大型综合性医院患者满意度指数模型的构建与实证分析
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摘要
随着我国近年来不断加快医疗卫生体制改革步伐，逐步开放医疗服务市场，医疗机构之间的竞争日益激烈。医疗机构要想在激烈的市场竞争中脱颖而出，获得患者者高度认可，步入可持续发展的良性轨道，首先要保证能够提供让患者满意的医疗服务。目前，国内主要采用患者满意度对医院的治疗效果以及医疗服务质量进行衡量，这也是现代医院管理评价的重要标准。开展对患者满意度的研究，对于进一步完善卫生质量管理理论，指导医疗机构有针对性地改进服务，具有重要的理论和现实意义。大型综合性医院作为我国医疗卫生体系主体，承担着区域医疗中心的角色，更应注重患者满意度，以患者需求推动医院发展。
我国患者满意度的研究起步较晚，目前无论是理论还是实践方面都处于探索之中，许多问题亟待解决。2010年，卫生部中日友好医院科研课题《大型综合性医院患者满意度测评指标体系研究》正式立项，希望运用科学的方法，进行大型综合性医院患者满意度量表指标的优化，形成更为科学合理的大型综合性医院患者满意度测评指标体系，创建患者满意度指数模型，研制患者满意度测评信息系统，为医院质量改进措施和服务发展策略提供帮助。本文即是该课题研究成果的反映。
基于这样的研究背景，本文将医院实际工作与理论研究相结合、传统的概率统计理论与近代的灰色理论、模糊数学相结合、现场调查取样与信息技术相结合，在广泛综合国内外满意度研究成果的基础上，进行了大型综合性医院患者满意度指数模型的构建和实证分析，所取得的主要研究成果和结论如下：
1、在对患者满意度初始调查量表及预调查量表反复进行设计、调查、分析、修改的基础上，在全国华北、华中、华东、华南和西南五个地区各选一家在国内很有影响的大型综合性医院进行抽样调查，经探索性因子分析和验证性因子分析构建了多层次的大型综合性医院患者满意度测评指标体系，形成了大型综合性医院患者满意度测评问卷。
2、采用多层线性模型与结构方程模型相结合的方法，进行了多层次大型综合性医院患者满意度指数（LCHPSI）模型的创新。通过实证分析，证实了本文创建的多层次大型综合性医院患者满意度指数（LCHPSI）模型潜变量与观测变量之间的因果关系设置正确，结构模型与实际数据契合。
3、通过对不同阶数大型综合性医院患者满意度指数模型的研究，发现采用二阶模型或一阶模型在本质上并无根本差别、对满意度指数的测定不产生影响，解决了采用不同的层次结构是否会影响到满意度指数测评结果的问题。
4、进行了基于排序求因子权重的患者满意度多层次模糊综合评价的研究，这种直接根据患者统计数据的客观赋权法，使权重系数的分配比较客观，再结合多层次模糊综合评价法，使评判结果更趋真实。通过实证分析，证明效果良好。
5、进行了基于灰色关联求因子权重对病人满意度的多层次模糊综合评价的研究，这种将多个近代数学工具结合使用的方法在一定程度上减少了专家差异所造成的偏差，使患者满意度的测评能取得更好效果。
6、通过实证分析，将基于排序求因子权重对病人满意度的多层次模糊综合评价法和基于灰色关联求因子权重对病人满意度的多层次模糊综合评价法进行了对比，发现这两种方法的综合评价结果基本一致，但基于排序求因子权重的患者满意度多层次模糊综合评价法，在整体满意度得分上略高于基于灰色关联求因子权重的患者满意度多层次模糊综合评价法。
7、基于灰色模糊理论，进行了患者满意度测评信息系统的研制，实现医院患者满意度测评分析自动化。该信息系统适应患者满意度测评信息残缺的不确定状况，通过对部分已知信息来实现对缺省值的较确切描述和认识，客观地进行患者满意度测评。
本文的主要创新点有：
1、采用多层线性模型与结构方程模型相结合的方法，创建了二阶的大型综合性医院患者满意度指数（LCHPSI）模型。这种多层次的患者满意度指数模型，不但可合理地估计单个观测变量对满意度的影响，而且可以在不同层面上进行不同医疗服务领域间患者满意度的比较。
2、通过不同阶次患者满意度指数模型的研究，得出了患者满意度指数模型的阶数对满意度指数的测定不产生影响的结论，为研究人员进行多层次患者满意度指数模型的研究提供了一定的参考。
3、提出了基于排序求因子权重的病人满意度多层次模糊综合评价法，对多层次模型中各级的权重系数的确定进行了创新，从而使权重系数的分配比较客观，评判结果更趋于真实。
4、提出了基于灰色关联求因子权重病人满意度的多层次模糊综合评价法。这种新方法将灰色理论与模糊数学相结合，克服了对样本数量和规律性有一定要求的限制，弥补了传统统计方法的不足，在一定程度上减少了专家差异所造成的偏差。
With the deepening reform of China's medical and health system, gradually openingof medical service market, medical institutions is faced with increasingly intensemarket competition. Medical institutions, especially the Large ComprehensiveHospitals, win the trust of patients in competition and make the hospital constructionstepping into the benign orbit of sustainable development, only when they ensuredsatisfied medical services provision to patients. At present, in the modern hospitalmanagement evaluation index system, Patient Satisfaction is key criteria of appraisingthe treatment impact and medical service quality. Carring out the study on PatientSatisfaction is of great theoretical and realistic significance to improving healthquality management theory and guiding medical institution to improve targetedservices. As the main body in medical and health system and assumed to be regionalmedical centers, Large Comprehensive Hospitals should pay more attention to PatientSatisfaction and promote hospitals’ development according to patients’ demand.As patient satisfaction study in China started