Pacmed Critical, in partnership with ELI5, leverages AI and data visualization to empower ICU doctors with actionable insights, reducing unnecessary readmissions and optimizing patient flow. Discover how this award-winning solution is transforming critical care.
Challenge
Determining the optimal moment to discharge a patient from the ICU is a high-stakes, data-driven decision. Each patient generates around 30,000 data points per day, from vital signs to lab results. Discharging too early risks readmission and increased mortality; too late, and patients may suffer unnecessary consequences while blocking critical ICU beds for others in need.
When Pacmed approached us, they had a powerful algorithm capable of analyzing tens of thousands of data points per patient, but they needed a way to make this intelligence accessible and actionable for ICU doctors. That’s where we came in.
We worked closely with Pacmed’s data science and clinical teams to deeply understand the workflow and pain points of ICU physicians. Our team designed and built a custom dashboard that translates complex machine learning outputs into clear, intuitive visualizations. This dashboard doesn’t just display data—it tells a story, highlighting trends, surfacing risks, and providing real-time recommendations that support, but never replace, clinical judgment.
- User-centered design, ensuring the interface was intuitive for busy clinicians
- Real-time data processing, so doctors always have the latest insights
- Visual storytelling, making it easy to spot patient deterioration or readiness for discharge at a glance
- Seamless integration, so the tool fits naturally into existing hospital systems and workflows
What we built
Pacmed developed a sophisticated algorithm to predict the necessity of continued ICU care, analyzing vast amounts of patient data with advanced statistical techniques. We build a user-friendly dashboard for Pacmed Critical that would translate this complex analysis into clear, actionable information for ICU doctors.
The dashboard visualizes key patient data, length of stay, current status, trends over time, and readiness for discharge, helping doctors make informed decisions. Importantly, the algorithm supports, but never replaces, clinical judgment, offering transparency into the factors influencing each prediction.
Insight
Pacmed Critical draws on 14 years of data from 16,000 ICU admissions in Amsterdam, using machine learning to identify patterns and predict outcomes. The tool enables doctors to quickly answer critical questions, such as: “What is the chance of re-admission or premature death within seven days if the patient leaves now?” By surfacing insights from similar cases, the software accelerates and improves decision-making.
Impact
Our collaboration with Pacmed changed the way ICU teams make decisions. By making complex AI insights accessible and actionable. Doctors now have the confidence to make faster, safer discharge decisions, freeing up ICU beds for those who need them most and improving outcomes for patients and hospitals alike.
10–15% reduction in ICU readmissions
1–5% reduction in average length of stay
Winner: Computable Award 2019 (Best Healthcare Project)
"Eli5’s rapid prototyping and user validation approach allowed us to bring our innovative healthcare solution, Pacmed, to life in record time. Their ability to turn our vision into a fully functional product in just a matter of weeks was nothing short of impressive."
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