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Simulation of performance evaluation model for medical-elderly care integrated institutions based on system dynamics

Overview of attention for article published in BMC Health Services Research, November 2022
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Title
Simulation of performance evaluation model for medical-elderly care integrated institutions based on system dynamics
Published in
BMC Health Services Research, November 2022
DOI 10.1186/s12913-022-08835-0
Pubmed ID
Authors

Yongqiang Shi, Fangfang Fan, Zhiyong Zhang

Abstract

Based on the Chinese model of medical-elderly care integration, this paper aims to explore the impact of different investment levels on the performance of the medical-elderly care integrated institutions. Using the method of system dynamics, this paper establishes the performance evaluation model of medical-elderly care integrated institutions, sets the system element input, service level, and policy support as the key factors, and uses Vensim PLE software for simulation. The three key factors have different degrees of positive impact on the performance of medical-elderly care integrated institutions. On the whole, policy support has the most significant impact on the performance of institutions, followed by the level of medical-elderly care integrated services. Institutional input mainly has a great impact on the performance of institutions in the early stage. In addition, the model simulation results also show the emergence effect: the improvement rate of institutional performance under the comprehensive simulation is higher than the sum of the improvement rates under the separate action of single factor. Government policies have played an important role in promoting the development of medical-elderly care integrated institutions. The service level and resource input can effectively promote the performance of medical-elderly care integrated institutions. Institutions should formulate development strategies from a systematic perspective, and pay attention to the integration of "medical" and "elderly care" resources.

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Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 18%
Lecturer 2 18%
Other 1 9%
Student > Bachelor 1 9%
Student > Ph. D. Student 1 9%
Other 2 18%
Unknown 2 18%
Readers by discipline Count As %
Unspecified 2 18%
Nursing and Health Professions 2 18%
Medicine and Dentistry 2 18%
Business, Management and Accounting 1 9%
Engineering 1 9%
Other 0 0%
Unknown 3 27%