Abstract
The purpose of this study is to clarify the collateral health effects of health care , especially the relationship between patients and their families, using agent-based simulation. To this end we describe the general appearance of our simulation model and the simulation settings. The results of six model scenarios, each involving differing combinations of patient agents, patient’s family agents, doctor agents, a government agent, and nonprofit organization (NPO) agents, are then explained and discussed. We conclude with a summary that touches on the tasks that lie ahead, including an appropriate subset of health care policies that involve the participation of NPO agents.
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Notes
- 1.
- 2.
See Ref. [3].
- 3.
Quoted from Ref. [4].
- 4.
See Ref. [5].
- 5.
Social cost is generally defined in economics as “the cost to society as a whole from an event.” Here we narrowly define social cost as the financial and mental cost incurred by a patient’s family in supporting that patient.
- 6.
- 7.
- 8.
According to [10], the goodness-of-fit index (GFI) is 0.861 and the adjusted goodness-of-fit index (AGFI) is 0.781.
- 9.
The average number of people per family is based on [17, p. 3].
- 10.
In order to analyze the rate of decrease in health care resources in our other models, we implement the mechanism of a government health care system in Models 1 and 2, although in these models no government health care resources are distributed to patients.
- 11.
In our simulation model we use artisoc 3.0, which is produced by Kozo Keikaku Engineering, Inc.
- 12.
- 13.
Model 6 is based on Model 4. The number of simulation times is 10.
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Acknowledgements
This work was partially supported as “a Promotion Project for Distinctive Joint Research” by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), April 2012–March 2013. The second author gratefully acknowledges the support of Kansai University’s Overseas Research Program for the year 2010. We are also pleased to acknowledge the helpful comments of the referees.
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Murakami, M., Tanida, N. (2014). An Agent-Based Approach for Patient Satisfaction and Collateral Health Effects. In: Chen, SH., Terano, T., Yamamoto, R., Tai, CC. (eds) Advances in Computational Social Science. Agent-Based Social Systems, vol 11. Springer, Tokyo. https://doi.org/10.1007/978-4-431-54847-8_13
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DOI: https://doi.org/10.1007/978-4-431-54847-8_13
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