A Massachusetts-based mobile integrated healthcare provider engaged Techlogix to develop a state-of-the-art business platform that enhances ease of operation, security, and rapid decision-making to improve service experiences for both patients and healthcare providers. The platform leverages Machine Learning and Generative AI to support medical staff in triage, determining medical emergencies, and assigning optimal resources for swift in-home care.

The Challenge

Like many in the healthcare industry, the customer faced a significant nursing staff shortage, particularly in the aftermath of COVID-19. With experienced nurses retiring early and the growing demand for in-home care, the need for a cutting-edge business platform became critical. This platform required embedded machine learning solutions to enhance healthcare decision-making and effectively allocate paramedics. Additionally, the urgent care business experiences strong seasonal variability in visit volumes. Accurate projection systems were essential to optimize staffing and paramedic van resources to handle these fluctuations effectively.

The Solution

Techlogix developed a robust suite of machine learning solutions to address these challenges:

• Intelligent Triage: A system based on multiple machine learning algorithms, including Gradient Descent classifiers and multi-factor correlations, supports nurses in making quick, confident decisions about whether a patient requires emergency room care, paramedic attention, or routine follow-ups. The system includes confidence measures and reasoning to assist medical staff in making informed decisions. Additionally, a Generative AI module is being developed to create detailed visit notes based on nurse inputs, streamlining communication with doctors and paramedics during in-home visits.
• PeVolume Projection Algorithm: Leveraging Meta Prophet at its core, this algorithm provides highly accurate daily and monthly visit volume forecasts by analyzing historical data, periodic patterns, and weekend/holiday effects.
• Staffing and Scheduling Optimization: Volume projections are correlated with staff attendance data to generate new staffing schedules. This ensures optimal staff availability while integrating paramedic scheduling and inventory management for better operational planning.
• Smart Resource Assignment: Patient needs, service availability, geographic location, and projected paramedic availability are used to assign paramedic companies automatically.
• Route Optimization and Geo-Tracking: Smart route planning ensures efficient use of paramedic trucks, while geo-tracking provides frequent updates to patients via a mobile app, enhancing transparency and service satisfaction.
• Smart Alerts: Real-time health condition indicators, visit volumes, and inventory levels trigger alerts to improve response times and care quality.
• User-Friendly Dashboards: Elegant dashboards provide actionable insights tailored to the needs of key users, ensuring informed decision-making at all levels.

The Technology

The machine learning models are integrated into the platform, built on an advanced microservices architecture hosted on Microsoft Azure. The models operate in compute containers, using entry scripts to process JSON-formatted inputs and YAML files for configuration. Outputs are logged into a relational data store for auditing and analysis. Azure Event Grid and Azure Data Factory facilitate seamless data flow, moving data from the production MongoDB to the relational data store and triggering ML model execution. This architecture enables efficient data processing, robust model execution, and seamless integration with the healthcare platform.

Key Benefits

• Improved Decision-Making: The intelligent triage system and Generative AI modules provide actionable insights with confidence measures, enabling faster, data-driven decisions.
• Enhanced Resource Utilization: Smart resource assignment and route optimization ensure efficient use of paramedics, trucks, and inventory, reducing costs and response times.
• Operational Efficiency: Accurate volume projections and optimized staffing schedules help the organization handle seasonal variability effectively while maintaining high-quality care.
• Better Patient Experience: Real-time updates, smart alerts, and seamless communication improve service transparency, speed, and overall patient satisfaction.
• Scalable and Secure Platform: The Azure-based microservices architecture ensures scalability, robust data processing, and secure model execution for future growth.