Pacmed

Pacmed, an Amsterdam-based healthcare technology firm founded in 2015, develops clinical decision support systems for hospitals. The company's genesis traces back to the 2014 Dutch National ThinkTank, where founders Wouter Kroese (a medical student), Willem Herter (a physicist), and Hidde Hovenkamp (an econometrician) were tasked with exploring how big data could improve society's health. This experience prompted them to dedicate their careers to applying AI to extensive clinical data to provide healthcare professionals with personalized patient insights. Their goal is to empower medical experts, not replace them, by creating a synergy between physicians and AI.

Pacmed's business model centers on providing hospitals with end-to-end AI solutions that integrate into their existing workflows. Serving as a partner, the company assists with implementation, offers continuous support, and helps tailor the technology to the specific needs of the medical institution. This collaborative approach aims to enhance clinical reasoning, automate administrative tasks, and optimize resource management, thereby reducing costs and easing the workload on healthcare professionals. The firm ensures its AI solutions are secure, compliant, reliable, and interpretable, working with medical experts to validate them for safe and effective clinical impact.

The company's flagship product is Pacmed Critical, an AI platform designed for Intensive Care Units (ICUs). This platform analyzes vast amounts of real-time and historical patient data—with one early algorithm drawing on 14 years of data from 16,000 ICU admissions—to predict patient outcomes. Specifically, it helps clinicians determine the optimal time for a patient's discharge by calculating the probability of readmission or death within seven days. The system presents this complex analysis through a user-friendly dashboard that visualizes key patient data, trends, and discharge readiness, translating machine learning outputs into clear, actionable information to support high-stakes decision-making. The technology initially saw use in primary care, assisting general practitioners with treatment decisions for urinary tract infections, before the company shifted its focus to the ICU, where it identified the most significant potential for impact.

Keywords: clinical decision support, healthcare AI, medical machine learning, ICU optimization, patient data analytics, predictive healthcare, clinical intelligence, hospital workflow integration, responsible AI, data-driven medicine, Amsterdam, Wouter Kroese, Willem Herter, Hidde Hovenkamp, Pacmed Critical, ICU discharge, physician support tools, health-tech, medical software, clinical outcomes