Automatic Idea Detection: Implementing artificial intelligence in medical technology innovation (AID)

Summary

Healthcare-associated infections (HAIs) are among the major causes of death of hospitalized patients. HAIs led to patient suffering, hospital budget overruns, and several economic and social challenges such as antibiotic control policies, prolonged stays, and infection control programs with high alternative costs for staff and resources. Preventing and controlling HAIs are extremely difficult because of a) the complexity of implementing sustained improvements in hospitals, b) lack of ways to analyze staff behaviour in real-time, and c) presence of emergent pathologies that require constant innovative prevention and control practices.

A proposed way to better understand HAIs prevention and control practices is to use Automatic Idea Detection (AID) systems. AID system refers to classification algorithms that can screen large amounts of information and identify those likely to contain ideas/solutions. AID system can be used to scan healthcare online platforms and identify innovative ideas/solutions. It can yield a range of benefits, such as acceleration of medical discovery, identification of emergent practices, systematic scanning of databases, and greater efficiency in revealing novel procedures. Despite these benefits, healthcare organizations face immense challenges in developing and implementing AID systems, given the move's systemic transformation.

This multidisciplinary research project addresses these issues from an ecosystem's perspective by focusing on value creation and the role and nature of complementarities in developing an AID system. The project partners include Halmstad University and other global healthcare organizations engaged in preventing and controlling HAIs.