Mathematical modeling of medical equipment needs for public health purposes

Abstract

Abstract Issue A public health challenge facing many developing countries is the lack of medical equipment, such as mammograms and CT scanners, as well as the unequal access to available equipment. In order to rationalize costs and provide patients with more equal access to preventive and diagnostic services, optimized distribution based on actual needs, considering factors such as population structure and private sector capacities is necessary. The suggested optimization was made in cooperation between students of public health, applied mathematics, and information technology. Description of the problem Based on Open data released by the institutions of Republic of Serbia, pertaining to radiological equipment operated by state healthcare facilities over a period of three years (2015, 2016 and 2017) and projected population, by sex, age, and region, a mathematical model has been made, aimed at optimizing equipment distribution across the 4 regions. With the goal of finding an adequate model, region and year specific data were used for calculating the Gini coefficient. Multiple alternatives were tested over a period of a few months, with the results displayed graphically, using a web application presenting the equipment distribution. Results In maximizing the territory covered, the availability of the equipment to the patients was increased, and with it, the equipment’s utility. The results indicate savings can be achieved, taking into consideration the capacities of the private sector. Lessons An adequate mathematical model can contribute to a better distribution of equipment, as well as cost saving. Taking into consideration that inadequate funding is one of the major challenges faced by state healthcare services worldwide, with appropriate data, the model would find use in other countries as well. Key messages Open medical data opens up new space for action by the interested parties. Inter-professional cooperation holds great potential in solving public health problems.

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