Examining the Most Important Determinants of Health-Related Quality of Life (HRQoL). The Machine Learning Approach

Authors

  • Nino Kokashvili University of Tartu, Liivi 4, Tartu, 51009, Estonia
  • Youjun Shin University of Tartu, Liivi 4, Tartu, 51009, Estonia

Keywords:

Health Determinants, Health Policy, Machine Learning, Health-related quality of life (HRQoL), JEL Classification, I12, I18, I15.

Abstract

There are various circumstances affecting the individual health-related quality of life (HRQoL). The aim of the paper is to understand which health determinants are the most crucial while designing the efficient health policy. Using the machine learning approach, authors examine 42 health status related factors. The paper incorporates 27 individual level and 15 regional level health state determinants in empirical investigation. Results show that in terms of factor weights, the subjective health is the most influential on individual level and medical labor force - on regional level. However, in terms of frequency, the hospital visiting plays the most important role on individual level and estate condition - on regional level. In addition, empirical results indicate that individual level factors have higher impact on health status than regional level factors. Based on empirical results of the paper, authors provide policy recommendations.

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Published

2019-06-09

How to Cite

Kokashvili, N., & Shin, Y. (2019). Examining the Most Important Determinants of Health-Related Quality of Life (HRQoL). The Machine Learning Approach. International Journal of Sciences: Basic and Applied Research (IJSBAR), 47(1), 12–36. Retrieved from https://gssrr.org/index.php/JournalOfBasicAndApplied/article/view/10061

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