comparatively late, at present, there aremany problems demanding prompt solution in theoretical and practical exploration. In2010, a scientific research project of Study on Large Comprehensive Hospitals’Patient Satisfaction Evaluation Index System being officially approved byChina-Japan Friendship Hospital affiliated to Chinese Ministry of Health, hoped touse the scientific method to optimize the indicators of the Large ComprehensiveHospitals’ Patient Satisfaction Scale, build up a more scientific and reasonableevaluation index system, construct the patient satisfaction index model and develop apatient satisfaction evaluation information system so as to offering some help forhospital quality improvement and services developing strategies. This dissertation is areflection of the research production.
On the basis of extensive research achievements at home and abroad, this dissertationconstructed and empirical analyzed the Large Comprehensive Hospitals’ Patient Satisfaction Index Model, with the combination of hospitals’ practices and theoreticalresearch, traditional probability statistics theory and modern grey theory and fuzzymathematics, on-site investigation and sampling and information technology. Themain results and conclusions obtained are as follows:
1. Based on the repeated design, investigation, analysis and modification of theinitial scale and the preliminary survey scale, this study conducted samplingsurvey in5domestically influential Large Comprehensive Hospitals which wasrespectively chosen form northern China, southern China, central China, easternChina and southwest China.The survey data were processed by explorative factoranalysis and confirmatory factor analysis to construct the multi-level largegerneral hospital patient satisfaction evaluation index system and form LargeComprehensive Hospitals’ Patient Satisfaction Evaluation Questionnaire.
2. Using the method of combining the multilayer linear model with structuralequation modeling, this sudy innovated the multi-level model of LargeComprehensive Hospitals’ Patient Satisfaction Index (LCHPSI). By empiricalanalysis of the model, it was confirmed that the causal relationship between thelatent variables and observed variables was correct and the model structure fittedthe actual data.
3. By research on LCHPSI model of different order, it was found that, in essence,there is no fundamental difference in adopting the second-order model or thefirst-order model and it would not affect the determination of the satisfactionindex. Thus the discussion of the different hierarchies affect the results of thesatisfaction index or not was settled.
4. This study conducted multi-level fuzzy comprehensive evaluation of patientsatisfaction based on sorting method for factor weights. Such a direct objectiveweighting method on a basis of statistical data of patients made the weightcoefficients assignment more objective. Combined with the multi-level fuzzycomprehensive evaluation method, the evaluation results tended to be truer. It wasproved effective through empirical analysis.
