Predictors of Medical and Dental Clinic Closure by Machine Learning Methods: Cross-Sectional Study Using Empirical Data
This study showed that machine running methods are useful tools for predicting the closure of small medical facilities with a moderate level of accuracy. Essential factors affecting medical facility closure also differed between MCs and DCs. Developing good models would prevent unnecessary medical facility closures at the national level.
Authors
- Ji Soo Jeon
- Young‐Taek Park (ORCID: https://orcid.org/0000-0002-7574-4165)
- Kwang Gi Kim (ORCID: https://orcid.org/0000-0001-9714-6038)
- Donghan Kim (ORCID: https://orcid.org/0000-0003-1824-3898)
Institutions
- Gachon University (KR)
- Health Insurance Review and Assessment Service (KR)
- Korea Research Institute for Human Settlements (KR)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2024-08-30
- DOI
- https://doi.org/10.2196/46608
- Citations
- 3
- Primary Topic
- Patient Satisfaction in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 2.55