基层医护人员学习和使用卫生适宜技术的偏好及影响因素研究

发布时间：2018-03-15 20:18

本文选题：卫生适宜技术　切入点：医护人员　出处：《北京中医药大学》2017年硕士论文　论文类型：学位论文

【摘要】：目的:以北京市朝阳区社区卫生服务中心的医护人员为研究对象,采用离散选择实验的方法,研究基层医护人员学习和使用卫生适宜技术的偏好和影响医护人员学习和使用卫生适宜技术的关键因素,并进一步分析不同的医护人员群体的选择偏好,为进行卫生适宜技术培训和推广工作提供参考和借鉴。方法:研究整体采用离散选择实验的方法,其中,(1)运用文献研究法归纳卫生适宜技术和卫生经济领域离散选择实验相关的文献和研究资料;(2)运用专家咨询的方法确定卫生适宜技术的属性和属性水平;(3)运用正交设计的方法对属性和属性水平进行组合确定离散选择实验的选择集并设计基层医护人员学习和使用卫生适宜技术的偏好调查问卷;(4)运用问卷调查法对朝阳区10家社区卫生服务中心的医护人员进行现场调查;(5)运用数理统计方法对数据进行分析,首先用描述性统计对调查对象基本情况进行分析;其次,采用离散选择模型的RPL模型对医护人员的卫生适宜技术学习和使用偏好进行分析,分析不同属性的影响作用和影响程度;最后用潜分类选择模型对不同个体特征的医护人员群体的选择偏好和各因素对不同群体的影响作用进行分析。所有数据用Excel2013进行录入,基本情况的分析和正交实验设计采用SPSS19.0进行分析,选择数据的离散选择模型采用Nlogit5.0进行分析。结果:(1)RPL模型结果显示,对收入的影响属性的参数系数为1.20474(P0.01),技术的预期疗效属性的系数为0.71888(P0.01),个人发展机会属性的系数为0.36491(P0.01),患者对技术的认可程度的系数为0.35101(P0.01),技术学习和使用难度的系数为-0.20115(P0.1),专项激励机制的系数为0.12036(P0.1)。医护人员的个体特征因素中性别的影响系数为0.38064(P0.05),年龄的系数为0.04969(P0.01),编制的系数为0.24387(P0.05),从事本专业的年限的系数为-0.02958(P0.1);(2)潜分类选择模型结果显示,第一细分组中,对收入的影响属性的参数系数为3.64054(P0.1),技术的预期疗效属性的系数为3.71740(P0.1),个人发展机会属性的系数为5.24820(P0.1),技术学习和使用难度的系数为-1.57067(P0.1),配套设备条件的系数为2.05074(P0.1),卫生适宜技术专项激励机制系数为2.68697(P0.1);第二细分组中,对收入的影响属性的参数系数为0.82981(P0.01),技术的预期疗效属性的系数为0.35739(P0.05),患者对技术的认可程度的系数为0.22331(P0.1)。结论:(1)在卫生适宜技术的7个属性中收入的变化、技术预期疗效、个人发展机会、患者对技术的认可程度、学习和使用难度对医护人员选择学习和使用卫生适宜技术有一定的影响作用,与技术配套设备的条件、专项激励机制两个属性没有影响作用。(2)具有不同个体特征的医护人员群体对卫生适宜技术的学习和使用偏好不同,第一类群体更愿意学习和使用预期疗效高、学习和使用难度低、配套设备齐全、增加个人收入、专项激励机制健全、个人发展机会多的卫生适宜技术;第二类群体愿意学习预期疗效高、增加个人收入、患者认可程度高的卫生适宜技术。
[Abstract]:Objective: to Chaoyang District community health service center of Beijing City medical staff as the research object, using the method of discrete choice experiment, study the basic medical staff learning and the use of appropriate health technology preferences and effect of medical staff to study and use the appropriate health technology the key factors, preferences and further analysis of different health care groups, for to provide reference for technical training and promotion of appropriate health. Methods: the study adopted method, discrete choice experiment, (1) using the methods of literature research summarized appropriate health technology and health economic research discrete choice experiment literature and research relevant information; (2) using the method of expert consultation to determine the appropriate technology attributes and levels of health; (3) by the method of orthogonal design to determine the combination of attribute and attribute level discrete choice experiment and selection set Plan of primary health care workers to learn and use appropriate health technology preference questionnaire; (4) using the method of questionnaire survey of 10 community health service centers of Chaoyang District medical personnel on-site investigation; (5) using statistical methods to analyze the data, first using descriptive statistics to survey the basic situation analysis; secondly, the RPL model uses discrete choice model of technological learning and preferences of the medical staff of appropriate health, influence and influence degree of different attributes; finally the influence of different groups on the role of the submarine classification selection preferences for health care groups with the individual characteristics of the model and the various factors. All data with Excel2013 input, analysis and orthogonal experimental design, the basic situation of using SPSS19.0 analysis, discrete choice model selection data by Nlogit5.0 For analysis. Results: (1) the RPL model results show that the influence on income attribute coefficient is 1.20474 (P0.01), the expected effect coefficient attribute of technology was 0.71888 (P0.01), the coefficient of personal development opportunities attribute is 0.36491 (P0.01), in recognition of the extent of the coefficient is 0.35101 (P0.01), technological learning and difficult to use for the -0.20115 coefficient (P0.1), the special coefficient incentive mechanism was 0.12036 (P0.1). Other neutral individual factors influence coefficient of medical staff was 0.38064 (P0.05), the age coefficient was 0.04969 (P0.01), the coefficient is 0.24387 (P0.05), the coefficient in the professional the number of -0.02958 (P0.1); (2) choose the latent class model results show that the first sub group, the income effects attribute coefficient is 3.64054 (P0.1), the expected effect coefficient of attribute technology was 3.71740 (P0.1), the coefficient of personal development opportunities attribute 5.24820 (P0.1), and the coefficient of difficulty of the use of learning technology for -1.57067 (P0.1), the coefficient of equipment conditions was 2.05074 (P0.1), the mechanism of incentives for appropriate health technology special coefficient of 2.68697 (P0.1); second subgroups, number of parameters affect the property department revenue was 0.82981 (P0.01), coefficient the expected effect of property of technology is 0.35739 (P0.05), in recognition of the extent of the coefficient was 0.22331 (P0.1). Conclusion: (1) changes in income in 7 properties of appropriate health technology in technology, expected outcomes, personal development opportunities, in recognition of the extent of technology, learning and the use of difficulty the medical personnel to study and use of appropriate health technology have a certain effect, and the technology of equipment condition, the two attributes of special incentive mechanism has no effect. (2) with different individual characteristics of the medical staff of the appropriate health technology group The study and use of different preferences, the first group are more willing to learn and use the expected high efficacy, low degree of difficulty to learn and use, form a complete set of equipment, increase personal income, special incentive mechanisms, appropriate health technology for personal development opportunities; the second group is willing to learn the expected high efficacy, increase personal income, health appropriate technology approval patients with high levels.

【学位授予单位】：北京中医药大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R197.61

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