Health orgs tap analytics to hone population health management
With ever-increasing amounts of health data available, healthcare organizations are using predictive analytics to study patient trends in their facilities. The hard part, however, is figuring out what to do about the trends that need fixing.
According to a recent article at Hospitals & Health Networks, a recent survey by Health Catalyst found that thirty-one percent of hospitals have used some form of predictive analytics technology for more than one year, and nearly 80 percent of hospital executives said they believe that with the use of predictive analytics healthcare could be improved significantly.
But while the potential of predictive analytics “to solve some of the most entrenched quality-, cost- and resource-intensive problems is driving adoption,” experts caution that predictions are only as good as the underlying data and that hospitals need the resources to respond to predicted outcomes.
“It’s very seductive,” says Michael Kanter, M.D., executive vice president of quality and chief quality officer of the Oakland, Calif.-based Permanente Federation, whose parent Kaiser Permanente has implemented predictive analytics in a number of areas. “It holds huge promise. But it’s one thing to predict the future and a whole other thing to change it.”
So how can healthcare organizations implement and make good use of predictive analytics technology? According to the article, all areas of leadership, from the board to the C-suite to the clinical experts.
For trustees, “governance support is needed to implement robust data analytics and allocate the required resources to change predicted patient outcomes.”
For hospital executives, the challenge is to support data validation efforts and allocate resources appropriately. “This might mean adding more staff initially, including care coordinators, nurses and home health workers, to respond to predictions in patient health.”
And providers should conduct small tests of change to see what works best in terms of implementation. This could require extra training and changes to daily practices, such as rounding. “If providers don't act on the prediction,” the article notes, “patient outcomes won't change.”