Bayesian Analysis of Financial Impact of Cardiovascular Diseases in LAUTECH Teaching, Hospital, Oyo State, Nigeria
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Abstract
cardiovascular diseases (CVDs) remain a major health challenge in Nigeria that leads to high morbidity, mortality, and financial burden. Low- and middle-income countries (LMIC), with no exception to Nigeria, are suffering from high hospitalization costs for treating CVDs. The cost leads to Monthly Financial Loss (MFL) and prolonged treatments. In literature, there is a dearth of study on Financial Impact (FI) for treating CVDs in Nigeria.
Objective— This work is aimed at evaluating the FI where there is prior information about CVDs at LAUTECH Teaching Hospital (LTH).
Method— Bayesian Multinomial Logistic Regression (BMLR) is explored to evaluate the MFL incurred by CVD patients at LTH and the type of CVDs contributing to it.
Result— The results show that there is a probability of having MFL among different CVD patients in LTH.
Conclusion— Policymakers in health sectors should implement targeted financial aid for the treatment of CVDs to address the different MFL.
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Multinomial logistic, financial aid, financial loss, prior information, and Bayesian







