AI-Powered Health Supply Chains Avoid Shortages

AI can improve cost-effective deliveries and create a resilient, predictive supply chain and avoid shortages in this essential industry. 

Many diseases beyond COVID-19 require a continuous supply of resources to correctly address patients’ needs. For example, only 1 percent of clinics and 14 percent of hospitals in low and middle-income countries have the equipment or staff they need to diagnose endemic diseases, such as HIV, tuberculosis and malaria, according to the MIT Technology Review.

These limitations represent a large gap on health supply chains that could be successfully tackled by increasing the level of automation in supply chain management, said Andrés Posada, Supply Chain Manager Mexico and Central America, Boston Scientific. For example, “within the medical devices industry, the implementation of AI is being explored to improve logistics distribution,” he said.

While a certain level of automation is already a feature of most supply chain models, these systems still require human intervention despite having complex algorithms predicting demand and aiding forecasting. As AI and other tools such as machine learning become more accessible, the opportunities to have a completely automated system arise.

AI can facilitate better planning for the types of services and products needed to support patient care. Furthermore, it can help ensure products are available where needed by helping predict potential backorders or shortages, while avoiding overstocking products that are at risk of expiring before use.

Aside from material provision, AI has been used to source understaffed clinics or hospitals and to find the best-suited conditions for patients. For example, a project between the Foundation for Innovative New Diagnostics (FIND) and the US-Coupa used AI to suggest to an insurer the provision of a Spanish-speaking social worker and a taxi voucher for Spanish-speaking clients who do not live near a clinic.

However, this approach requires robust data that would correctly train the algorithms for a positive outcome. While many Mexican companies have large databases to support AI, the country is still behind Brazil and Argentina in data and digitalization, said Miguel Angelo Ricchiuti, Operations and Supply Chain Director Mexico and LATAM, Apotex.