EFFECT OF HEALTHCARE EXPENDITURE ON THE CORRELATION BETWEEN THE NUMBER OF NURSES AND DOCTORS EMPLOYED

Öz

Aim: The aim of this study is to analyze the correlation between the numbers of doctors and nurses, as well as the effect of health expenditure (HE) on the employment of doctors and nurses. Methods: The study data belong to the Turkish health system and cover the years 1975-2018. The amount of HE data was handled as the ratio of Turkey to national income (GDP). Pearson correlation test and linear regression model methods were used in this study. The doctor-nurse ratio was examined in order to see the interaction levels of the relationship between the doctor and the nurse apart from the correlation. Findings: There is a strong correlation between nurse and doctor employment, and the correlation value was calculated as 0.973 (p-value=0.001, n=44 samples). Correlation coefficients between dependent variables and independent (HE) variables were analyzed as 0.715 (p-value=0.001) for nurse employment and 0.840 (p-value=0.001) for physician employment, respectively. Conclusion: The amount of HE was very effective on both the number of physicians and the nurses based on the regression analysis.

Anahtar Kelimeler

• The number of physicians
• The number of physicians
• The number of nurses
• Healthcare expenditure
• Pearson correlation
• Linear regression model

Kaynakça

1. Abedi, V., Olulana, O., Avula, V., Chaudhary, D., Khan, A., Shahjouei, S., Li, J., & Zand, R. (2021). Racial, Economic, and Health Inequality and COVID-19 Infection in the United States. Journal of Racial and Ethnic Health Disparities, 8(3), 732–742. https://doi.org/10.1007/s40615-020-00833-4
2. Atalan, A. (2018). Türkiye Sağlık Ekonomisi için İstatistiksel Çok Amaçlı Optimizasyon Modelinin Uygulanması. İşletme Ekonomi ve Yönetim Araştırmaları Dergisi, 1(1), 34–51. http://dergipark.gov.tr/download/article-file/414076
3. Atalan, A. (2020). Forecasting for Healthcare Expenditure of Turkey Covering the Years of 2018-2050. Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi, 9(1), 8–16. https://doi.org/10.37989/gumussagbil.538111
4. Atalan, A., & Donmez, C. C. (2020). Developing Optimization Models To Evluate Healthcare Systems. Sigma Journal of Engineering and Natural Sciences, 38(2), 853–873.
5. Barnes, H., Richards, M. R., McHugh, M. D., & Martsolf, G. (2018). Rural And Nonrural Primary Care Physician Practices Increasingly Rely On Nurse Practitioners. Health Affairs, 37(6), 908–914. https://doi.org/10.1377/hlthaff.2017.1158
6. Briggs, A. H., & Gray, A. M. (1999). Handling uncertainty when performing economic evaluation of healthcare interventions. In Health Technology Assessment.
7. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd Editio). Lawrence Erlbaum Associates.
8. Craven, M. P., Morgan, S. P., Crowe, J. A., & Lu, B. (2009). Deploying a spreadsheet tool for early economic value assessment of medical device innovations with healthcare decision makers. Journal of Management & Marketing in Healthcare, 2(3), 278–292. https://doi.org/10.1179/mmh.2009.2.3.278

9. Eriksen, S., & Wiese, R. (2019). Policy induced increases in private healthcare financing provide short-term relief of total healthcare expenditure growth: Evidence from OECD countries. European Journal of Political Economy. https://doi.org/https://doi.org/10.1016/j.ejpoleco.2019.02.001
10. Folland, S., Goodman, A. C., & Stano, M. (2013). The Economics of Health and Health Care (Internatio). Routledge.
11. Gerdtham, U. G., Søgaard, J., Andersson, F., & Jönsson, B. (1992). An econometric analysis of health care expenditure: A cross-section study of the OECD countries. Journal of Health Economics, 11(1), 63–84. https://doi.org/https://doi.org/10.1016/0167-6296(92)90025-V
12. Jaba, E., Balan, C. B., & Robu, I.-B. (2014). The Relationship between Life Expectancy at Birth and Health Expenditures Estimated by a Cross-country and Time-series Analysis. Procedia Economics and Finance. https://doi.org/10.1016/S2212-5671(14)00454-7
13. Kurtzman, E. T., & Barnow, B. S. (2017). A Comparison of Nurse Practitioners, Physician Assistants, and Primary Care Physicians’ Patterns of Practice and Quality of Care in Health Centers. Medical Care, 55(6), 615–622. https://doi.org/10.1097/MLR.0000000000000689
14. Malehi, A. S., Pourmotahari, F., & Angali, K. A. (2015). Statistical models for the analysis of skewed healthcare cost data: a simulation study. Health Economics Review, 5, 11. https://doi.org/10.1186/s13561-015-0045-7
15. Mihaylova, B., Briggs, A., O’Hagan, A., & Thompson, S. G. (2011). Review of statistical methods for analysing healthcare resources and costs. Health Economics, 20(8), 897–916. https://doi.org/10.1002/hec.1653
16. Minitab. (2021). Pearson’s correlation using Minitab. Montgomery, D. C., Jennings, C. L., & Kulahci, M. (2015). Introduction to time series analysis and forecasting. John Wiley & Sons.
17. Nghiem, S. H., & Connelly, L. B. (2017). Convergence and determinants of health expenditures in OECD countries. Health Economics Review, 7(1), 29. https://doi.org/10.1186/s13561-017-0164-4
18. Pacáková, V., Jindrová, P., & Kopecká, L. (2019). Statistical Analysis of Health Inequalities in European Countries. ITM Web of Conferences, 24, 02002. https://doi.org/10.1051/itmconf/20192402002
19. Pellegrini, L. C., Rodriguez-Monguio, R., & Qian, J. (2014). The US healthcare workforce and the labor market effect on healthcare spending and health outcomes. International Journal of Health Care Finance and Economics. https://doi.org/10.1007/s10754-014-9142-0
20. Rachmani, E., Hsu, C. Y., Nurjanah, N., Chang, P. W., Shidik, G. F., Noersasongko, E., Jumanto, J., Fuad, A., Ningrum, D. N. A., Kurniadi, A., & Lin, M. C. (2019). Developing an Indonesia’s health literacy short-form survey questionnaire (HLS-EU-SQ10-IDN) using the feature selection and genetic algorithm. Computer Methods and Programs in Biomedicine. https://doi.org/10.1016/j.cmpb.2019.105047
21. Radeschi, G., Urso, F., Campagna, S., Berchialla, P., Borga, S., Mina, A., Penso, R., Di Pietrantonj, C., & Sandroni, C. (2015). Factors affecting attitudes and barriers to a medical emergency team among nurses and medical doctors: A multi-centre survey. Resuscitation, 88, 92–98. https://doi.org/10.1016/j.resuscitation.2014.12.027
22. Siciliani, L., Stanciole, A., & Jacobs, R. (2009). Do waiting times reduce hospital costs? Journal of Health Economics, 28, 771–780.
23. Svensson, R. (1996). The interplay between doctors and nurses -- a negotiated order perspective.
24. Sociology of Health and Illness, 18(3), 379–398. https://doi.org/10.1111/1467- 9566.ep10934735
25. TUIK. (2021). Sağlık İstatistikleri, istatistiksel Tablolar ve Dinamik Sorgulama. Türkiye İstatistik Kurumu. https://tuikweb.tuik.gov.tr/PreTablo.do?alt_id=1095
26. Yang, X. (2019). Health expenditure, human capital, and economic growth: an empirical study of developing countries. International Journal of Health Economics and Management, 1–14. https://doi.org/10.1007/s10754-019-09275-w