What if doctors could predict more accurately which of their patients were most likely to get sick? With the collection of digital data becoming mandatory and health care shifting from a volume-based to value-based delivery system, they potentially can — if they can access and interpret the information efficiently.
That’s where KenSci comes into play. The risk-prediction platform was collaboratively built by physicians, data scientists, software developers, and computing and biomedical researchers at the University of Washington. KenSci selects from more than 180 health care-specific models to identify statistically significant patterns and areas most susceptible to risk. It gathers data from existing data sources within health systems, such as electronic medical records, claims, sensors and wearables.
“We mine the data to find out not what has happened but what is most likely to happen,” says cofounder and CEO Samir Manjure. Since its launch in 2015, KenSci has positively affected more than 27 million lives and delivered return on investment across more than 15 of the largest health systems, including the National Health Service, Fullerton Health, the Centers for Disease Control, the U.S. Army Medical Corps, Kaiser Permanente, St. Luke’s Health Partners (Boise), Multicare Health System, Seattle Children’s and the UW.
The platform has also been used to tackle critical health care issues such as emergency department overloads, population cost prediction, readmissions for chronic diseases and fraudulent claims data.
Named by Inc. magazine one the nation’s fastest-growing companies, MedBridge is a leading online continuing education, patient engagement and reporting solution for health care professionals. The company helps some 85,000 clinicians and more than 1,000 organizations improve clinical, patient and financial outcomes through its platform. MedBridge’s products include certification preparation programs, patient education, patient satisfaction surveys, and outcome tracking and reporting. The return on investment has been profound: One 700-plus clinician private practice network saw more than $1.1 million in annual saving; another saw a 75 percent reduction in staff attrition.