Roger Eurelings and Math Hundscheid, HuisartsenOZL, share their experiences
In eastern South Limburg, more than 265,000 people rely on the family doctor on-call service in Heerlen for 24-hour care. That clinic is part of the HuisartsenOZL healthcare group, which includes more than 130 general practitioners. They run their own practices and take turns being scheduled at the HAP. HAP manager Roger Eurelings and general practitioner Math Hundscheid, who also serves as the application administrator, discuss the transition to data-driven management.
“If I hear on Monday that the HAP has been busy, I can see in the dashboard what caused that rush.”
Many activities at the HAP are recorded in the registration system. But for a long time, that data wasn’t used effectively. During the search for a BI system, Power BI and Qlik were compared. Qlik won out because of its user-friendliness for the end user. Through a general practice organization in North Limburg, HuisartsenOZL came to EscuLine (part of SureSync).
The HAP Basic Dashboard developed by EscuLine provides a comprehensive overview of interrelated themes and KPIs. Selecting by ICPC code immediately updates other sections of the dashboard, allowing you to see at a glance how much time was spent on certain diagnoses or how many consultations took place on specific days.
Roger Eurelings uses the dashboard not only to see where the standard is being met, but also—and more importantly—where it isn’t. The standard for emergency calls is to arrive on-site within 20 minutes. These are precisely the cases where there is still room for improvement, and he wants to understand them, not just identify them.
A key factor at HuisartsenOZL is the presence of Math Hundscheid: a family physician who approaches BI from various angles and understands the processes behind the data. This makes it possible to draw meaningful conclusions and interpret the dashboard correctly.
A concrete finding from the dashboard analysis: a small group of patients accounts for a large number of contact moments at the out-of-hours practice (HAP). By identifying this group, analyzing the nature of their complaints, and looking for patterns, new opportunities for targeted care emerge.
The next step is predictive analytics: using historical data to forecast future demand, so that supply and demand at the HAP can be better aligned. EscuLine has the statistical expertise to do this, and HuisartsenOZL has the ambition to take that step.