Smart Work Injury Management (SWIM) System: Artificial Intelligence in Work Disability Management

Area of Science:

• Occupational Health
• Data Science
• Artificial Intelligence

Background:

• Effective management of work injuries is crucial for worker well-being and economic stability.
• Current systems often lack advanced analytical capabilities for predicting injury outcomes and facilitating return-to-work (RTW).

Purpose of the Study:

• To develop and illustrate the Smart Work Injury Management (SWIM) system, a cloud-based platform for managing work injury data.
• To leverage artificial intelligence (AI) and text-mining for in-depth analysis of injury case files.
• To create predictive models for work injury costs and RTW trajectories.

Main Methods:

• Stage one involved identifying RTW facilitators and barriers through stakeholder interviews and focus groups.
• Stage two focuses on developing an AI-powered machine learning model using text-mining, principal component analysis, and advanced neural networks (Variational Autoencoder, LSTM, Neural Turing Machines).
• Development includes an interactive dashboard and website for querying the model. Stage three is for field testing the SWIM system.

Main Results:

• The SWIM system is designed as a secure, centralized cloud platform for data storage, analytics, and machine learning.
• AI-driven text-mining will extract dynamic and static data from case files, including sociodemographic information.
• The system aims to provide accurate prediction models for injury costs and RTW outcomes.

Conclusions:

• The SWIM system offers a comprehensive approach to work injury management through advanced data analytics and AI.
• It has the potential to significantly improve predictions for injury costs and RTW success.
• The system will provide valuable advice on medical care and RTW interventions to all stakeholders.