Are State-Sponsored New Radiation Therapy Facilities Economically Viable in Low- and Middle-Income Countries?

• Published in: International journal of radiation oncology, biology, physics Vol. 93; no. 2; pp. 229 - 240
• Main Authors: Datta, Niloy R., MD, Samiei, Massoud, PhD, Bodis, Stephan, MD
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.10.2015
• Subjects: BREAKEVEN; CALCULATION METHODS; Cancer Care Facilities - economics; Cancer Care Facilities - organization & administration; Cancer Care Facilities - supply & distribution; COST; Cost-Benefit Analysis; Developing Countries - classification; Developing Countries - economics; ECONOMICS; EMPLOYMENT; Employment - economics; Employment - statistics & numerical data; ENERGY PLANNING, POLICY AND ECONOMY; Facility Design and Construction - economics; Financing, Government; Gross Domestic Product; Health Expenditures - statistics & numerical data; Hematology, Oncology and Palliative Medicine; HOSPITALS; Humans; INCOME; INVESTMENT; Neoplasms - mortality; Neoplasms - radiotherapy; PATIENTS; POPULATIONS; Radiology; RADIOLOGY AND NUCLEAR MEDICINE; RADIOTHERAPY; Radiotherapy - economics; Radiotherapy - instrumentation; Regression Analysis; Survivors; Time Factors; WORLD BANK
• ISSN: 0360-3016; 1879-355X
• DOI: 10.1016/j.ijrobp.2015.05.036

Purpose The economic viability of establishing a state-funded radiation therapy (RT) infrastructure in low- and middle-income countries (LMICs) in accordance with the World Bank definition has been assessed through computation of a return on investment (ROI). Methods and Materials Of the 139 LMICs, 100 were evaluated according to their RT facilities, gross national income (GNI) per capita, and employment/population ratio. The assumption was an investment of US$5 million for a basic RT center able to treat 1000 patients annually. The national breakeven points and percentage of ROI (%ROI) were calculated according to the GNI per capita and patient survival rates of 10% to 50% at 2 years. It was assumed that 50% of these patients would be of working age and that, if employed and able to work after treatment, they would contribute to the country's GNI for at least 2 years. The cumulative GNI after attaining the breakeven point until the end of the 15-year lifespan of the teletherapy unit was calculated to estimate the %ROI. The recurring and overhead costs were assumed to vary from 5.5% to 15% of the capital investment. Results The %ROI was dependent on the GNI per capita, employment/population ratio and 2-year patient survival (all P <.001). Accordingly, none of the low-income countries would attain an ROI. If 50% of the patients survived for 2 years, the %ROI in the lower-middle and upper-middle income countries could range from 0% to 159.9% and 11.2% to 844.7%, respectively. Patient user fees to offset recurring and overhead costs could vary from “nil” to US$750, depending on state subsidies. Conclusions Countries with a greater GNI per capita, higher employment/population ratio, and better survival could achieve a faster breakeven point, resulting in a higher %ROI. Additional factors such as user fees have also been considered. These can be tailored to the patient's ability to pay to cover the recurring costs. Certain pragmatic steps that could be undertaken to address these issues are discussed in the present study.