Modelling the Variation of the Impact of Medical Personnel Availability on Mortality Rates: Cardiovascular Disease Case

Alexander E. Drozd, Artur R. Nagapetyan

Far Eastern Federal University, Vladivostok, Russia

Abstract

. The study attempts to empirically assess the impact of socio-economic and demographic characteristics of areas on the influence of the level of cardiologist availability on mortality rates from circulatory system disease. This research question with regards to improving the accuracy of the estimates under consideration is important for the implementation of the approach proposed in the literature to determine the optimal volume of specialist medical personnel on the basis of the Samuelson equation, which determines its relevance. It is necessary to develop approaches for estimating the marginal utility function of hiring additional specialist medical personnel for further comparison with the corresponding marginal cost function. To solve the problems of endogeneity, we use the instrumental variable method with the author's approach to constructing sources of exogenous variation based on spatial matrices and the approach to clustering areas using the k-means method. According to the obtained results, a higher statistically significant impact of profile medical personnel was observed in the territories characterised by higher values of such indicators as the share of elderly people, the share of urban population, real income per capita, alcohol consumption, tobacco consumption, total marriage rate and a lower value of the poverty rate. The variation in the estimates of the impact of the level of availability of cardiologists on mortality rates from circulatory system diseases in the considered subgroups of the federal districts of the Russian Federation was also demonstrated. In particular, the highest value of the corresponding coefficient is observed in the Central Federal District, while in such Federal Districts as the Southern Federal District, the North Caucasian Federal District, the Far Eastern Federal District, and the Siberian Federal District its value is significantly lower than the average Russian level, which was also observed in such federal districts as the Northwestern Federal District, the Volga Federal District, and the Urals Federal District. The results obtained can significantly improve the targeting of management decisions in the healthcare sector in terms of improving the validity of the level of provision of specialist medical personnel in different territories, both in terms of determining its optimal level and in terms of comparing the return on hiring medical personnel of different profiles.

Keywords

CVD mortality; cardiologists; health economics; impact variation; socio-economic factors; instrumental variable method; decision-making; quasi-experimental methods

JEL classification

References

1. Kehr, J. (2023). The moral economy of universal public healthcare. On healthcare activism in austerity Spain. Social Science & Medicine, Vol. 319, 115363. https://doi.org/10.1016/j.socscimed.2022.115363

                2. Sarbaji, C., Kumar Dwibedi, J., Biswas, A. (2017). Subsidizing healthcare in the presence of market distortions. Economic Modeling, Vol. 64, 539–552. https://doi.org/10.1016/j.econmod.2017.04.011

                3. Samuelson, P. (1954). The Pure Theory of Public Expenditure. Journal of Political Economy, Vol. 56, No. 4, 496–505. http://dx.doi.org/10.2307/1925895

                4. Nagapetyan, A., Drozd, A., Subbotovsky, D. (2023). How to Determine the Optimal Number of Cardiologists in a Region? Mathematics, Vol. 11, Issue 21, 4422. https://doi.org/10.3390/math11214422

                5. Subbotovsky, D., Kalashnikov, V., Drozd, A., Nagapetyan, A. (2023). The Impact of the Supply of Oncologists on Mortality from Neoplasms in the Regions of Russia. Journal of Applied Economic Research, Vol. 22, No. 4, 892–931. (In Russ.). https://doi.org/10.15826/vestnik.2023.22.4.036

                6. Cochrane, A.L., Leger, A.S.St., Moore, F. (1978). Health service 'Input' and mortality 'Output' in developed countries. Journal of Epidemiology & Community Health, Vol. 32, Issue 3, 200–205. https://doi.org/10.1136/jech.32.3.200

                7. Palmer, R.H., Reilly, M.C. (1979). Individual and institutional variables which may serve as indicators of quality of medical care. Medical Care, Vol. 17, Issue 7, 693–717. https://doi.org/10.1097/00005650-197907000-00001

                8. Hopkins, Z.H., Moreno, C., Carlisle, R., Secrest, A.M. (2019). Melanoma prognosis in the United States: Identifying barriers for improved care. Journal of the American Academy of Dermatology, Vol. 80, Issue 5, 1256–1262. https://doi.org/10.1016/j.jaad.2019.01.003

                9. Martinez, D., Zhang, H., Bastias, M., et al. (2019). Prolonged wait time is associated with increased mortality for Chilean waiting list patients with non-prioritized conditions. BMC Public Health, Vol. 19, 233. https://doi.org/10.1186/s12889-019-6526-6

                10. Prentice, J., Pizer, S. (2007). Delayed access to health care and mortality. Health Services Research, Vol. 42, Issue 2, 644–662. https://doi.org/10.1111%2Fj.1475-6773.2006.00626.x

                11. Hartigan, J., Wong, M. (1979). Algorithm AS 136: A K-means clustering algorithm. Applied Statistics, Vol. 28, No. 1, 100–108. https://doi.org/10.2307/2346830

