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九江市浔阳区居民对“医养结合”模式的需求调查及其影响因素分析
引用本文:喻明霞. 九江市浔阳区居民对“医养结合”模式的需求调查及其影响因素分析[J]. 医学信息, 2018, 0(21): 118-121. DOI: 10.3969/j.issn.1006-1959.2018.21.033
作者姓名:喻明霞
作者单位:江西省九江市第一人民医院纪检监察室,江西 九江 332000
摘    要:目的 调查九江市浔阳区居民对不同“医养结合”模式的需求,分析其影响因素。方法 采用现场问卷调查的方式,于2018年3月随机对九江市浔阳区居民300人进行不同“医养结合”模式需求的调查,采用SPSS 22.0软件对数据进行统计分析。结果 不同年龄、居住状况、家庭收入、健康状况的居民在医养模式的选择上,差异有统计学意义(P<0.05)。70岁以下居民更偏好“以养融医”模式(50~60岁、60~70岁年龄组分别为33.33%、30.17%);70岁以上的居民对“合作转诊”的支持度较低(8.64%)。独居老人更偏好“以养融医”模式(44.44%),对“以医融养”的支持度较低(2.22%);与配偶或子女居住的老人对“合作上门”的支持度较高(32.56%)。家庭年收入20万元以下的居民更偏好于“以养融医”和“合作上门”模式(家庭年收入为2~8万、8~20万的居民对“以养融医”的支持度分别为32.00%、26.77%,对“合作上门”的支持度分别为30.67%、33.07%);家庭年收入20万元以上者对“以养融医”“合作转诊”“合作上门”的支持度分别为24.14%、39.66%、31.03%,而对“以医融养”模式支持度非常低,为5.17%。无患病或仅患有一种慢性病的老人偏好“合作上门”模式(支持度分别为34.33%、32.62%);患有两种及以上慢性病的老人更偏好“以养融医”模式(支持度为48.08%),对“以医融养”模式支持度较低(9.62%)。结论 “合作上门”“以养融医”模式较受浔阳区居民欢迎,“合作转诊”“以医融养”模式的认同度较低。影响居民“医养结合”模式的选择因素主要为年龄、居住状况、家庭年收入、健康情况等。

关 键 词:医养结合  模式  需求  影响因素

An Investigation on the Demands of the "Combination of Medicine and Nourishment"Modes in the Residents of Xunyang District of Jiujiang City and Analysis of its Influencing Factors
YU Ming-xia. An Investigation on the Demands of the "Combination of Medicine and Nourishment"Modes in the Residents of Xunyang District of Jiujiang City and Analysis of its Influencing Factors[J]. Medical Information, 2018, 0(21): 118-121. DOI: 10.3969/j.issn.1006-1959.2018.21.033
Authors:YU Ming-xia
Affiliation:Department of Discipline Inspection and Supervision,Jiujiang First People's Hospital,Jiujiang 332000,Jiangxi,China
Abstract:Objective To investigate the needs of residents in Xunyang District of Jiujiang city for different modes of"combination of medicine and nourishment"and analyze the influencing factors. Methods In the way of on-site questionnaire survey, in March 2018, 300 people in Xunyang District of Jiujiang City were randomly selected to investigate the needs of different "combination of medicine and nourishment" mode. The data were statistically analyzed using SPSS 22.0 software.Results The differences in the choice of health care patterns among residents of different ages, living conditions, family income and health status were statistically significant (p<0.05). Residents under the age of 70 prefer the "following health care" model (33.33%, 30.17% in the 50-60, 60-70 age group, respectively); residents over 70 years of age have low support for "cooperative referral" (8.64 %).The elderly living alone prefer the "following health care" model (44.44%), and the support for "following health care" is low (2.22%); the elderly living with spouses or children have higher support for"cooperative door-to-door"(32.56%). Residents with an annual income of less than RMB 200,000 are more likely to support the "following medical care" and "cooperative door-to-door" models (residents support for following medical care with annual household income of 20,000 to 80,000 and 800,000 to 200,000 were 32.00% and 26.77% respectively, and the support for "cooperative door-to-door" was 30.67% and 33.07% respectively); those with annual household income of more than 200,000 yuan were "following health care" "cooperative referral"and"cooperative door-to-door"support levels were 24.14%, 39.66%, and 31.03%,while the support for the "merge and nourish with medicine" model was very low 5.17%. Old people who are not sick or have only one chronic disease prefer the "cooperative door-to-door" mode (support is 34.33%, 32.62%); elderly people with two or more chronic diseases prefer the "following health care" mode (support for 48.08%), the support for the "merge and nourish with medicine" mode is low (9.62%). Conclusion "Cooperative door-to-door"and "following health care"modes are more popular among residents in Xunyang District, and the recognition of "cooperative referral" and "merge and nourish with medicine"mode is lower. The factors that influence the residents' "combination of medicine and nourishment" are mainly age, living conditions, annual family income, and health status.
Keywords:Combination of medicine and nourishment  Modes  Demand  Influence factors
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