IntroductionThis article analyses the composition of healthcare costs for HIV/AIDS infected patients in a country with limited resources and attempts to identify the factors that influence these costs. The aims are to calculate medical care costs, analysing how they vary depending on patients’ income, and to evaluate the factors explaining healthcare consumption.MethodsThis is a prospective cohort study focusing on patients who were admitted to hospital for a short stay between January 2010 and June 2011, before their integration into a specialised program. The patients were selected randomly. Free consent was obtained from all participants. Data were analysed using the SPSS 19.0 software. The significance threshold was set at 5% and the CI (Confidence Interval) at 95%. We used Kruskal-Wallis tests, Fisher's exact test and multiple linear regression.ResultsWe monitored 209 patients. Their average age was 36.37 years (SD: 8.72). The sex ratio was 0.58 and the women patients were generally younger than the male ones (p=0.011). The overall cost of healthcare amounted to $US 41,922. The cost of Antiretroviral Therapy represented 21.6% ($US 9,045). The price of para-clinical examinations represented 46% ($US 19,136) of the overall cost. The patient's average monthly income was $US 157.40 whereas the average direct cost per patient was$US 201.45. Both monthly income (t=4.385; p=0.0000) and education level (t=3.703 p=0.0003) were statistically significant predictive factors for healthcare consumption. The medical care costs for patients with opportunistic infections were nine times higher than those for patients who presented none. The presence of opportunistic infections increased healthcare consumption by approximately 31$ US (CI 95%: 15-46.9).ConclusionThe average direct cost for patients on each short-term stay was higher than the average monthly income. To be able to access the necessary services, the patients need additional resources, which are derived from various sources. Monthly income and the level of education were both statistically significant predictors for healthcare consumption. The analysis allows us to extend the study by using different analytical accounting approaches such as by case and by pathology.

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