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Modeling Medical Services with Mobile Health Applications
Zhenfei Wang1, Liying Zhang1, Ling Ma1
1School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China.
Journal of Healthcare Engineering
|June 1, 2018
Summary
Mobile health (m-Health) applications enhance patient-doctor communication and optimize healthcare services. Our model balances supply and demand, minimizing patient costs and doctor inefficiency in the evolving medical market.
Area of Science:
- Health Informatics
- Health Economics
- Medical Technology
Background:
- Mobile health (m-Health) technology is rapidly advancing, offering new ways to improve healthcare delivery.
- m-Health applications facilitate direct communication between patients and doctors via smartphones, increasing in popularity.
- The impact of these applications on the medical service market requires thorough evaluation.
Purpose of the Study:
- To evaluate the influence of m-Health applications on the medical service market.
- To develop a medical service equilibrium model that balances doctor supply and patient demand.
- To analyze patient and doctor behaviors to minimize healthcare costs and provider inefficiency.
Main Methods:
- Development of a medical service equilibrium model.
- Analysis of patient and doctor behaviors within the model.
- Mathematical reasoning to derive a resolution algorithm.
- Experimental evaluation using an artificially generated dataset.
Main Results:
- The proposed model effectively balances the supply of doctors and demand for medical services.
- Analysis indicates potential for minimizing patient healthcare costs and doctor "futility" (inefficiency).
- Experimental results demonstrate the impact of m-Health applications on medical service efficiency.
Conclusions:
- m-Health applications present significant opportunities for optimizing the medical service market.
- The developed model provides a framework for understanding and improving healthcare delivery with m-Health integration.
- Further research and application of the model can lead to more efficient and cost-effective healthcare solutions.
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