AI in Healthcare: Unlocking Operational Intelligence through RTLS Systems for Healthcare
In today’s healthcare landscape, hospitals and health systems are under immense pressure to do more with less—delivering high-quality care, optimizing staff utilization, and managing costly equipment. Traditional reporting systems fall short in this environment. What healthcare providers need is a more dynamic, real-time capability powered by solutions like a Healthcare RTLS system and AI-driven analytics: operational intelligence.
What is Operational Intelligence in Healthcare?
Operational intelligence (OI) refers to the ability to understand, optimize, and act on the day-to-day functioning of a hospital using real-time data and AI-powered analytics. It moves beyond historical reporting by allowing administrators and clinical leaders to respond as situations unfold. It connects data from disparate systems—location data, scheduling platforms, electronic health records—and converts them into actionable insights that improve care delivery, resource utilization, and workflow efficiency.
Operational Intelligence in 2025
In 2025, operational intelligence is being realized through the convergence of real-time data streams and machine learning. Hospitals are deploying location-aware technologies like Real-Time Location Systems (RTLS), integrating them with hospital information systems (HIS), and applying AI models to optimize everything from staff movement to equipment availability.
Recent research indicates roughly 20% of hospitals now have some form of RTLS infrastructure in place, and more than 60% are actively exploring AI integration for operational use cases. Increasingly, health systems are moving from smart infrastructure to truly intelligent operations—anticipating issues before they arise and orchestrating resources proactively.
The Role of Location in Operational Intelligence
The location of staff, patients, and assets provides critical context for understanding operational performance. Knowing that a ventilator is idle in one ward while another department is searching for one is no longer just a logistical issue—it’s a patient safety risk. Similarly, tracking clinician movement across units reveals patterns of inefficiency, unnecessary fatigue, or burnout.
Location-based data answers questions like:
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Where are critical assets right now?
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How long are patients waiting between care stages?
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Are staff workflows aligned with care protocols?
This foundational awareness sets the stage for AI to derive insight and recommend actions.
RTLS as a Foundation for Operational Intelligence
RTLS provides the spatial and temporal data that makes operational intelligence possible. On its own, RTLS can help staff locate assets or monitor patient movement. But when paired with AI and integrated with hospital systems, it becomes an engine for continuous improvement.
For instance, real-time alerts can be generated when an infusion pump leaves a designated floor. Predictive analytics can forecast future equipment shortages based on historical utilization. Staff workflow data can be correlated with patient outcomes or safety incidents. The key is integration—RTLS must not operate in isolation.
Integrating RTLS with Other Healthcare Systems
The full power of operational intelligence emerges when RTLS is tied into clinical and administrative systems. Integrating RTLS with electronic health records allows location data to be tied to patient episodes. Nurse call systems can use staff proximity to optimize alert routing. Bed management systems can track patient movement and accelerate discharge processes.
This cross-system data fusion enables a shift from siloed reaction to coordinated, intelligent action.
Example: RTLS + AI for Asset Utilization Optimization
Let’s walk through a specific use case—optimizing IV pump utilization using RTLS and AI.
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Data Collection:
RTLS infrastructure captures the location of every IV pump in the hospital, storing movement and dwell times in a central database (e.g., PostgreSQL or TimescaleDB). -
Data Preparation:
Raw location data is preprocessed using Python and Pandas. Records are enriched with metadata (e.g., pump type, department, assigned patient). -
Feature Engineering:
Using scikit-learn and NumPy, features such as idle time, relocation frequency, and average usage per shift are extracted. Time-series trends are generated using libraries like tsfresh. -
Modeling and Insight Generation:
A machine learning model (e.g., XGBoost or LightGBM) is trained to classify usage patterns into underutilized, optimally used, or over-utilized. Anomalies—such as units with unusually high idle time—are flagged. -
Operational Dashboard:
Insights are presented via a dashboard built using Streamlit or Power BI. Decision-makers can see which departments are hoarding pumps or which units have persistent shortages. Alerts can be generated when a pump exceeds a predefined idle threshold. -
Workflow Action:
The hospital’s logistics team is automatically notified to redistribute idle equipment. If patterns persist, purchasing decisions and staff training may be adjusted accordingly.
This is a clear example of how location data is transformed into operational intelligence through the layered application of data engineering, machine learning, and user-friendly visualization.
Additional Use Cases: Burnout Detection and Beyond
One compelling example of operational intelligence is clinician burnout detection. RTLS data, when correlated with shift schedules, EMR interactions, and patient assignments, can help AI models estimate stress levels, movement fatigue, and cognitive overload. Proactive interventions—such as adjusting assignments or providing mental health support—can be triggered long before burnout results in turnover or clinical error.
Other emerging use cases include:
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Predicting bottlenecks in emergency departments
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Optimizing environmental cleaning schedules based on occupancy
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Automating contact tracing during infection outbreaks
Conclusion: Let’s Build the Intelligent Hospital Together
Penguin Location Services is at the forefront of operational intelligence in healthcare. Our RTLS platform integrates with hospital systems, delivering real-time visibility and AI-powered insight at scale. Whether you’re tackling asset utilization, staff optimization, or patient safety—we can help you build a more intelligent, responsive healthcare facility.
Reach out today to learn how Penguin can bring operational intelligence to your hospital. Contact Us
