The goal of sustainable development in health is to promote wellness and healthy living. Within this context, we highlight two collaborative projects:
Instituto Marquês Vale Flôr (IMVF)
Quidgest established one of them with Instituto Marquês Vale Flôr (IMVF). The Non-Governmental Development Organization (NGDO) aims to contribute to sustainable development and promotion of human dignity through the design, implementation, and collaboration in projects and activities in a wide range of areas. The gap in the supply of medicines and health goods in remote areas, especially in African countries such as Guinea-Bissau, is one of the challenges IMVF planned to solve.
A project of Stock Management and Transportation of Pharmaceutical Products emerged from the joint effort. Quidgest developed an information system that allows stock management – from transportation to storage – to organize the distribution through healthcare centers. Mitigating product losses, controlling stock limits, expiration dates, alerts, creating automatic deliveries with forecasts of expenses and shortages are vital points for the process to be successful. The logistics in a country “organized” and with adequate infrastructure is a challenge. In Guinea-Bissau, it has become an epic quest.
Santa Marta Hospital
Another close collaboration project, which falls under Research and Development, arose with the Santa Marta Hospital. The challenge is to use a data registry of cardiac patients who have undergone a surgical intervention and turn it into a useful clinical support tool, enabling information share and analysis.
Each year, an estimated 17 million people die globally from cardiovascular disease. According to 2020 data from the American Heart Association, about 80% of premature deaths can be prevented by controlling major risk factors and making timely and accurate clinical decisions. The creation of a digital cardiac platform, enabling real-time, hands-on clinical decision support and data analysis for healthcare professionals, is of utmost necessity. The passage from “paper” to digital is thus the milestone of this project, which intends to extract information from data effectively. A significant challenge arises from the outset: to make the data robust, reliable, and reproducible (enhancing the quality and quantity of data – standardization).
The development of predictive models for “Operation Risk” and “Post-Surgery Rehabilitation” integrated into the platform is a critical point in this project, which will leverage the artificial intelligence of the Genio framework and thus develop algorithms adapted through Machine Learning tools.
Another major challenge within this project arises from obtaining large-scale data to feed the database and make the model more robust. Therefore, it is a pressing need to create a collaborative network between hospitals, research, and technology centers, which will enable an integrated system of information sharing and make the predictive models more robust and reliable.