to reschedule appointments, and how long the office is open. Hospitals must be able to provide immediate aid to anyone in need, regardless of their ability to make an appointment in advance. Completeness is an important sub-dimension for delivering quality service. Hospitals must be able to provide all types of treatment, as the client will be dissatisfied if their disease cannot be treated in the hospital to which medical professionals have sent them. In conclusion, the definition of responsiveness incorporates willingness [45] as an attribute. It implies that personnel are willing to aid patients whenever necessary, listen to their problems, and devise solutions based on the demands of the clients they serve.

Reliability is the capacity to deliver the promised service consistently and precisely. Accuracy relates to delivering information about a service clearly and concisely, showing that the service provider should be concerned with human health. This includes information provided by the hospital, such as disease diagnosis and surgical expenses. Image and skill add to the hospital’s trustworthiness. The more positive the image presented by the hospital, the more credible it will be. When a service provider is skilled, they can meet strict requirements [33]. The specialization of doctors, nurses, and other medical personnel is essential if patients are to have confidence in a hospital’s services.

The assurance dimension describes the employees’ expertise, kindness, and ability to inspire trust and confidence in others. Since patients feel psychologically dependent on service providers, the employees’ politeness is crucial for the patients’ confidence [32]. Protecting all types of consumer data, including patient information, is crucial for establishing trust. Aspects of assurance include how an organization compensates for its patients’ issues. In the event of a problem, patients can be reassured by compensatory free services in the future and an apology.

Moreover, a reasonable cost of therapy for patients appears to be needed. Patients prefer the entire cost of services to be provided ahead of treatment rather than having additional fees presented later; otherwise, hospitals risk losing patients.

In the context of healthcare service excellence, empathy demonstrates compassion and understanding for patients. Caring is defined by customized customer service, attention to patients, and the ability to detect and address patients’ needs. In a service setting, the behavior and attitude of staff are just as important as their compassion. One of the most talked-about things is how a service provider (doctor, nurse, secretary, etc.) and a patient get along. Examples are, “The personnel are helpful” and “They are sympathetic and caring.” Communication is essential for developing empathy. This includes the flow of information between professionals and patients, as well as the level of interaction and two-way communication.

Constancy includes knowledge, technical expertise, education, and experience. A person’s ability and competence in their field of work, as well as their ability and competency in their area of work, constitute their skill [46]. Patients place a premium on accurate initial disease diagnosis and treatment. Experience is a collection of step-by-step occurrences which enables hospital workers to make decisions regarding patients’ circumstances. In judging innovation, the level of professionalism is also taken into account. The performance of hospital staff should be enhanced through training, and the performance of hospital services should be enhanced through new technologies.

In conclusion, security can be defined as the state of being free from any kind of danger, risk, or uncertainty during the time spent engaging in the process of delivering patient service. This safety is maintained on a personal level. When a patient gives information to the hospital, it is the duty of the hospital to ensure the patient’s right to privacy [32]. It is essential to ensure the safety of all kinds of customer data, such as patient records, to create customer confidence. As can be seen in Table 1, the considerations that form the basis of our criteria and qualities for assessing the level of quality provided by the healthcare services are as follows.

3.1. Methodology

Even within the healthcare industry, service quality can be challenging to maintain. It involves multiple criteria and unclear, qualitative features that are hard to measure. The service quality literature describes qualitative and quantitative methodologies, with models such as statistical analysis and decision theory. The difficulty in assessing service quality is exacerbated by the ambiguity of novel technologies and the scarcity of professionals. Due to the intangible and diverse criteria structure, a powerful approach that can handle ambiguity should be used. MCDM is a popular and influential approach for analyzing service quality performance choices, which helps decision-makers face contradicting assessments [47]. The AHP is a helpful tool for making decisions in various contexts, including selection, ranking, prioritization, allocation of resources, benchmarking, and process improvement. The latter is concerned with the multifaceted aspects of quality and quality development. The analytic hierarchy process, or AHP, was initially developed by Saaty [48]. It is a quantitative tool that helps in the framework of a complex maldistributed problem and provides a goal methodology for choosing between a set of attributes to find the best combination for tackling that problem and involves a series of steps, as below [49].

