A Kansei engineering-based decision-making method for offline medical service quality evaluation with multidimensional attributes

IF 6.2 2区经济学 Q1 ECONOMICS

Socio-economic Planning Sciences Pub Date : 2024-11-01 DOI:10.1016/j.seps.2024.102100

Yujia Liu , Xinru Ren , Feixia Ji , Changyong Liang , Jian Wu

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引用次数: 0

Abstract

The evaluation of doctors’ offline medical service quality plays a vital role in evaluating hospital performance. There are two challenges that need to be addressed: (1) Currently, telephone follow-up and questionnaire surveys are the main methods for evaluating the quality of offline (mainly outpatient and inpatient) medical services in hospitals. However, these methods suffer from drawbacks such as low efficiency and resource consumption. (2) There are certain limitations to determining attribute dimensions and weighting patient evaluation attributes based solely on word frequency. To this end, this study proposes a Kansei engineering-based decision-making method for offline medical service quality evaluation with multidimensional attributes. First, this study constructs a medical Kansei lexicon based on speed and cosine similarity. Second, a concept of Kansei utility values is been defined to represent attribute values in medical service quality evaluation. Additionally, this study builds upon the Kano model to obtain the Kano classification of each attribute. On that basis, a novel approach to obtaining the implicit importance of the attributes is proposed. Thus, the weight vector of the attributes can be calculated as the combination of explicit and implicit importance. Finally, the evaluation result is obtained by using the multiattribute decision-making method. The effectiveness of the proposed method is verified through an analysis of online reviews from Haodf.com. The case study reveals that offline patients consider medical ethics and communication skills as the ”must-be” dimension of attributes, medical competence as a one-dimensional attribute, and medical advice and prescriptions as the attractive dimension of attributes. A comparative analysis with the traditional method is conducted to demonstrate the importance of dimensional analysis for offline medical service quality evaluation. The main contributions of this study include the following: (1) A medical Kansei lexicon is constructed based on Kansei engineering, and (2) a novel decision-making framework for medical service evaluation based on both appearance and implicit importance is constructed.

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基于 Kansei 工程的多维属性离线医疗服务质量评价决策方法

医生线下医疗服务质量评价在医院绩效评价中起着至关重要的作用。需要解决的难题有两个：（1）目前，电话随访和问卷调查是评价医院线下（主要是门诊和住院）医疗服务质量的主要方法。然而，这些方法存在效率低、资源消耗大等缺点。(2) 仅根据词频确定属性维度和患者评价属性权重存在一定的局限性。为此，本研究提出了一种基于康熙工程学的多维属性离线医疗服务质量评价决策方法。首先，本研究构建了基于速度和余弦相似度的医疗 Kansei 词库。其次，定义了 Kansei 实用价值的概念，以表示医疗服务质量评价中的属性值。此外，本研究以 Kano 模型为基础，获得了每个属性的 Kano 分类。在此基础上，提出了一种获取属性隐含重要性的新方法。因此，属性的权重向量可以计算为显性和隐性重要性的组合。最后，使用多属性决策方法得出评估结果。通过分析 Haodf.com 上的在线评论，验证了所提方法的有效性。案例研究显示，线下患者认为医德和沟通技巧是 "必须的 "属性维度，医疗能力是一维属性，而医疗建议和处方则是有吸引力的属性维度。通过与传统方法的对比分析，证明了维度分析法在线下医疗服务质量评价中的重要性。本研究的主要贡献包括以下几点：(1) 基于 Kansei 工程学构建了医疗 Kansei 词库；(2) 构建了基于外观和隐含重要性的新型医疗服务评价决策框架。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Socio-economic Planning Sciences OPERATIONS RESEARCH & MANAGEMENT SCIENCE-

CiteScore

9.40

自引率

13.10%

发文量

294

审稿时长

58 days

期刊介绍： Studies directed toward the more effective utilization of existing resources, e.g. mathematical programming models of health care delivery systems with relevance to more effective program design; systems analysis of fire outbreaks and its relevance to the location of fire stations; statistical analysis of the efficiency of a developing country economy or industry. Studies relating to the interaction of various segments of society and technology, e.g. the effects of government health policies on the utilization and design of hospital facilities; the relationship between housing density and the demands on public transportation or other service facilities: patterns and implications of urban development and air or water pollution. Studies devoted to the anticipations of and response to future needs for social, health and other human services, e.g. the relationship between industrial growth and the development of educational resources in affected areas; investigation of future demands for material and child health resources in a developing country; design of effective recycling in an urban setting.