Hospital Service Quality Evaluation Research Articles

Development of an Intuitive GUI-Based Fuzzy Multi-Criteria Decision Model for Comprehensive Hospital Service Quality Evaluation and Indexing

Recently, hospital care and other services have become increasingly important for patient satisfaction. Better hospital care and assistance improve patients’ medical conditions, management trust, and financial success. In this regard, monitoring and measuring hospital service quality is necessary to improve patient satisfaction and wellness. However, the evaluation of healthcare service quality is a complex and critical task due to its intangible nature. Existing methodologies often struggle to effectively incorporate multiple criteria and address uncertainties inherent in healthcare evaluations. To address these challenges, this research work seeks to develop a comprehensive and robust approach for evaluating hospital service quality to improve decision making and resource allocation for service enhancement. This study aims to evaluate multi-faceted healthcare service quality by combining many criteria and uncertainties into a single index. The model is constructed methodically utilizing fuzzy logic and decision modeling. A dataset collected from diverse healthcare facilities covering various medical specialties and regions is employed to validate and refine the model. Numerous criteria, factors, and dimensions are examined and embedded into the development of the model. Fuzzy logic is used to capture and manage healthcare evaluations’ inherent vagueness and imprecision, yielding more accurate and comprehensive outcomes. The model’s outcome is the hospital service quality fuzzy index (HSQFI), an easy-to-understand single performance measure. A graphical user interface (GUI) is developed for collecting data, and then it shows the results in the form of barriers and recommendations. Based on the findings, recommendations in terms of barriers (service criteria) to enhance the hospital’s service quality have been made. This approach can be a tool for managers or other stakeholders to quickly realize the success of their service plans and pinpoint areas that may need improvement in the future.

An extended best-worst multi-criteria decision-making method by belief functions and its applications in hospital service evaluation

In the healthcare industry, hospital service quality assessment is an important work, which can not only promote medical service providers to improve the status quo of the industry, but also ensure patients to enjoy better service. Since hospital service evaluation involves a great many qualitative and quantitative factors, it is a complex multi-criteria decision-making (MCDM) issue. In the real-life MCDM problems, the ambiguity of information expression often occurs because of the lack of complete knowledge, and the vagueness of decision makers in qualitative judgment is quite common, so the crisp values of criteria may be inadequate to deal with such complex situations. To achieve the evaluation of hospital service quality under uncertain environment, in this paper, the traditional best-worst method (BWM) is extended based on belief function theory (BFT) that has powerful ability of uncertain expression and reasoning. This paper describes in detail the implementation process of evidential BWM and the proposed hospital service quality evaluation framework based on it. A case study is presented to evaluate hospital service quality based on the constructed model. The results manifest the effectiveness of the proposed method and offer an insightful reference for the evaluation of healthcare industry.

Hospital service quality evaluation: an integrated model based on Pythagorean fuzzy AHP and fuzzy TOPSIS

Providing better hospital service quality is one of the major concerns of healthcare industry in the world. Since health services in Turkey are provided in a very competitive environment, for making a better choice, the services delivered by the public and private hospitals should be evaluated according to the viewpoint of stakeholders in terms of satisfaction. In this study, a model proposal is presented based on the concept of Pythagorean fuzzy analytic hierarchy process and Pythagorean fuzzy technique for order preference by similarity to ideal solution method to provide an accurate decision-making process for evaluating the hospital service quality. We study under fuzzy environment to reduce uncertainty and vagueness, and use linguistic variables parameterized by Pythagorean fuzzy numbers. The proposed approach is separated from others with the integration of the methods in a way providing a systematic fuzzy decision-making process. A case study including 32 service quality criteria and two public and one private hospitals in Turkey assessed by 32 evaluators by medical staff, hospital executives, auxiliaries, and patients is performed to demonstrate the applicability and validity of the proposed approach. On conclusion, integrated model produces reliable and suggestive outcomes better representing the vagueness of decision-making process.

Hospital service quality evaluation with IVIF-PROMETHEE and a case study

Measuring satisfaction of patients and understanding their perceptions are important for the hospital management to respond to customers' growing demands for acceptable quality of healthcare services. The main purpose of this paper is to present a methodology that can be used in the healthcare service quality evaluation. IVIF-PROMETHEE method is applied for service quality evaluation based on patients' views in a real-life case study of a public hospital in Istanbul and the results are compared with the results from IVIF-TOPSIS method. Interval Valued Intuitionistic Fuzzy (IVIF) set is considered an appropriate tool because of the complexity and vagueness of the evaluation of healthcare services. The evaluation of the quality level of the healthcare service provides detailed information about the effects of considered criteria as well as creates opportunities in implementing effective procedures to overcome service quality problems via analysing the patients' views. The proposed methodology can be a useful tool for hospital management.

Design of Doctor's Humanistic Care System Based on the Multiple Values Theory

To further improve the scientificity and accuracy of evaluation of hospital service quality, a kind of research method of hospital evaluation system of maximum deviation combination evaluation pattern is proposed herein. Firstly, the index of multi-attribute decision making is described, and on this basis, the combination evaluation model is established in accordance with maximum deviation pattern to obtain the multi-attribute decision-making model. Secondly, the model solving process is designed for proposed multi-attribute decision-making model, and shall be applied to the research of hospital evaluation system. Finally, by evaluating and analyzing the data of a certain hospital from 2002 to 2010, the results have confirmed the effectiveness of proposed algorithm.

The evaluation of hospital service quality by fuzzy MCDM

This study applies the Multiple Criteria Decision Making (MCDM) to evaluate the service quality of some Turkish hospitals. In general the service quality has abstract properties, which mean that using the previously known measurement approach is insufficient. It is for this reason that the fuzzy set theory is adopted as a research template. In Istanbul, Turkey, there are four B class hospitals classed as private hospitals that are covered by the Social Security Institution (SSI) and for which we propose to represent the service performance measurement using triangular fuzzy numbers. In this study, importance weights of performance criteria are found with AHP. Then, the Multiple Criteria Decision Making methods TOPSIS and Yager's min-max approach are applied to find and rank the crisp performance values. In a second step, an aggregation of performance criteria with OWA and Compensatory AND operators are looked at instead of the TOPSIS method and min-max approach. Thereby numerical applications are supplied by the four methods and the obtained results are compared.