From intuition to objective, data-driven care allocation. AZ Alma, a 500 bed general hospital in Eeklo, Belgium, has been using Team n Time for several years to measure nursing workload and care intensity across its wards. Today, it becomes the first hospital to connect the platform directly to the nexuzhealth Electronic Health Record (EHR), enabling patient-level care weighting based on real-time clinical data.
This groundbreaking integration allows AZ Alma to move beyond general averages and instead calculate precise workload per patient—resulting in more balanced staffing decisions and transparent discussions around workload.
“Before Team n Time, we mainly worked on gut feeling,” says Jeffrey De Laere, care group manager and project lead for Team n Time at AZ Alma. “Head nurses would indicate where it felt busiest, but we lacked objective data. Some units never asked for help even when we knew their workload was high.”
Through training sessions and exchanges with other hospitals, AZ Alma discovered Team n Time and quickly decided to adopt it. “The support from Team n Time has been a major advantage,” Jeffrey explains. “They listen carefully, act quickly, and take feedback seriously. That gave us confidence.”
After the initial implementation and valuable insights gained during the COVID-19 period, the hospital transitioned to Team n Time’s next-generation cloud platform. “The old version had its limits. Thanks to close collaboration with the Team n Time team and other hospitals, we were able to contribute to the development of this new platform.”
AZ Alma opted for a phased rollout, starting with four pilot units: one surgical unit, one rehabilitation unit, and two geriatric wards. “The head nurses of these units took the lead, which had a very positive impact on the rest of the rollout,” Jeffrey recalls.
“Even those with less digital experience could quickly get started thanks to the platform’s intuitive design. It turned out to be a success—by involving them as ambassadors, enthusiasm grew and broad support followed.”
The main challenge? Accurately defining care minutes. “Through close collaboration between our pilot units and Team n Time, we refined and ranked the care plans together,” Jeffrey explains. “It required focus and time but produced valuable insights and a much stronger foundation.”
The integration with the nexuzhealth EHR marks a key milestone for AZ Alma. Instead of relying on departmental averages, care intensity is now assessed based on each patient’s individual care plan.
“No two patients are the same,” Jeffrey emphasizes. “A geriatric patient with a stoma or complex wound care needs far more attention than average. Thanks to the nexuzhealth link, we finally have an accurate picture of that.”
This represents a major improvement compared to traditional methods based on generic indicators like nursing categories or ward types. “Previously, every geriatric patient was assigned the same workload—say, one hour and 32 minutes. But a patient needing glucose monitoring, wound care, or with wandering behavior naturally requires much more care time and follow-up. Now, that differentiation is visible,” Jeffrey explains.
The system even accounts for patients staying on a non-specialized ward, a common occurrence in hospitals. “An orthopedic patient temporarily placed on another unit still receives the correct workload classification, based on their personal care plan.”
This patient-level visibility has strengthened confidence in the data. “Our teams now see that staffing plans are based on actual patient needs, not gut feeling. It makes decisions about reallocating or deploying staff easier to explain and justify.”
Looking ahead, AZ Alma aims to further refine its care plans. “We’re exploring how to automatically include complex variables such as wound-care levels or behavioral patterns like wandering. Over time, we want to measure workload even more realistically at the individual level.”
The shift from averages to patient-level insight has generated enthusiasm across the wards. “Staff immediately recognized the added value. The estimations feel more realistic and support objective discussions about support requests and staffing.”
While formal measurements are still upcoming, COO Fritz Defloor notes that early results are already visible. “Team n Time now helps us distribute support more objectively and efficiently. Head nurses proactively exchange staff based on the data—rather than on who shouts the loudest. This aligns perfectly with our architectural vision of closer collaboration between units.”
The system also fosters transparent discussions about workload. “In the past, there were many more arguments. Now, you can literally show how busy a unit is.”
Because Team n Time integrates seamlessly with existing data sources, it adds no extra administrative burden. “On the contrary—it encourages accurate EHR documentation of care activities.”
At a strategic level, the hospital expects to soon gain additional insights from patterns in help requests and staff movements. “These data will soon allow us to improve our strategic workforce planning as well.”
What’s next for AZ Alma? “Capacity management is high on our agenda,” says Fritz. “Given the financial context, we need to manage bed occupancy and staffing more intelligently.”
The hospital also plans to use Team n Time for operational steering—for instance, optimizing patient transfers. “If you know when a unit has a lighter workload, you can plan transfers more efficiently. That saves valuable time.”
Further automation of workforce scheduling is also on the horizon. “It’s a big advantage that Team n Time is already heavily investing in this area,” Fritz concludes.
By linking Team n Time with the nexuzhealth EHR, AZ Alma has taken a decisive step toward smarter, data-driven nursing management. The hospital now moves from intuition and averages to real-time, patient-specific insight—strengthening trust, improving efficiency, and paving the way for a more objective approach to care delivery.