First, the overall importance of the traits must be established, which can be accomplished by utilizing expert opinion or through an in-depth analysis of matched comparisons [50].

Table 2. Nine-point scale for AHP analysis.

Intensity	(1)	(3)	(4)	(7)	(9)	(2,4,6,8)
Linguistic	Equal	Moderate	Strong	Demonstrated	Extreme	Intermediate-Value

shows Saaty’s ratio scale This scale represents a “one-to-one” mapping between linguistic choices available to decision makers (DMs) and discrete numbers representing the priority or weight of the previous linguistic choice (s) [50]. Then, different weights are assigned to each attribute with the use of an algorithm. The alternative approaches to each attribute’s solution are analyzed similarly, and a single score is created for all of the possible solutions. Finally, one might rank and arrange the many potential solution options based on their final score and select the best option. In the present study, a panel of six experts (two doctors, two nurses and two top administrators from each of the three hospitals) developed the model, as shown in Figure 1.

There are four basic steps in AHP methodology, as shown in Figure 2 [49].

To solve decision problems, the AHP methodology can be summarized with the help of the following equation:

1. First, we build pairwise comparisons, presented by questionnaires with the expert’s subjective perception having a set of n attributes denoted by $({\widetilde{\tilde{𝒶}}}_1$,${\widetilde{\tilde{𝒶}}}_1$,$\dots .,{\widetilde{\tilde{𝒶}}}_m$) according to their relative importance weights denoted by (${\widetilde{\tilde{𝓌}}}_1$,${\widetilde{\tilde{𝓌}}}_2$,…..,${\widetilde{\tilde{𝓌}}}_m$)

$$\tilde{A}=\left(\begin{array}{ccc}{\widetilde{\tilde{𝒶}}}_{11}& \cdots & {\widetilde{\tilde{𝒶}}}_{1m}\\ ⋮& \ddots & ⋮\\ {\widetilde{\tilde{𝒶}}}_{m1}& \cdots & {\widetilde{\tilde{𝒶}}}_{mm}\end{array}\right);\mathrm{m}\to \mathrm{the} \mathrm{no}. \mathrm{of} \mathrm{considered} \mathrm{evaluation} \mathrm{criteria}$$

(1)

($\tilde{A}{}_{ij}$) where i,j = 1,2,3….m;

($\tilde{A}{}_{ij})$ = 1 for all i = j;

($\tilde{A}{}_{ij}=\frac{1}{\tilde{A}{}_{ij}}$) for i ≠ j (the positive-reciprocal of the matrix elements);

where $\tilde{A}$ →a real matrix of dimension (m × m);

and the diagonal element value in the above matrix $(\tilde{A}$ is equal to 1. (${\tilde{A}}_{ij}$) = 1; i = j).

Founded on the three conditions listed below, the importance of one criterion, i.e., ((equal, less and more) importance) over the other criteria can be defined as:

Condition 1—$({\widetilde{\tilde{𝒶}}}_{ij}>1)$ denotes that the ith criterion is relatively more important than the jth criterion.

Condition 2—$({\widetilde{\tilde{𝒶}}}_{ij}<1)$ denotes that the ith criterion is relatively less important than the jth criterion.

Condition 3—$\left({\widetilde{\tilde{𝒶}}}_{ij}=1\right)$ denotes that both criteria hold relatively equal importance.