5. This study also conducted multi-level fuzzy comprehensive evaluation of patient satisfaction based on grey relational analysis for factor weights. Several modernmathematical tools used in conjunction reduced the expert differences caused bythe deviation to a certain extent and made the patient satisfaction evaluationachieve better results.
6. Through the empirical analysis, this study compared the two objective weightingmethod above and founded that the comprehensive evaluation results of these twomethods were basically the same whereas the multi-level fuzzy comprehensiveevaluation method of patient satisfaction based on sorting method for factorweights got higher overall satisfaction scores than the multi-level fuzzycomprehensive evaluation method of patient satisfaction based on grey relationalanalysis for factor weights.
7. Based on grey fuzzy theory, this study developed Patient Satisfaction EvaluationInformation System which realized the automation of hospitals’ patientsatisfaction evaluation. This information system carried on objective patientsatisfaction evaluation by adapting to the uncertainty caused by the incompleteevaluation data of patient satisfaction and achieving comparatively exactdescription and understanding of default values through part of knowninformation.
The main innovations of this dissertation:
1. Adopting the method combining multi-level linear model with structural equationmodeling, a second-order Large Comprehensive Hospitals’ Patient SatisfactionIndex (LCHPSI) model was created. Such a multi-level patient satisfaction indexmodel, could reasonably estimat that single observed variable’s influence onsatisfaction, and even compare the patient satisfaction on different levels indifferent fields of medical services.
2. By research on patient satisfaction index model of different order, it wasconcluded that the order of patient satisfaction index model would not infiluencethe determination of patient satisfaction index, so as to provide some reference forresearchers studying on multi-level patient satisfaction index model.
3. Proposing the method of multi-level fuzzy comprehensive evaluation of patientsatisfaction based on sorting method for factor weights, the determination of theweighting coefficients at all levels of the multi-level model was innovated, so asto make the weight coefficients assignment relatively objective and the evaluationresults truer.
4. The multi-level fuzzy comprehensive evaluation method of patient satisfactionbased on grey relational analysis for factor weights was also proposed. As acombination of grey theory and fuzzy mathematics, this new approach overcamethe restrictions of sample size and regularity, made up for the deficiencies of thetraditional statistical methods, and reduced the deviation caused by expertdifferences to a certain extent.
我国患者满意度的研究起步较晚，目前无论是理论还是实践方面都处于探索之中，许多问题亟待解决。2010年，卫生部中日友好医院科研课题《大型综合性医院患者满意度测评指标体系研究》正式立项，希望运用科学的方法，进行大型综合性医院患者满意度量表指标的优化，形成更为科学合理的大型综合性医院患者满意度测评指标体系，创建患者满意度指数模型，研制患者满意度测评信息系统，为医院质量改进措施和服务发展策略提供帮助。本文即是该课题研究成果的反映。
基于这样的研究背景，本文将医院实际工作与理论研究相结合、传统的概率统计理论与近代的灰色理论、模糊数学相结合、现场调查取样与信息技术相结合，在广泛综合国内外满意度研究成果的基础上，进行了大型综合性医院患者满意度指数模型的构建和实证分析，所取得的主要研究成果和结论如下：
