The Monte Carlo Model as a Tool for Estimating the Economic Burden of Ectopic Pregnancy by Predicting Future Cases

OBJECTIVES: To assess the accuracy of the Monte Carlo model in predicting healthcare costs by comparing observed and calculated expenses in the treatment of patients diagnosed with ectopic pregnancy at a Mexican public health institution.

METHODS: The medical records of 42 women diagnosed with ectopic pregnancy were reviewed to calculate the total healthcare expenditure during their treatment. Subsequently, the Monte Carlo predictive mathematical model was developed to estimate expenditures, considering inflation for each period, over a 5-year projection. This model accounts for the same clinical characteristics, including emergency care, hospitalization days, use of ultrasonography, intervention in tocosurgery, surgical interventions, blood bank services, dressings, pathological anatomy studies, and specialty consultations. The sample consisted of cases reported at a Mexican public health institution.

RESULTS: An increase in the total number of pregnancies attended to in the medical unit was observed, in line with the population growth rates established by the National Institute of Statistics and Geography for Sinaloa, Mexico. A maximum increase of 2 new cases was noted during the last period. This controlled increase contributes to a rise in the projected expenditure for the care of patients with ectopic pregnancy. The current average cost per patient is $85,736 MXN, and the average cost projected for the sample in 5 years is estimated to be $107,461.46 MXN.

CONCLUSIONS: The Monte Carlo predictive model could prove to be a useful tool in estimating healthcare service expenditures and calculating a budget that closely aligns with the actual cost.