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Huang Y, Xu T, Yang Q, Pan C, Zhan L, Chen H, Zhang X, Chen C. Demand prediction of medical services in home and community-based services for older adults in China using machine learning. Front Public Health 2023; 11:1142794. [PMID: 37006569 PMCID: PMC10060662 DOI: 10.3389/fpubh.2023.1142794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 02/28/2023] [Indexed: 03/18/2023] Open
Abstract
BackgroundHome and community-based services are considered an appropriate and crucial caring method for older adults in China. However, the research examining demand for medical services in HCBS through machine learning techniques and national representative data has not yet been carried out. This study aimed to address the absence of a complete and unified demand assessment system for home and community-based services.MethodsThis was a cross-sectional study conducted on 15,312 older adults based on the Chinese Longitudinal Healthy Longevity Survey 2018. Models predicting demand were constructed using five machine-learning methods: Logistic regression, Logistic regression with LASSO regularization, Support Vector Machine, Random Forest, and Extreme Gradient Boosting (XGboost), and based on Andersen's behavioral model of health services use. Methods utilized 60% of older adults to develop the model, 20% of the samples to examine the performance of models, and the remaining 20% of cases to evaluate the robustness of the models. To investigate demand for medical services in HCBS, individual characteristics such as predisposing, enabling, need, and behavior factors constituted four combinations to determine the best model.ResultsRandom Forest and XGboost models produced the best results, in which both models were over 80% at specificity and produced robust results in the validation set. Andersen's behavioral model allowed for combining odds ratio and estimating the contribution of each variable of Random Forest and XGboost models. The three most critical features that affected older adults required medical services in HCBS were self-rated health, exercise, and education.ConclusionAndersen's behavioral model combined with machine learning techniques successfully constructed a model with reasonable predictors to predict older adults who may have a higher demand for medical services in HCBS. Furthermore, the model captured their critical characteristics. This method predicting demands could be valuable for the community and managers in arranging limited primary medical resources to promote healthy aging.
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Affiliation(s)
- Yucheng Huang
- School of Public Health and Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Tingke Xu
- School of Public Health and Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Qingren Yang
- School of Public Health and Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Chengxi Pan
- The State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen, China
| | - Lu Zhan
- School of Public Health and Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Huajian Chen
- School of Public Health and Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Xiangyang Zhang
- School of Public Health and Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Xiangyang Zhang
| | - Chun Chen
- School of Public Health and Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Center for Healthy China Research, Wenzhou Medical University, Wenzhou, Zhejiang, China
- *Correspondence: Chun Chen
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Zhang Y, Zhang M, Hu H, He X. Spatio-Temporal Characteristics of the Supply and Demand Coupling Coordination of Elderly Care Service Resources in China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:10397. [PMID: 36012031 PMCID: PMC9408112 DOI: 10.3390/ijerph191610397] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 08/06/2022] [Accepted: 08/17/2022] [Indexed: 06/15/2023]
Abstract
The current situation and future development of the supply and demand coupling coordination of elderly care service resources reflect the level of elderly care service resource allocation. Whether factors affecting its development can be found is the key to promote the accurate allocation of elderly care service. Based on the coupling coordination model, the supply and demand of elderly care service resources, the development circumstance and the spatio-temporal evolution of supply and demand coupling coordination are analyzed in this paper by using the data of the elderly care service resources in 31 regions and autonomous regions in China from 2010 to 2019. The result shows that there are regional differences in the development of supply and demand coupling coordination of elderly care service resources. The degree of supply and demand coupling coordination of elderly care service resources in the western and northern regions is lower than that in the eastern and southern regions. Although the level in most areas of supply and demand coupling coordination of elderly care service resources will improve in the future, there is still a gap from good coordination. In order to strengthen the supply of elderly care service resources, and promote the upgrade of the supply and demand of elderly care service resources, the government should start from the demand of the elderly to increase investment in infrastructure construction, investment in elderly care services resources, talent training and other aspects.
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Affiliation(s)
- Yijie Zhang
- School of Economics and Management, Yanshan University, Qinhuangdao 066004, China
| | - Mingli Zhang
- School of Economics and Management, Yanshan University, Qinhuangdao 066004, China
- Department of Public Education, Hebei University of Chinese Medicine, Shijiazhuang 050200, China
| | - Haiju Hu
- School of Economics and Management, Yanshan University, Qinhuangdao 066004, China
| | - Xiaolong He
- School of Mechanical Engineering, Yanshan University, Qinhuangdao 066004, China
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Research on Supply and Demand of Aged Services Resource Allocation in China: A System Dynamics Model. SYSTEMS 2022. [DOI: 10.3390/systems10030059] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
With the rapid growth of the elderly population of China in recent years, the service demands of older Chinese people continue to increase. The increasingly severe situation with respect to the elderly population is an important social problem that China will face for a long time into the future. It is urgent to solve the problem of how to scientifically carry out allocation planning of service resources for the aged and guide the effective supply of service resources. This paper analyzes the factors affecting service resources for the aged, divides China’s service resource supply and demand system into a supply subsystem, a demand subsystem, and a population and economy subsystem. Using system dynamics methods to analyze the causal relationship between variables and the state space method to build a mathematical model and perform simulation analysis, we research the the current situation of China’s service resources supply and demand balance for the aged. In addition, we put forward resource configuration optimization measures for the future allocation of service resources for the aged, providing a practical basis for future decision-making.
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Essuman A, Agyemang FA, Mate-Kole CC. Long-term Care for Older Adults in Africa: Whither Now? J Am Med Dir Assoc 2018; 19:728-730. [PMID: 30149839 DOI: 10.1016/j.jamda.2018.07.012] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Accepted: 07/13/2018] [Indexed: 10/28/2022]
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Yamauchi Y. Decomposing Cost Efficiency in Regional Long-term Care Provision in Japan. Glob J Health Sci 2015; 8:89-100. [PMID: 26493427 PMCID: PMC4803933 DOI: 10.5539/gjhs.v8n3p89] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2015] [Accepted: 05/25/2015] [Indexed: 11/12/2022] Open
Abstract
Many developed countries face a growing need for long-term care provision because of population ageing. Japan is one such example, given its population's longevity and low birth rate. In this study, we examine the efficiency of Japan's regional long-term care system in FY2010 by performing a data envelopment analysis, a non-parametric frontier approach, on prefectural data and separating cost efficiency into technical, allocative, and price efficiencies under different average unit costs across regions. In doing so, we elucidate the structure of cost inefficiency by incorporating a method for restricting weight flexibility to avoid unrealistic concerns arising from zero optimal weight. The results indicate that technical inefficiency accounts for the highest share of losses, followed by price inefficiency and allocation inefficiency. Moreover, the majority of technical inefficiency losses stem from labor costs, particularly those for professional caregivers providing institutional services. We show that the largest share of allocative inefficiency losses can also be traced to labor costs for professional caregivers providing institutional services, while the labor provision of in-home care services shows an efficiency gain. However, although none of the prefectures gains efficiency by increasing the number of professional caregivers for institutional services, quite a few prefectures would gain allocative efficiency by increasing capital inputs for institutional services. These results indicate that preferred policies for promoting efficiency might vary from region to region, and thus, policy implications should be drawn with care.
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Duku SKO, van Dullemen CE, Fenenga C. Does Health Insurance Premium Exemption Policy for Older People Increase Access to Health Care? Evidence from Ghana. J Aging Soc Policy 2015; 27:331-47. [DOI: 10.1080/08959420.2015.1056650] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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