1、在对患者满意度初始调查量表及预调查量表反复进行设计、调查、分析、修改的基础上，在全国华北、华中、华东、华南和西南五个地区各选一家在国内很有影响的大型综合性医院进行抽样调查，经探索性因子分析和验证性因子分析构建了多层次的大型综合性医院患者满意度测评指标体系，形成了大型综合性医院患者满意度测评问卷。
2、采用多层线性模型与结构方程模型相结合的方法，进行了多层次大型综合性医院患者满意度指数（LCHPSI）模型的创新。通过实证分析，证实了本文创建的多层次大型综合性医院患者满意度指数（LCHPSI）模型潜变量与观测变量之间的因果关系设置正确，结构模型与实际数据契合。
3、通过对不同阶数大型综合性医院患者满意度指数模型的研究，发现采用二阶模型或一阶模型在本质上并无根本差别、对满意度指数的测定不产生影响，解决了采用不同的层次结构是否会影响到满意度指数测评结果的问题。
4、进行了基于排序求因子权重的患者满意度多层次模糊综合评价的研究，这种直接根据患者统计数据的客观赋权法，使权重系数的分配比较客观，再结合多层次模糊综合评价法，使评判结果更趋真实。通过实证分析，证明效果良好。
5、进行了基于灰色关联求因子权重对病人满意度的多层次模糊综合评价的研究，这种将多个近代数学工具结合使用的方法在一定程度上减少了专家差异所造成的偏差，使患者满意度的测评能取得更好效果。
6、通过实证分析，将基于排序求因子权重对病人满意度的多层次模糊综合评价法和基于灰色关联求因子权重对病人满意度的多层次模糊综合评价法进行了对比，发现这两种方法的综合评价结果基本一致，但基于排序求因子权重的患者满意度多层次模糊综合评价法，在整体满意度得分上略高于基于灰色关联求因子权重的患者满意度多层次模糊综合评价法。
7、基于灰色模糊理论，进行了患者满意度测评信息系统的研制，实现医院患者满意度测评分析自动化。该信息系统适应患者满意度测评信息残缺的不确定状况，通过对部分已知信息来实现对缺省值的较确切描述和认识，客观地进行患者满意度测评。
本文的主要创新点有：
1、采用多层线性模型与结构方程模型相结合的方法，创建了二阶的大型综合性医院患者满意度指数（LCHPSI）模型。这种多层次的患者满意度指数模型，不但可合理地估计单个观测变量对满意度的影响，而且可以在不同层面上进行不同医疗服务领域间患者满意度的比较。
2、通过不同阶次患者满意度指数模型的研究，得出了患者满意度指数模型的阶数对满意度指数的测定不产生影响的结论，为研究人员进行多层次患者满意度指数模型的研究提供了一定的参考。
3、提出了基于排序求因子权重的病人满意度多层次模糊综合评价法，对多层次模型中各级的权重系数的确定进行了创新，从而使权重系数的分配比较客观，评判结果更趋于真实。
4、提出了基于灰色关联求因子权重病人满意度的多层次模糊综合评价法。这种新方法将灰色理论与模糊数学相结合，克服了对样本数量和规律性有一定要求的限制，弥补了传统统计方法的不足，在一定程度上减少了专家差异所造成的偏差。
With the deepening reform of China's medical and health system, gradually openingof medical service market, medical institutions is faced with increasingly intensemarket competition. Medical institutions, especially the Large ComprehensiveHospitals, win the trust of patients in competition and make the hospital constructionstepping into the benign orbit of sustainable development, only when they ensuredsatisfied medical services provision to patients. At present, in the modern hospitalmanagement evaluation index system, Patient Satisfaction is key criteria of appraisingthe treatment impact and medical service quality. Carring out the study on PatientSatisfaction is of great theoretical and realistic significance to improving healthquality management theory and guiding medical institution to improve targetedservices. As the main body in medical and health system and assumed to be regionalmedical centers, Large Comprehensive Hospitals should pay more attention to PatientSatisfaction and promote hospitals’ development according to patients’ demand.As patient satisfaction study in China started comparatively late, at present, there aremany problems demanding prompt solution in theoretical and practical exploration. In2010, a scientific research project of Study on Large Comprehensive Hospitals’Patient Satisfaction Evaluation Index System being officially approved byChina-Japan Friendship Hospital affiliated to Chinese Ministry of Health, hoped touse the scientific method to optimize the indicators of the Large ComprehensiveHospitals’ Patient Satisfaction Scale, build up a more scientific and reasonableevaluation index system, construct the patient satisfaction index model and develop apatient satisfaction evaluation information system so as to offering some help forhospital quality improvement and services developing strategies. This dissertation is areflection of the research production.
