An AI-powered dashboard for intensive care

Connecting data from complex diagnostic machinery to predict the chance of readmissions for patients


Design, Engineering, Product Strategy




Prototype, MVP, V1.0, Post-launch dev

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For a healthcare system where all patients receive care adjusted to their personal needs.

Pacmed helps healthcare providers by providing them with tools to make data driven decisions. It combines medical expertise with machine learning and learns from large volumes of data.


Determining the optimal moment of discharge for a patient from an Intensive Care Unit (ICU) is a complex decision. A patient in the ICU generates about 30,000 data points per day. This concerns values of vital functions, but also lab tests and results. Together they indicate the chance that a patient would be readmitted if they were discharged - and both early and late discharge have negative consequences.


Pacmed had built an algorithm to predict how necessary it is for people to stay in the ICU. Eli5 built a dashboard that would process this analysis to provide ICU doctors with a clear overview of all required information to prevent unnecessary readmissions and long stays in the ICU. The dashboard needed to make the data visual, so doctors could use it on their screen.


Pacmed Critical is a discharge software that uses 14 years of data from 16,000 IC admissions in Amsterdam. The machine learning algorithm make predictions based on self-found patterns and connections. This supports physicians in making important decisions by sharing information about what has worked with similar patients.


Pacmed predicts the probability of a patient being re-admitted or dying within 7 days if they are discharged and predicts recordings with an accuracy in line with scientific research. Based on retrospective scenario analyses, the software can reduce the number of readmissions by 10-15%. The average length of stay may be reduced by 1-5%. In 2019 Pacmed Critical won the Computable Award for best healthcare project.

Pacmed's technology specifications

We’ve designed and developed the Pacmed user interface entirely from scratch, using Vue.js, Python, Kubernetes, and Ansible.

Jelle Bot

Head of Design

Design Commentary

In a matter of weeks we realised a complete prototype to monitor clients, tested it with real users and completed the final design within a month.

Kishan Chamman

CTO at Eli5

Engineering commentary

Building Pacmed Critical required us to rework the notion of safe development, since this is a medical application used by medical professionals on the Intensive Care unit. This requires us to comply with strict rules and requlations, while rapid feature development also being a necessity. We've achieved this by fully automating the test suites and integrations, that allow us to deploy with complete confidence.

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