In addition to driving COVID-19 understanding within the United States, a national disease registry is informing research beyond U.S. borders. Clinicians with the Singapore Ministry of Healthcare Office for Healthcare Transformation (MOHT) have used Health Catalyst Touchstone® COVID-19 data to develop a machine learning tool that helps predict the likelihood of COVID-19 mortality. With this national data set that leverages deep aggregated EHR data, the MOHT accessed the research-grade data it needed to build a machine-learning algorithm that predicts risk of death from COVID-19. The registry-informed prediction model was accurate enough to stand up to comparisons in the published literature and promises to help inform vaccine research and, ultimately, allocation of vaccines within populations.
Learn more about Pol Margalef, PhD
Pol Margalef, PhD, Strategy and Business Development Consultant, is part of the team at the Life Sciences Business Unit at Health Catalyst. He brings broad experience in analyzing data and solving complex problems to help in strategic decision making with the desire to help the healthcare industry to improve patient's quality of life. Prior to joining Health Catalyst, he conducted research in Hospital del Mar (Barcelona) and at The Francis Crick Institute (London), work from which he received different grants. He holds a bachelor's degree in human biology, an MSc in Biomedical Research, a PhD in Biomedicine, and a postgraduate in Pharmacoeconomics.