On the basis of extensive research achievements at home and abroad, this dissertationconstructed and empirical analyzed the Large Comprehensive Hospitals’ Patient Satisfaction Index Model, with the combination of hospitals’ practices and theoreticalresearch, traditional probability statistics theory and modern grey theory and fuzzymathematics, on-site investigation and sampling and information technology. Themain results and conclusions obtained are as follows:
1. Based on the repeated design, investigation, analysis and modification of theinitial scale and the preliminary survey scale, this study conducted samplingsurvey in5domestically influential Large Comprehensive Hospitals which wasrespectively chosen form northern China, southern China, central China, easternChina and southwest China.The survey data were processed by explorative factoranalysis and confirmatory factor analysis to construct the multi-level largegerneral hospital patient satisfaction evaluation index system and form LargeComprehensive Hospitals’ Patient Satisfaction Evaluation Questionnaire.
2. Using the method of combining the multilayer linear model with structuralequation modeling, this sudy innovated the multi-level model of LargeComprehensive Hospitals’ Patient Satisfaction Index (LCHPSI). By empiricalanalysis of the model, it was confirmed that the causal relationship between thelatent variables and observed variables was correct and the model structure fittedthe actual data.
3. By research on LCHPSI model of different order, it was found that, in essence,there is no fundamental difference in adopting the second-order model or thefirst-order model and it would not affect the determination of the satisfactionindex. Thus the discussion of the different hierarchies affect the results of thesatisfaction index or not was settled.
4. This study conducted multi-level fuzzy comprehensive evaluation of patientsatisfaction based on sorting method for factor weights. Such a direct objectiveweighting method on a basis of statistical data of patients made the weightcoefficients assignment more objective. Combined with the multi-level fuzzycomprehensive evaluation method, the evaluation results tended to be truer. It wasproved effective through empirical analysis.
5. This study also conducted multi-level fuzzy comprehensive evaluation of patient satisfaction based on grey relational analysis for factor weights. Several modernmathematical tools used in conjunction reduced the expert differences caused bythe deviation to a certain extent and made the patient satisfaction evaluationachieve better results.
6. Through the empirical analysis, this study compared the two objective weightingmethod above and founded that the comprehensive evaluation results of these twomethods were basically the same whereas the multi-level fuzzy comprehensiveevaluation method of patient satisfaction based on sorting method for factorweights got higher overall satisfaction scores than the multi-level fuzzycomprehensive evaluation method of patient satisfaction based on grey relationalanalysis for factor weights.
7. Based on grey fuzzy theory, this study developed Patient Satisfaction EvaluationInformation System which realized the automation of hospitals’ patientsatisfaction evaluation. This information system carried on objective patientsatisfaction evaluation by adapting to the uncertainty caused by the incompleteevaluation data of patient satisfaction and achieving comparatively exactdescription and understanding of default values through part of knowninformation.
The main innovations of this dissertation:
1. Adopting the method combining multi-level linear model with structural equationmodeling, a second-order Large Comprehensive Hospitals’ Patient SatisfactionIndex (LCHPSI) model was created. Such a multi-level patient satisfaction indexmodel, could reasonably estimat that single observed variable’s influence onsatisfaction, and even compare the patient satisfaction on different levels indifferent fields of medical services.
2. By research on patient satisfaction index model of different order, it wasconcluded that the order of patient satisfaction index model would not infiluencethe determination of patient satisfaction index, so as to provide some reference forresearchers studying on multi-level patient satisfaction index model.
3. Proposing the method of multi-level fuzzy comprehensive evaluation of patientsatisfaction based on sorting method for factor weights, the determination of theweighting coefficients at all levels of the multi-level model was innovated, so asto make the weight coefficients assignment relatively objective and the evaluationresults truer.
4. The multi-level fuzzy comprehensive evaluation method of patient satisfactionbased on grey relational analysis for factor weights was also proposed. As acombination of grey theory and fuzzy mathematics, this new approach overcamethe restrictions of sample size and regularity, made up for the deficiencies of thetraditional statistical methods, and reduced the deviation caused by expertdifferences to a certain extent.
引文
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