Exploring cost drivers to improve disease management: the case of type 2 diabetes at a tertiary hospital in Burundi, Africa

Authors

  • Benitha Hezagirwa Social, Economic, and Administrative Pharmacy Program, Department of Pharmacy, Faculty of Pharmacy, Mahidol University
  • Arthorn Riewpaiboon Division of Social and Administrative Pharmacy, Department of Pharmacy, Faculty of Pharmacy, Mahidol University, Rajathevi, Bangkok https://orcid.org/0000-0003-2959-3244
  • Farsai Chanjaruporn Division of Social and Administrative Pharmacy, Department of Pharmacy, Faculty of Pharmacy, Mahidol University, Rajathevi, Bangkok

DOI:

https://doi.org/10.4081/jphia.2023.2266

Keywords:

Burundi, cost driver, economic burden, type 2 diabetes mellitus, disease management

Abstract

Background. In Burundi, the International Diabetes Federation estimated the prevalence of diabetes mellitus (DM) as high as 2.4% in adults aged between 20 and 79 years old. Thus, the healthcare expenditure for the treatment of diabetic patients is considerably high.
Objective. This study explores the economic burden of type 2 DM and its cost drivers at a tertiary hospital in 2018. It included adult type 2 DM patients who received treatment from a tertiary hospital (Hospital Prince Regent Charles) in 2018. In this study, 81 patients were included.
Methods. Data on illness treatment and complications were collected through patient interviews and by reviewing patients’ medical and financial records. A stepwise multiple linear regression model was used to explore factors affecting the cost of type 2 diabetes mellitus.
Results. The average total cost per patient per year was estimated at $2621.06. The fitted cost model had an adjusted R2 of 0.427, which explained up to 43% of the variation in the total cost. The results suggest primary cost drivers such as treatment regimen, duration of the disease, payment method, and number of complications.
Conclusion. The findings confirm the profound economic burden of type 2 DM and the need to improve patient care and prevent disease progression. The establishment of a special clinic for patients with diabetes is recommended, as is financial support for underprivileged patients. A specific focus on cost drivers could help establish appropriate disease management programs to control the costs for type 2 diabetes patients.

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References

Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: Diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998;15:539-53. DOI: https://doi.org/10.1002/(SICI)1096-9136(199807)15:7<539::AID-DIA668>3.0.CO;2-S

International Diabetes Federation. IDF Diabetes Atlas. 9th ed. https://diabetesatlas.org/en/resources/. Accessed February 21, 2020.

The DHS Program. Troisième enquête démographique et de santé (EDSB-III) au Burundi. https://dhsprogram.com/pubs/pdf/SR247/SR247.pdf. Accessed February 21, 2020 (in French).

Nsabiyumva F, Gaturagi C, Bizimana P. Etude prospective de la prise en charge du pied diabétique portant sur 21 cas dans 3 hôpitaux de Bujumbura. Méd Afr Noire 2013;60:187-92.

Ministère de la Santé et de la Lutte contre le Sida. Plan stratégique national de lutte contre les maladies chroniques non transmissibles 2011–15 (in French). https://www.iccp-portal.org/system/files/plans/BDI_B3_PS%20PNILMCNT%2029%2006%202011%5B1%5D.pdf. Accessed March 31, 2020.

Mbanya JC, Sobngwi E. Diabetes in Africa. Diabetes microvascular and macrovascular disease in Africa. J Cardiovasc Risk 2003;10:97-102. DOI: https://doi.org/10.1177/174182670301000204

Kilpatrick ES. Haemoglobin A1c in the diagnosis and monitoring of diabetes mellitus. J Clin Pathol 2008;61:977-82. DOI: https://doi.org/10.1136/jcp.2007.054304

Segel JE. Cost-of-illness studies—A primer. RTI-UNC Cent Excell Health Promot Econ 2006;2006:1-39.

Mutyambizi C, Pavlova M, Chola L, Hongoro C, Groot W. Cost of diabetes mellitus in Africa: A systematic review of existing literature. Global Health 2018;14:3. DOI: https://doi.org/10.1186/s12992-017-0318-5

Jo C. Cost-of-illness studies: Concepts, scopes, and methods. Clin Mol Hepatol 2014;20:327-37. DOI: https://doi.org/10.3350/cmh.2014.20.4.327

Hospital Prince Regent Charles. Présentation et localisation de l’Hopital Prince Regent Charles. http://www.hprc-burundi.bi/. Accessed March 31, 2020 (French).

World Health Organization. International statistical classification of diseases and related health problems, 10th 2010 Revision. World Health Organization; 2010.

Tabachnick BG, Fidell LS. Using multivariate statistics. 7th ed. Boston, Pearson; 2019.

World Health Organization. Health service delivery costs 2020. https://www.who.int/choice/cost-effectiveness/inputs/health_service/en/. Accessed April 8, 2020.

Van Houtven CH, Coe NB, Skira MM. The effect of informal care on work and wages. J Health Econ 2013;32:240-52. DOI: https://doi.org/10.1016/j.jhealeco.2012.10.006

The World Bank. GNI per capita (current LCU)-Burundi 2018. https://data.worldbank.org/indicator/NY.GNP.PCAP.CN?locations=BI. Accessed April 8, 2020.

