Round out clinician instinct, experience and education with analytics.
Dan Hogan, founder and CEO of Medalogix in Nashville, Tenn.: Just recently, Medicare announced its upcoming reimbursement for physicians and their end-of-life planning conversations. Predictive analytics can help ensure these conversations are happening with the right patients at the optimal time. This is just one example of how analytics can help assist in healthcare decisions. Analytics are invaluable because they add a fourth dimension of decision-making.
For example, a clinician, armed with his or her experience, instinct and education (three dimensions), can detect when a patient is nearing the final few days of his or her life. It's much more difficult for these three levels of decision making to help inform when a patient is going to pass away within 180 days — the full extent of the hospice benefit. Analytics adds a fourth dimension, which can predict an outcome 180 days away. This extra time to discuss all options makes all the difference — for the clinician, the patient and the patient's family.