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

A new way to seize innovative healthcare practices is to screen online health platforms to identify novel and feasible solutions. Artificial intelligent algorithms can screen vast amounts of information and automatically detect user‐contributed ideas. This algorithm is called automatic idea detection or AID.


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.

About the project

Project period:

April 2021 to March 2024


The Knowledge Foundation

Project leader:

Fábio Gama, Assistant Professor in Healthcare Innovation, Halmstad University

Other participating researchers:

  • Peyman Mashhadi, Assistant Professor in Machine Learning, Halmstad University
  • Mahmoud Rahat, Assistant Professor in Natural Language Processing, Halmstad University
  • Jens Nygren, Professor in Healthcare and AI, Halmstad University
  • Magnus Holmèn, Professor in Business model, Halmstad University
  • Slamowir Nowaczyk, Professor in Machine Learning, Halmstad University
  • Carina Göransson, Assistant Professor in Healthcare, Halmstad University
  • Hanna Johnsson, Master Student, Halmstad University
  • Chaithanya Anjanappa, Master Student, Halmstad University
  • Manisha Gurung, Master Student, Halmstad University
  • Amir Gharaie, PhD Student, Linköping University
  • Zahra Kharazian, PhD Student, Stockholm University

Project partners:

  • Håkan Lindström, Global Technical Innovation Manager, Essity
  • Peter Blomström, Global Brand Service Director, Essity
  • Jens Backman, Clinician, Region Västerbotten