Macrotrends. Burundi GNI per capita 1962-2020. https://www.macrotrends.net/countries/BDI/burundi/gni-per-capita. Accessed April 12, 2020.

World Health Organization. Making choices in health: WHO guide to cost-effectiveness analysis 2003. https://apps.who.int/iris/handle/10665/42699. Accessed March 29, 2020.

The World Bank. PPP conversion factor, GDP (LCU per international $)-Burundi 2018. https://data.worldbank.org/indicator/PA.NUS.PPP?locations=BI. Accessed April 12, 2020.

Cohen J, Cohen P, West SG et al. Applied multiple regression/correlation analysis for the behavioral sciences. 3rd ed. New York, Routledge; 2002.

Belsley DA, Kuh E, Welsch RE. Regression diagnostics: Identifying influential data and sources of collinearity. NJ, John Wiley & Sons; 1980. DOI: https://doi.org/10.1002/0471725153

Afifi A, May S, Clark VA. Computer-aided multivariate analysis. CRC Press; 2003.

The World Bank. The World Bank in Burundi 2019. https://www.worldbank.org/en/country/burundi/overview. Accessed April 21, 2020.

World Health Organization Regional Office for Africa. WHO African Regional Expenditure Atlas. https://apps.who.int/iris/handle/10665/145197. Accessed April 28, 2020.

Kirigia JM, Sambo HB, Sambo LG, Barry SP. Economic burden of diabetes mellitus in the WHO African region. BMC Int Health Hum Rights. 2009;9(1):6. DOI: https://doi.org/10.1186/1472-698X-9-6

Basu S, Shankar V, Yudkin JS. Comparative effectiveness and cost-effectiveness of treat-to-target versus benefit-based tailored treatment of type 2 diabetes in low-income and middle-income countries: A modelling analysis. Lancet Diabetes Endocrinol 2016;4:922-32. DOI: https://doi.org/10.1016/S2213-8587(16)30270-4

Suleiman IA, Festus JA. Cost of illness among diabetes mellitus patients in Niger Delta, Nigeria. Health Serv Res. 2015;6:53-60.

Boutayeb W, Lamlili MEN, Boutayeb A, Boutayeb S. Estimation of direct and indirect cost of diabetes in Morocco. JBiSE 2013;06:732-8. DOI: https://doi.org/10.4236/jbise.2013.67090

Tharkar S, Devarajan A, Kumpatla S, Viswanathan V. The socioeconomics of diabetes from a developing country: A population based cost of illness study. Diabetes Res Clin Pract 2010;89:334-40. DOI: https://doi.org/10.1016/j.diabres.2010.05.009

Javanbakht M, Baradaran HR, Mashayekhi A, et al. Cost-of-illness analysis of type 2 diabetes mellitus in Iran. PLOS ONE 2011;6:e26864. DOI: https://doi.org/10.1371/journal.pone.0026864

Nuhoho S, Vietri J, Worbes-Cerezo M. Increased cost of illness among European patients with type 2 diabetes treated with insulin. Curr Med Res Opin 2017;33:47-54. DOI: https://doi.org/10.1080/03007995.2016.1233099

Blonde L. Current antihyperglycemic treatment guidelines and algorithms for patients with type 2 diabetes mellitus. Am J Med 2010;123(suppl):S12-8. DOI: https://doi.org/10.1016/j.amjmed.2009.12.005

Rosenblum MS, Kane MP. Analysis of cost and utilization of health care services before and after initiation of insulin therapy in patients with type 2 diabetes mellitus. J Manag Care Pharm 2003;9:309-16. DOI: https://doi.org/10.18553/jmcp.2003.9.4.309

Bell K, Parasuraman S, Raju A, Shah M, Graham J, Denno M. Resource utilization and costs associated with using insulin therapy within a newly diagnosed type 2 diabetes mellitus population. J Manag Care Spec Pharm 2015;21:220-8a. DOI: https://doi.org/10.18553/jmcp.2015.21.3.220

Yang C, Huang Z, Sun K, Hu Y, Bao X. Comparing the economic burden of type 2 diabetes mellitus patients with and without medical insurance: A cross-sectional study in China. Med Sci Monit 2018;24:3098-102. DOI: https://doi.org/10.12659/MSM.907909

Al-Delaimy WK, Merchant AT, Rimm EB, Willett WC, Stampfer MJ, Hu FB. Effect of type 2 diabetes and its duration on the risk of peripheral arterial disease among men. Am J Med 2004;116:236-40. DOI: https://doi.org/10.1016/j.amjmed.2003.09.038

Mash R, Kroukamp R, Gaziano T, Levitt N. Cost-effectiveness of a diabetes group education program delivered by health promoters with a guiding style in underserved communities in Cape Town, South Africa. Patient Educ Couns 2015;98:622-6. DOI: https://doi.org/10.1016/j.pec.2015.01.005

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Published

19-04-2023

How to Cite

Hezagirwa, B., Riewpaiboon, A., & Chanjaruporn, F. (2023). Exploring cost drivers to improve disease management: the case of type 2 diabetes at a tertiary hospital in Burundi, Africa. Journal of Public Health in Africa, 14(4). https://doi.org/10.4081/jphia.2023.2266

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Original Articles