2. For the normalization of the matrix ($\tilde{A}$), find the ‘operator equation’;

$$\widetilde{\tilde{𝓌}}={\sum }_{j=1}^n{\widetilde{\tilde{𝒶}}}_{ij};$$

(2)

The next step, after completion of the formation of pairwise comparison matrices, is the normalization process of the matrix by using the operator equation (Equation (2)).

$$\begin{array}{ll}\frac{\tilde{A}}{\widetilde{\tilde{𝓌}}}={\sum }_{j=1}^n{\widetilde{\tilde{𝒶}}}_{ij}·{\widetilde{\tilde{𝓌}}}_j^{-1}& =\left(\begin{array}{ccc}{a}_{11}& \cdots & a_{1m}\\ ⋮& \ddots & ⋮\\ a_{m1}& \cdots & a_{mm}\end{array}\right)·\left[\frac{1}{{\widetilde{\tilde{𝓌}}}_1},\frac{1}{{\widetilde{\tilde{𝓌}}}_2},\dots \dots \dots .\frac{1}{{\widetilde{\tilde{𝓌}}}_n}\right];\\ & =\left(\begin{array}{ccc}\frac{a_{11}}{{\widetilde{\tilde{𝓌}}}_1}& \cdots & \frac{a_{1m}}{{\widetilde{\tilde{𝓌}}}_n}\\ ⋮& \ddots & ⋮\\ \frac{a_{m1}}{{\widetilde{\tilde{𝓌}}}_1}& \cdots & \frac{a_{mm}}{{\widetilde{\tilde{𝓌}}}_n}\end{array}\right)\end{array}$$

(3)

We find the normalized principle eigenvector using Equation (4):

$$\begin{array}{ll}{\widetilde{\tilde{\mathcal{W}}}}_j=\frac{1}{n}\sum _{j=1}^n\frac{a_{ij}}{{\widetilde{\tilde{𝓌}}}_j}& =\left(\begin{array}{ccc}\frac{a_{11}}{{\widetilde{\tilde{𝓌}}}_1}& \cdots & \frac{a_{1m}}{{\widetilde{\tilde{𝓌}}}_n}\\ ⋮& \ddots & ⋮\\ \frac{a_{m1}}{{\widetilde{\tilde{𝓌}}}_1}& \cdots & \frac{a_{mm}}{{\widetilde{\tilde{𝓌}}}_n}\end{array}\right)·\left[\begin{array}{c}1\\ 1\\ ⋮\\ 1\end{array}\right]·n^{-1};\\ & =\left[\begin{array}{c}\frac{1}{n} \sum _{j=1}^n\frac{a_{1j}}{{\widetilde{\tilde{𝓌}}}_j} \\ ⋮\\ \frac{1}{n} \sum _{j=1}^n\frac{a_{nj}}{{\widetilde{\tilde{𝓌}}}_j} \end{array}\right]\end{array}$$

(4)

Using Equation (5), we find the final weight of the alternatives:

$$\widetilde{\tilde{\mathcal{W}}}=\mathrm{MMULT}(Arra{y}_i,Arra{y}_j).$$

(5)

In order to evaluate the level of agreement between the panel of experts, the kappa coefficient is used. The computation is based on the difference between the actual amount of agreement and the expected amount of agreement, anticipated to be there only by coincidence. A kappa value of 0 indicates that there is a poor agreement between the methods, and a value of 1 indicates an almost perfect agreement. For the present result, the value of kappa is 0.83, which is close to 1. Hence, there is a close agreement in the survey.

3.2. Model Development

As indicated in the preceding section, comprehensive literature research was conducted to determine service quality dimensions and sub-criteria. Prior to gathering any data, a conceptual model for a decision problem must be developed. Hence, model development uses 7 dimensions and 31 sub-criteria. Three hospitals, Abha Private Hospital (APH), Asir General Hospital (AGH), and Al Haya Hospital (AHH), were chosen based on demand in the Asir region to examine the quality of healthcare services. To conceal their identities, the three hospitals are called Healthcare Services A, Healthcare Services B, and Healthcare Services C, respectively.

