Creating a “patient flight path” helps patients clearly see what their health future could be, and that’s supported by improving the use of predictive data analytics at a large multi-specialty group practice in New York State.
Crystal Run Healthcare in Middletown runs analyses to support patient interventions and has been using predictive data analytics from Health Catalyst for a few years now, said Gregory Spencer, M.D., chief medical officer, during an interview at HIMSS16.
The flight path identifies patients likely to be hospitalized using the patients’ own data, and possible health outcomes if patients’ health status continues to move in the current direction—including predicted out-of-pocket expenses for the patients.
In a snowy region, the practice also conducted analyses to inform development of a “snow plan” to predict the ability to have access to patients, expected attendance of patients coming in for care, as well as the number of providers and staff that could make it to work.
While Crystal Run Healthcare has been preparing for accountable care and value-based payments, other providers behind the curve soon will find out that these changes are becoming very real as health insurers get ready for risk-based arrangement with providers, Spencer said. And the analytics tools needed today “are really different from doing fee-for-service,” he added.
That’s because claims data no longer is the gold standard for analyzing, as patient populations must be risk-stratified and prioritized, and an organization can wait up to four months to get actionable claims data.
Risk stratifying can identify high-risk patients needing care management that can keep them at home rather than in the hospital, and can identify care gaps to get ahead of possible problems looming, according to Spencer.
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