Today, there is a mountain of data on population health. As the Senior data scientist in the Care Management Solutions department of Philips Research Europe it’s my job to make this data useful.
I recently worked on CareSage, the cloud-based, predictive analytics engine that helps health organizations reduce avoidable admissions and ER visits for its frail and elderly population. CareSage is the predictive power behind the Philips Lifeline Frail and Elderly Program (FEP). My work in this area of predictive data has enabled health systems to better monitor and care for elderly patients by combining actionable insights with the wearable Philips Lifeline healthcare alert device.
A good example of Lifeline and CareSage in action is a story I heard about an elderly lady in Yorkshire, England, who accidentally set her chip pan on fire. She pressed her lifeline button, and within a minute the lifeline support team was able to send the appropriate response based on her health records. Luckily she wasn’t injured and soon recovered from the ordeal. She has had a number of falls since this incident, but the response has been immediate and appropriate thanks to the predictive data collected by CareSage.
It’s because of stories like this that I realize that by working for Philips you really can make a difference to people’s lives. Even saving them on occasion.
More recently, I’ve been involved as the project leader on the ACT Program (Advancing Care Coordination & Telehealth Deployment), which is the first program to explore the processes for bringing personalized care into the home of the elderly and chronically ill. I’m currently analyzing this data to see how we can bring the hospital to the home, and improve the quality of life for elderly patients across Europe. Which is a widespread desire, given the rapidly ageing baby boomer generation.