An AHP-based questionnaire was created, developed, and administered, with several comparison tables containing the 7 dimensions and 31 sub-criteria of service quality. A consensus was reached by brainstorming and formal discussion on critical decision-making. The following are the three options being assessed to find the best healthcare services:

Abha Private Hospital (APH)

Asir General Hospital (AGH)

Al Haya Hospital (AHH)

The hospital management cares for the cleaning, maintenance and feeding for the comfort of the patient. There are 6 sections in the hospital: (1) the men’s section, (2) the women’s section, (3) children from 1 day old to 15 years, (4) surgery, (5) intensive care for premature babies, and (6) premature infants. The hospital also has facilities such as outpatient clinics, specialized units, service units, radiology, laboratories, physiotherapy, pharmacies and non-medical services. The demand for healthcare is affected by a number of factors, including the following: needs (as perceived by patients), patient preferences, price or cost of use, income, transportation costs, waiting times during service and the quality of care received from the patient point of view.

Figure 3 depicts a step-by-step evaluation of the best healthcare services, demonstrating how the model was created utilizing the AHP approach.

3.3. Prioritization of Dimensions and Sub-Criteria

All seven aspects of service quality were compared to each other in terms of the goal, which was to evaluate the quality of service in healthcare services. Comparing two dimensions shows how important each is to the model’s goal. Various pairwise comparison was made, and each pairwise comparison’s matrix was checked by calculating λ max, the consistency index (CI), and the consistency ratio (CR). It was found that all the tables met the requirement of the consistency check.

The local weight of each dimension was calculated by calculating the overall preferences of seven service quality dimensions: tangibles, responsiveness, reliability, assurance, empathy, constancy, and security. The five-sub criteria for tangibles were building layout, equipment, hygiene, appearance, and space. The five sub-criteria considered for responsiveness were timeliness, completeness, willingness, accessibility, and promptness. The five sub-criteria considered for reliability were accuracy, expertise, image, skills, and knowledge. The four sub-criteria considered for assurance were effectiveness, guarantee, courtesy, and compensation. The five sub-criteria considered for empathy were helpfulness, manner, concern, understanding, and communication. Finally, the four sub-criteria considered for constancy were skill, honesty, experience, and innovation.

The three sub-criteria considered for security were confidentiality, personal safety, and hospital infection safety. As with the local dimension weight, the local weights of all sub-criteria were computed. The global weight was computed by taking the product of respective dimensions with their sub-criteria. The pairwise comparison matrices for the seven dimensions are shown in

Table 3. Pairwise Comparison of Service Quality Dimensions.

Dimensions	Tangibles	Responsiveness	Reliability	Assurance	Empathy	Constancy	Security	E-Vector
Tangibles	1	6	1/2	1	2	3	1	0.2166
Responsiveness	1/6	1	1/2	1	1	2	1	0.1019
Reliability	2	2	1	2	2	3	2	0.2449
Assurance	1	1	1/2	1	1	2	1/2	0.1153
Empathy	1/2	1	1/2	1	1	2	1/2	0.1007
Constancy	1/3	1/2	1/3	1/2½	1/2	1	1/3	0.0574
Security	1	1	1/2	2	2	3	1	0.1633
λ max = 7.4; CR = 0.049; CI = 0.066

, and the pairwise comparisons of sub-criteria are shown in

Table 4. Pairwise Comparison of Five Sub-Criteria/Factors for Tangible Criteria/Dimension.

Sub-Criteria/Factors	Building Layout	Equipment	Hygiene	Appearance	Space	E-Vector
Building layout	1	1/2	1/3	2	3	0.1503
Equipment	2	1	1/2	3	4	0.2475
Hygiene	3	2	1	6	8	0.4650
Appearance	1/2	1/3	1/6	1	2	0.0845
Space	1/3	1/4	1/8	1/2	1	0.0527
λ max = 5.03; CR = 0.006; CI = 0.007

,

Table 5. Pairwise Comparison of Three Sub-Criteria/Factors for Responsiveness Criteria/Dimension.

Sub-Criteria/Factors	Timeliness	Completeness	Willingness	Accessibility	Promptness	E-Vector
Timeliness	1	9	1	1/2	1/3	0.1598
Completeness	1/9	1	1/9	1/9	1/9	0.0260
Willingness	1	9	1	1/2	1/2	0.1720
Accessibility	2	9	2	1	1/2	0.2618
Promptness	3	9	2	2	1	0.3804
λ max = 5.15; CR = 0.034; CI = 0.039

,

Table 6. Pairwise Comparison of Three Sub-Criteria/Factors for Reliability Criteria/Dimension.

Sub-Criteria/Factors	Accuracy	Expertise	Image	Skills	Knowledge	E-Vector
Accuracy	1	1/3	1/2	1/2	1/3	0.0865
Expertise	3	1	2	2	2	0.3404
Image	2	1/2	1	2	1/2	0.1801
Skills	2	1/2	1/2	1	1/2	0.1360
Knowledge	3	1/2	2	2	1	0.2571
λ max = 5.13; CR = 0.028; CI = 0.032

,

Table 7. Pairwise Comparison of Four Sub-Criteria/Factors for Assurance Criteria/Dimension.

Sub-Criteria/Factors	Effective	Guarantee	Courtesy	Compensation	E-Vector
Effective	1	1/9	1/2	1/9	0.0414
Guarantee	9	1	9	2	0.5272
Courtesy	2	1/9	1	1/9	0.0586
Compensation	9	1/2	9	1	0.3728
λ max = 4.12; CR = 0.044; CI = 0.04

,

Table 8. Pairwise Comparison of four Sub-Criteria/Factors for Empathy Criteria/Dimension.

Sub-Criteria/Factors	Helpful	Manner	Concern	Understanding	Communication	E-Vector
Helpful	1	7	1/2	3	1/2	0.2215
Manner	1/7	1	1/5	1/4	1/6	0.0410
Concern	2	5	1	2	2	0.3380
Understanding	1/3	4	1/2	1	1/3	0.1170
Communication	2	6	1/2	3	1	0.2824
λ max = 5.28; CR = 0.06; CI = 0.07

,

Table 9. Pairwise Comparison of three Sub-Criteria/Factors for Constancy Criteria/Dimension.

Sub-Criteria/Factors	Skill	Honesty	Experience	Innovation	E-Vector
Skill	1	1/2	2	2	0.2762
Honesty	2	1	2	2	0.3905
Experience	1/2	1/2	1	2	0.1953
Innovation	1/2	1/2	1/2	1	0.1381
λ max = 4.12; CR = 0.04; CI = 0.04

,

Table 10. Pairwise Comparison of three Sub-Criteria/Factors for Security Criteria/Dimension.

Sub-Criteria/Factors	Confidentiality	Personal Safety	Hospital’s Infection-Safety	E-Vectors
Confidentiality	1	3	1/3	0.2499
Personal safety	1/3	1	1/6	0.0953
Hospital’s infection-safety	3	6	1	0.6548
λ max = 3.01; CR = 0.019; CI = 0.009

and

Table 11. Pairwise Comparison of three Alternatives with respect to sub-criteria of Confidentiality to enhance Security Criteria/Dimension.

Security Sub Criteria	APH	AGH	AHH	E-Vectors
APH	1	4	1/2	0.33
AGH	1/4	1	1/5	0.10
AHH	2	5	1	0.57
λ max = 3.02; CR = 0.025, CI = 0.012

. The pairwise comparison of three alternatives with respect to three sub-criteria to enhance security criteria/dimensions is shown in Table 11,

Table 12. Pairwise Comparison of three Alternatives with respect to sub-criteria of Personal safety to enhance Security Criteria/Dimension.

Security Sub Criteria	APH	AGH	AHH	E-Vectors
APH	1	5	2	0.56
AGH	1/5	1	1/4	0.09
AHH	1/2	4	1	0.35
λ max = 3.02; CR = 0.025, CI = 0.012

and

Table 13. Pairwise Comparison of three Alternatives with respect to sub-criteria of Hospital’s infection safety to enhance Security Criteria/Dimension.

