University Medical Center Utrecht improves quality of care with applied data analytics
University Medical Center Utrecht (UMC Utrecht) strives for the highest levels in patient care, scientific research and education. To achieve their ambition the academic hospital invests in advanced data analytics. Harry Pijl, Program Manager Board of Directors at UMC Utrecht, explains how, among others, SAS software enables UMC Utrecht to develop a data strategy and help them to generate insights to further improve care.
With applied data analytics we can pioneer cutting-edge treatments, foster ground-breaking findings, and deliver a standard of care that meets the healthcare needs for today, and the future. Harry Pijl Program Manager Board of Directors, University Medical Center Utrecht
UMC Utrecht always has had a unique position in the digital world of healthcare in the Netherlands. They developed solutions like the patient portal, which give patients real-time access to their patient information. Another great solution SAS helped developing is the Research Data Platform to collect, manage and unlock anonymized and depersonalized data for research purposes. To maintain their leading position the board of UMC Utrecht asked to develop a data strategy, to set up an experimental environment for data analytics in collaboration with external partners, and to realize several concrete projects as a benchmark for the future.
Infrastructure for advanced analytics
To structure and support all the existing data analytics initiatives within the organization, UMC Utrecht first priority was to implement an overarching and integrated infrastructure or data lake and centralized coordination. The hospital developed partnerships with the leading organizations like Philips, Siemens and SAS.
UMC Utrecht uses the following SAS products:
- SAS Studio
A web browser-based programming environment to easily write and interact with SAS code wherever and whenever needed.
- SAS Enterprise Guide
A point-and-click, menu- and wizard-driven tool that empowers users to analyze data and publish results. It provides fast-track learning for quick data analysis, generates code for productivity and speeds the ability to deploy analyses and forecasts in real time.
- SAS Visual Analytics
A powerful in-memory environment, scalable and compliant, for visual data discovery interactive reporting and self-service analytics.
- Text Miner
Text miner software for faster, deeper insight from unstructured data.
So far UMC Utrecht has done 4 pilots projects in the field of diagnosis and treatment: Neonatal Intensive Care Unit, Psychosis, Cardiovascular Risk Management and Rheumatoid arthritis. For these project the data was mostly collected from owned data sources. With data analytics the first insights are generated and the first algorithms are available for clinical decision support.
“We are in the experimental phase of data-driven care, based on the huge amounts of data already available. We are exploring data analytics with the help of external collaborations including SAS”, says Pijl. “That helps us to generate meaningful insights from the data.”
Pijl is very positive about the near future: “With the buy-in of the management, the data roadmap embedded in the strategy of the organization, the infrastructure set and the first results that prove the added value, all ingredients are there to scale up to the next phase in advanced data analytics.”
Develop a data strategy and implement an overarching infrastructure with applied data analytics to improve quality of care.
- Optimized insights through collecting data from multiple resources.
- Algorithms and models to further improve clinical care.
- New ways of working; clinical decision support, shared decision making towards personalized care.