Hospitals are being asked to do more with less – deliver rapid connections to health care services, generate better outcomes and have tighter coordination across teams and services.
The patient is at the center of it all. Getting people the care they need, where they are and when they need it, has never been more important.
Advanced analytics play a pivotal role in helping health care organizations meet the challenge head-on. By bringing together data from across the system and turning it into clear, actionable insights, health leaders can make better decisions. Whether it’s routing an ambulance, preparing for a patient surge or coordinating staff, organizations proactively prepare.
Analytics is making an impact in several areas. Optimizing mobile care delivery, predicting patient surges and simulating patient throughput are several use cases that address improving care delivery. Moreover, analytics is taking center stage in addressing the challenge of managing both human and material resources based on service demand.
Health analytics: What it is and why it matters
Rethinking mobile care routing for better patient outcomes
Emergency medical services are the frontline responders in health care. Their ability to respond and transport patients efficiently can directly influence outcomes, especially in urgent situations. With support from real-time data, advanced analytics can help guide EMS teams along the safest and quickest routes, considering road conditions, infrastructure and the severity of a patient’s condition.
This kind of routing support not only improves response times but also ensures that critical patients receive timely medical attention and that less critical patients are routed to the most appropriate level of care.
This proactive approach reduces congestion, wait times and ensures patients receive timely care. By analyzing patterns and outcomes, healthcare providers can implement strategies to enhance resource allocation and patient experiences during critical situations.
These same capabilities extend beyond traditional EMS. For patients enrolled in hospital-at-home programs or who are receiving post-acute care medical services, advanced analytics can help plan routes, streamline coordination between care teams and improve communication. Features like real-time updates and estimated arrival times keep patients informed and support a more transparent, patient-friendly experience.
Ultimately, these improvements help providers deliver care more efficiently while enhancing the overall patient experience journey.
Anticipating demand to proactively plan resources
Caring for patients efficiently requires more than just knowing what’s happening now; it means anticipating what’s coming next. With the right analytics in place, hospital leaders can monitor current capacity in real time while also planning for shifts in patient volume.
Forecasting models can highlight potential surges before they happen by analyzing historical trends and patient flow data. Whether it’s an expected seasonal spike or something more unexpected, having early insight allows care teams to make timely decisions about staffing, bed availability and admissions.
This level of foresight helps reduce last-minute scrambles and supports a smoother, more responsive approach to hospital operations, so care teams can stay focused on patients, not just logistics.
Using digital twins to model, test and respond
When hospitals are stretched thin, there’s little room for trial and error. That’s where digital twins come in. These virtual models of hospital operations allow leaders to simulate real-world scenarios, like sudden surges in patient volume or shifts in staff availability, without disrupting care.
By connecting these models to near-real-time data, hospitals can see how changes in one part of the system might ripple through the rest. This gives leaders a better way to test different responses, adjust workflows on the fly, and make decisions grounded in insight, not guesswork. It’s a practical way to plan and respond with confidence when conditions change quickly.
Right staff, right skill, right patient
Staffing has always been a balancing act, but it’s becoming one that’s harder to manage with stretched teams and growing patient complexity. Analytics can assess patient condition and acuity and significantly enhance the process of matching nurses and other care delivery staff with specific skills to the most appropriate care delivery units and the condition and acuity of patients.
By analyzing data on nurses’ qualifications, certifications and past performance, health care facilities can create detailed profiles of each nurse’s skills and competencies for the purpose of identifying the best fit for specific care delivery units based on the required expertise. Applying this information to current and forecasted future demands based on patient condition, nurse availability and unit requirements allows health care leaders to make dynamic adjustments to staffing, aligning available staff with the right skills to the right patient.
Digital twin technology takes this a step further. By creating a virtual model of the hospital’s operations – updated in near real time – leaders can simulate changes in staffing and patient volume to understand the downstream impact. As patient conditions shift or volumes spike, digital twins can help dynamically adjust schedules and staffing assignments, ensuring teams stay balanced and care quality stays high.
Furthermore, analytics can monitor nurse workloads and distribute tasks evenly to prevent burnout and maintain high levels of care. With this, health care facilities can ensure that nurses are not overburdened and can perform at their best.
A smarter, more sustainable approach to patient flow
From the moment a patient enters the system, advanced analytics can guide smarter decisions at every step. The goal isn’t just to move patients through the system faster. It’s to connect care teams, reduce delays, automate tasks and make the overall experience for patients more responsive and more humane.
The SAS Health Analytics platform integrates all of these capabilities into one solution, offering real-time visibility, predictive insight and tools that support meaningful action.
As hospitals continue to adapt to growing demands, analytics will be key to building a system that works better for both patients and providers.