Security Sub Criteria	APH	AGH	AHH	E-Vectors
APH	1	4	2	0.56
AGH	1/4	1	1/3	0.12
AHH	1/2	3	1	0.32
λ max = 3.01; CR = 0.019, CI = 0.009

. The other results were computed similarly and are incorporated in

Table 14. Composite Priority Weights for Criteria and Sub-criteria to Establish Best Healthcare Services.

Dimension	Local wt.	Sub-Criteria	Local Wt.	Global Weight	APH Lw	AGH Lw	AHH Lw	APH Gw	AGH Gw	AHH Gw
Tangibles	0.21656	Building layout	0.1503	0.032549	0.59363	0.157053	0.249317	0.019322044	0.005111913	0.008115011
		Equipment	0.2475	0.053599	0.539613	0.163425	0.296962	0.028922501	0.008759351	0.015916747
		Hygiene	0.465	0.1007	0.625005	0.136505	0.238491	0.062938254	0.013746108	0.024016139
		Appearance	0.0845	0.018299	0.238491	0.136505	0.625005	0.004364223	0.002497949	0.011437166
		Space	0.0527	0.011413	0.097737	0.186961	0.715302	0.001115444	0.002133732	0.008163536
Responsiveness	0.101941	Timeliness	0.1598	0.01629	0.31082	0.195798	0.493382	0.005063311	0.003189583	0.008037278
		Completeness	0.026	0.00265	0.31082	0.195798	0.493382	0.000823818	0.000518956	0.001307692
		Willingness	0.172	0.017534	0.660759	0.131109	0.208133	0.011585651	0.002298846	0.003649373
		Accessibility	0.2618	0.026688	0.31082	0.195798	0.493382	0.008295212	0.005225487	0.013167455
		Promptness	0.3804	0.038778	0.333072	0.09739	0.569539	0.012915985	0.003776624	0.022085786
Reliability	0.244906	Accuracy	0.0865	0.021184	0.493382	0.195798	0.31082	0.010451986	0.004147857	0.006584526
		Expertise	0.3404	0.083366	0.31082	0.195798	0.493382	0.025911821	0.016322897	0.041131285
		Image	0.1801	0.044108	0.539613	0.296962	0.163425	0.023801018	0.013098272	0.00720828
		Skills	0.136	0.033307	0.571429	0.142857	0.285714	0.019032709	0.004758169	0.009516338
		Knowledge	0.2571	0.062965	0.184003	0.231822	0.584175	0.01158581	0.014596749	0.036782773
Assurance	0.115299	Effectiveness	0.0414	0.004773	0.654798	0.095343	0.249859	0.003125599	0.000455108	0.001192672
		Guarantee	0.5272	0.060786	0.625005	0.136505	0.238491	0.037991324	0.008297543	0.014496826
		Courtesy	0.0586	0.006757	0.296962	0.539613	0.163425	0.00200643	0.003645907	0.001104185
		Compensation	0.3728	0.042983	0.527828	0.139646	0.332527	0.022687878	0.006002469	0.014293163
Empathy	0.100666	Helpfulness	0.2215	0.022298	0.648329	0.12202	0.229651	0.014456128	0.002720743	0.005120648
		Manner	0.041	0.004127	0.527828	0.139646	0.332527	0.002178508	0.000576362	0.001372441
		Concern	0.338	0.034025	0.332527	0.139646	0.527828	0.011314267	0.00475147	0.017959405
		Understanding	0.117	0.011778	0.44343	0.1692	0.38737	0.005222684	0.001992824	0.004562414
		Communication	0.2824	0.028428	0.539613	0.163425	0.296962	0.015340161	0.004645859	0.008442059
Dimension	local wt.	Sub-Criteria	Local Wt.	Global Weight	APH Lw	AGH Lw	AHH Lw	APH Gw	AGH Gw	AHH Gw
Constancy	0.057368	Skill	0.2762	0.015845	0.163425	0.539613	0.296962	0.002589476	0.00855019	0.004705375
		Honesty	0.3905	0.022402	0.238491	0.625005	0.136505	0.005342724	0.01400149	0.003058013
		Experience	0.1953	0.011204	0.296962	0.539613	0.163425	0.003327153	0.006045808	0.001831009
		Innovation	0.1381	0.007923	0.587629	0.088984	0.323386	0.004655503	0.000704978	0.002562032
Security	0.163261	Confidentiality	0.249859	0.040792	0.333072	0.09739	0.569539	0.01358675	0.003972755	0.023232766
		Personal safety	0.095343	0.015566	0.569539	0.09739	0.333072	0.008865326	0.001515953	0.00518453
		Hospital’s infection safety	0.654798	0.106903	0.558424	0.121957	0.319619	0.059697188	0.013037566	0.034168222
								0.458516886	0.181099519	0.360405144