                12. Ge, Y., Zhang, L., Gao, Y., Wang, B., Zheng, X. (2022). Socio-economic status and 1 year mortality among patients hospitalized for heart failure in China. ESC Heart Failure, Vol. 9, Issue 2, 1027–1037. https://doi.org/10.1002/ehf2.13762

                13. Wang, T., Li, Y., Zheng, X. (2023). Association of socioeconomic status with cardiovascular disease and cardiovascular risk factors: a systematic review and meta-analysis. Journal of Public Health, Vol. 21, 385–399. https://doi.org/10.1007/s10389-023-01825-4

                14. Lemstra, M., Rogers, M., Moraros, J. (2015). Income and heart disease: Neglected risk factor. Canadian Family Physician, Vol. 61, Issue 8, 698–704. Available at: https://pubmed.ncbi.nlm.nih.gov/26836056/

                15. Khan, N., Javed, Z., Acquah, I., et al. (2023). Low educational attainment is associated with higher all-cause and cardiovascular mortality in the United States adult population. BMC Public Health, Vol. 23, 900. https://doi.org/10.1186/s12889-023-15621-y

                16. Ma, Y., Nolan, A., Smith, J.P. (2018). The value of education to health: Evidence from Ireland. Economics and Human Biology, Vol. 31, 14–25. https://doi.org/10.1016/j.ehb.2018.07.006

                17. Larsson, S., Wallin, A., Wolk, A. (2018). Alcohol consumption and risk of heart failure: Meta-analysis of 13 prospective studies. Clinical Nutrition, Vol. 37, Issue 4, 1247–1251. https://doi.org/10.1016/j.clnu.2017.05.007

                18. Wood, A., Kaptoge, S., Butterworth, A., et al (2018). Risk thresholds for alcohol consumption: combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies. Lancet, Vol. 391, Issue 10129, 1513–1523. https://doi.org/10.1016/S0140-6736(18)30134-X

                19. Banks, E., Joshy, G., Korda, R., et al. (2019). Tobacco smoking and risk of 36 cardiovascular disease subtypes: fatal and non-fatal outcomes in a large prospective Australian study. BMC Medicine, Vol. 17, 128. https://doi.org/10.1186/s12916-019-1351-4

                20. Gallo, W., Teng, H., Falba, T., Kasl, S.V., Krumholz, H., Bradley, E. (2006). The impact of late career job loss on myocardial infarction and stroke: a 10 year follow up using the health and retirement survey. Occupational and Environmental Medicine, Vol. 63, Issue 10, 683–687. https://doi.org/10.1136/oem.2006.026823

                21. Mikkola, T., Gissler, M., Merikukka, M., Tuomikoski, P., Ylikorkala, O. (2013). Sex differences in age-related cardiovascular mortality. PloS ONE, Vol. 8, Issue 5, e63347. https://doi.org/10.1371/journal.pone.0063347

                22. Rosjidi, C., Isroin, L., Wahyuni, N. (2017). Differences in Risk Factor of Cardiovascular Disease Risk on Rural and Urban Population. Journal Kesehatan Masyarakat, Vol. 13, No. 1, 69–76. https://doi.org/10.15294/kemas.v13i1.4174

                23. Asadi, Z., Ghazizadeh, H., Yaghooti, M., et al. (2020). Role of Socio-demographic, Lifestyle, Psychological and Anthropometric Parameters on Cardiovascular Disease Risk Among Mashad Cohort Study Population. Preprint. https://doi.org/10.21203/rs.3.rs-35931/v1

                24. Ha, N., Hendrie, D., Moorin, R. (2014). Impact of population ageing on the costs of hospitalisations for cardiovascular disease: A population-based data linkage study. BMC Health Services Research, Vol. 14, 554. https://doi.org/10.1186/s12913-014-0554-9

                25. Wong, C., Kwok, C., Narain, A., et al. (2018). Marital status and risk of cardiovascular diseases: a systematic review and meta-analysis. Heart, Vol. 104, Issue 23, 1937–1948. https://doi.org/10.1136/heartjnl-2018-313005

                26. Pope, C.A., Burnett, R.T., Thurston, G.D., Thun, M.J., Calle, E.E., Krewski, D., Godleski, J.J. (2004). Cardiovascular mortality and long-term exposure to particulate air pollution: epidemiological evidence of general pathophysiological pathways of disease. Circulation, Vol. 109, No. 1, 71–77. https://doi.org/10.1161/01.cir.0000108927.80044.7f

                27. Catling, L., Abubakar, I., Lake, I., Swift, L., Hunter, P. (2008). A systematic review of analytical observational studies investigating the association between cardiovascular disease and drinking water hardness. Journal of Water and Health, Vol. 6, Issue 4, 433–442. https://doi.org/10.2166/wh.2008.054

                28. Sundmacher, L., Busse, R. (2011). The impact of physician supply on avoidable cancer deaths in Germany. A spatial analysis. Health Policy, Vol. 103, Issue 1, 53–62. https://doi.org/10.1016/j.healthpol.2011.08.004

