基于SWOT-CLPV模型的我国医养联合体发展策略研究
Strategies for medical and elderly care consortium development in China:a SWOT-CLPV analysis
燕芳红 1张国莉 2彭国恬 2孙瑞仪 2马玉霞 1孙霞 3韩琳4
作者信息
- 1. 730000 兰州,兰州大学循证护理中心/兰州大学护理学院;兰州大学第一临床医学院
- 2. 730000 兰州,兰州大学循证护理中心/兰州大学护理学院
- 3. 兰州市盐场路草场街街道社区卫生服务中心
- 4. 730000 兰州,兰州大学循证护理中心/兰州大学护理学院;兰州大学第一临床医学院;甘肃省人民医院护理部(韩琳)
- 折叠
摘要
老年人存在医疗与养老的双重需求,医养联合体是推动医养结合发展的有益实践,已有研究聚焦老年人的多重需求,主要围绕医养联合体的内涵特点、模式类型、发展困境及对策开展探索实践,但少有研究结合环境因素对其发展态势进行分析.本研究基于SWOT-CLPV模型对我国医养联合体的优势、劣势、机会和威胁进行梳理,并对其相互转化产生的抑制性、杠杆效应、问题性、脆弱性进行分析,提出现代化信息技术助推医养资源有效融合的增长型策略、明确机构间分工职责与利益分配的扭转型策略、加强全方位制度保障的多元型策略、提高基层机构服务水平的防御型策略,为我国医养联合体发展提供参考,从而更好地满足广大老年人医养服务需求,提升老年人生活质量和养老服务水平.
Abstract
The elderly have the dual needs for medical care and elderly care.The medical and elderly care consortium(MECC)is valuable for promoting the integrated care for the older people.Focusing on the multiple needs of the elderly,the currently available studies have explored the connotations,characteristics,modes,dilemmas,and solutions of MECC.However,few studies have analyzed its environmental factors and development trends.Based on the SWOT-CLPV model,we elucidated the advantages,disadvantages,opportunities,and threats of MECC and analyzed the leverage,constraint,vulnerability,and problem generated by their mutual transformation.It is proposed that the modern information technology may boost the effective integration of medical care and elderly care resources(the growth strategy),define the division of responsibilities and allocation of benefits among institutions(the torsion strategy),strengthen the comprehensive institutional guarantees(the diversified strategy),and raise the service level of grassroots institutions(the defensive strategy).These findings can guide the development of MECC,thus better addressing the needs of the elderly for medical care and elderly care and improving the quality of life of the elderly.
关键词
医养联合体/医养结合/SWOT-CLPV模型/发展策略Key words
Medical and elderly care consortium/Integration of medical and elderly care services/SWOT-CLPV model/Strategy引用本文复制引用
出版年
2024
NETL
NSTL
维普
万方数据