.

Furthermore, all three options, i.e., Abha Private Hospital (APH), Asir General Hospital (AGH), and Al Haya Hospital (AHH), were compared for each sub-criteria of the seven dimensions of service quality. Then, their results were calculated to assess the healthcare services, and the global weight of all three alternatives was computed by taking the product of the sub-criterion global weight with the local weight of the three alternatives. Finally, the summation of all three alternative global weights was taken. The alternative with a higher summation value is the best, while the one with the most negligible value is considered the worst. The synthesized comparison matrix is shown in Table 14.

The MCDM helps analyze dimensions, main criteria, and sub-criteria critically to facilitate making a decision as to which hospital has the best healthcare system (alternatives). Since the best healthcare system plays a vital role in the selection of a hospital for any health organization, patients can choose based on the facility provided. The selected alternative (hospital) must be in a position to cater to the patient’s needs. Looking to the requirements, AHP-based modeling has been used in the present condition. The AHP has excellent potential to evaluate and rank the dimensions and sub-criteria that are significant decision-making parameters when selecting a hospital. Based on the chosen dimensions and subfactors, the people involved in the health system can run it smoothly and effectively, as it is made easy for those in charge to constantly evaluate, track, and manage the criteria to fit with their strategic goals. Since expensive infrastructure (hardware and software) technologies are required to ensure that the healthcare system works well and is solid, ranking dimensions and sub-criteria can help with planning and managing resources. AHP and ranking, followed by comparison, can be used to determine the correct order of importance for the dimension, sub-criteria, and choice of hospital.

The AHP provides the ranking of dimensions of the healthcare system as reliability > tangibles > security >assurance > responsiveness >empathy >constancy, where ‘>’ indicate preference over another. From the result, it may be concluded that the reliability dimension plays a significant role. In contrast, constancy plays a comparatively less significant role in deciding the preference of the healthcare system, as shown in Figure 4. The prioritization of this service quality dimension helps the organization understand the importance of each dimension so that the manager can use these weights and the importance of dimensions in strategic decision-making. All the sub-criteria of a dimension are compared to the goal to achieve. Thus, 31 sub-criteria of the seven dimensions were calculated, as were the various relationships between these factors. Based on the sub-criteria for tangible dimensions, hygiene > equipment > building layout > appearance > space. From the weightage in Figure 5, it may be concluded that the hygiene sub-criterion plays a significant role. In contrast, space plays a comparatively less significant role in deciding the preference among tangible dimensions. The results of other dimensions’ sub-criteria are shown in Figure 5.

From the sub-criteria global weight, as shown in Figure 6, the sub-criterion hospital infection is a highly influential sub-criterion, while completeness is given the least priority.

From the result of alternative pairwise comparison and global weight, as shown in Figure 7, the AHP provides the ranking of alternatives, i.e., hospital as APH > AHH > AGH. This indicates that the preference for the Abha private hospital is higher, and the Abha government hospital ranks as the lowest healthcare facility to the patient.

4. Discussion

This study took into account the 7 criteria and 31 subcriteria for evaluating the service quality of three hospitals in the Asir region, Saudi Arabia using the AHP technique. The AHP lists the healthcare system’s dimensions in the following order: reliability > tangibles > security > assurance > responsiveness > empathy > constancy. The study’s findings showed that these seven dimensions might be used to assess how much there is a difference in service quality in the hospitals. The study by Zarei et al. [51] done in Iranian private hospitals revealed that the tangible dimension had the greatest average score, and the empathy dimension had the lowest average. This is almost similar to the results of the present study. The Ramez [52] research placed assurance as the lowest and reliability as the top service quality factor, which is somewhat similar to our result. According to Abu Kharmeh [53], responsiveness is the most crucial factor, whereas reliability is the least crucial factor, which contradicts the present study’s findings. An appealing outpatient environment and adequate outpatient services are regarded as one of the most important reasons for patients to visit the hospital, and the physical environment of the hospital plays a significant role in increasing the service quality. The tangible factor, which is concerned with the physical infrastructure of treatment in private hospitals in Jordan, Saudi Arabia, Iran, and Malaysia, is where expectations and perceptions were shown to be the greatest in previous studies [53,54]. In contrast to the findings of our study, Marzban et al.’s [55] investigation showed that the assurance component was regarded as the most important dimension with the highest ratings. This study may be expanded to examine the relationship between overall satisfaction and aspects of service quality. Future research should take into account the perspectives of both service providers and patients. To better comprehend the complexity of service quality in future studies, it is vital to perform qualitative research with quantitative methods. It should be remembered that patients’ opinions and expectations for service quality cannot be captured by one instrument.

5. Conclusions

The purpose of this research was to develop a model that could be utilized to evaluate the quality of services in the healthcare field and to evaluate the effectiveness of several pioneering Asir hospitals via the application of the AHP method. As a consequence, information from the practices of five highly qualified medical professionals in Asir was compiled and incorporated into the model to assess the relative effectiveness of various choices in terms of patient care (hospitals). According to the findings, hospitals should concentrate the most on reliability, tangibles, and security and the least on consistency. In addition, according to the sub-criteria, the hospitals’ primary priority should be infection prevention and hygiene, with completeness receiving the least attention. Based on a survey of dimensions and their sub-criteria, the best hospital is Abha Private Hospital, followed by AHH, and then Asir General Hospital.

The findings of this study provide management with valuable information on the factors that demonstrate how satisfied patients are with the standard of treatment they receive. By addressing the specific limitations, they face, hospitals have the potential to boost the quality of their services and provide patients and customers with an even higher level of satisfaction. AHP was utilized to evaluate the proposed model; however, other methods can be employed to determine the quality of healthcare service. These approaches might be used to find a solution to the service quality and performance problem in further studies, and the findings could then be compared to one another.

6. Recommendation for Future Research

In general, we advise using the AHP to support the evaluation of healthcare technology when faced with complex decision-making issues, when it is necessary to share information among experts or between clinicians and patients, when there is a shortage of knowledgeable respondents, or when it is necessary to improve decision-making rather than merely explaining decision outcomes. Its primary benefit is that it permits talks amongst panelists and, as a result, information sharing. AHP can help health economic analyses of novel medical technologies, to be more precise. AHP may play a role in (1) prioritizing various patient-related outcomes in clinical trials and (2) assessing the net benefit of healthcare treatments, even though it has largely been established to help management decision-making. It is feasible to establish weights for individual and for groups of patient-relevant endpoints by creating a hierarchical structure of the outcome measures taken into account. This could be done before the benefits analysis, ideally with plenty of informed patients. AHP has not been used frequently for this specific purpose; thus, additional study is needed to determine whether it can be utilized in surveys and how it compares to utility-based patient-reported outcome measures.