                29. Simionescu, M., Bilan, S., Gavurova, B., Bordea, E. (2019). Health Policies in Romania to Reduce the Mortality Caused by Cardiovascular Diseases. International Journal of Environmental Research and Public Health, Vol. 16, Issue 17, 3080. https://doi.org/10.3390/ijerph16173080

                30. Gavurová, B., Toth, P., Čiutienė, R., Tarhaničová, M. (2019). The impact of healthcare availability on the amenable mortality: Country study. Economics and Sociology, Vol. 12, No. 3, 236–250. https://doi.org/10.14254/2071-789X.2019/12-3/16

                31. Farahani, M., Subramanian, S., Cannin, D. (2009). The effect of changes in health sector resources on infant mortality in the short-run and the long-run: A longitudinal econometric analysis. Social Science & Medicine, Vol. 68, Issue 11, 1918–1925. https://doi.org/10.1016/j.socscimed.2009.03.023

                32. Sundmacher, L., Kopetsch, T. (2015). The impact of office-based care on hospitalizations for ambulatory care sensitive conditions. The European Journal of Health Economics, Vol. 16, 365–375. https://doi.org/10.1007/s10198-014-0578-4

                33. Wang, Y., Pang, S., Yang, Y. (2021). A potential association between immunosenescence and high COVID-19 related mortality among elderly patients with cardiovascular diseases. Immun Ageing, Vol. 18, 25. https://doi.org/10.1186/s12979-021-00234-z

                34. Song, S., Guo, C., Wu, R., Zhao, H., Li, Q., Dou, J.-H., Guo, F.-S., Wei, J. (2024). Impact of the COVID-19 pandemic on cardiovascular mortality and contrast analysis within subgroups. Frontiers in Cardiovascular Medicine, Vol. 11, 1279890. https://doi.org/10.3389%2Ffcvm.2024.1279890

                35. Bunova, S., Okhotnikova, P., Skirdenko, Y., Nikolaev, N., Osipova. O., Zhernakova, N. (2021). COVID-19 and cardiovascular comorbidity: novel approaches to reduce mortality. Cardiovascular Therapy and Prevention, Vol. 20, No. 4, 2953. (In Russ.). https://doi.org/10.15829/1728-8800-2021-2953

                36. Drozd, A., Nagapetyan, A. (2023). Evaluation of the Influence of the Federal Center for Cardiovascular Surgery on Cardiovascular Disease Detection Rates in Penza Region. Theory and Practice of Social Development, No. 2, 95–102. (In Russ.). https://doi.org/10.24158/tipor.2023.2.13

                37. Nagapetyan, A., Subbotovsky, D., Pavlova, T., Li, J. (2024). How does the level of morbidity affect the indicator of real income of the population in the regions of the Russian Federation? Terra Economicus, Vol. 22, No. 2, 77–95. (In Russ.). http://dx.doi.org/10.18522/2073-6606-2024-22-2-77-95

Acknowledgements

The article was funded by the project “Spatial-autoregressive analysis of morbidity indicators for various classes of diseases in the regions of the Russian Federation”, as part of the implementation of the agreement on donation of funds, dated 19 May 2022, no. D-156-22 of the FEFU Endowment Fund to finance the winning projects from an open competition to support research and applied projects for the period from 7 February 2022 to 31 December 2024, from the FEFU School of Economics and Management, using income from the trust management of the target capital “FEFU Strategic Projects” (designated donation of the SBER (PJSC) for the development of SEM).

About Authors

Alexander Evgenyevich Drozd

Post-Graduate Student, Assistant, Department of Applied Economics, School of Economics and Management, Far Eastern Federal University, Vladivostok, Russia (690922, Primorsky Krai, Vladivostok, Russky Island, Ajax settlement, 10); ORCID https://orcid.org/0000-0001-6940-8491 e-mail: drozd.ae@dvfu.ru

Artur Rubikovich Nagapetyan

Candidate of Economic Sciences, Associate Professor, Department of Socio-Economic Research and Regional Development, School of Economics and Management, Head of the Laboratory of Data Analysis and Applied Econometric Research, Far Eastern Federal University, Vladivostok, Russia (690922, Primorsky Krai, Vladivostok, Russky Island, Ayaks settlement, 10); ORCID https://orcid.org/0000-0002-7885-2460 e-mail: nagapetyan_ar@dvfu.ru

For citation

Drozd, A.E., Nagapetyan, A.R. (2024). Modelling the Variation of the Impact of Medical Personnel Availability on Mortality Rates: Cardiovascular Disease Case. Journal of Applied Economic Research, Vol. 23, No. 4, 1017-1054. https://doi.org/10.15826/vestnik.2024.23.4.040

Article info

Received August 19, 2024; Revised September 7, 2024; Accepted September 21, 2024.

DOI: https://doi.org/10.15826/vestnik.2024.23.4.040

Download full text article: