In an interview with Health IT Outcomes, Dan Hogan, founder of Medalogix, detailed a few areas where predictive analytics can improve patient outcomes through better care coordination:
Traditionally, care is coordinated from the top of the acuity ladder, the hospital or emergency room, down … predict[ing] patient risk with advanced statistical modeling, we can proactively coordinate care at a lower, less restrictive and more cost effective acuity level, like home health, before a high acuity care stay is necessary.
End-of-life care, Hogan says, is another area in which predictive analytics could play a vital role for care coordination:
Eighty percent of patients want to die at home and only 20 percent do. Not only does this diminish care quality, it costs healthcare billions in avoidable hospital readmissions and prolonged intervention-based care … [by using] predictive analytics technology that identifies which patients are likely to pass away within 180 days, or those who could benefit from hospice care … caregivers can ensure the right patients get access to the right care, at the right time.
The bottom line, according to Hogan, is that analytics can be an invaluable tool for health care providers:
Analytics can add an invaluable dimension to a caregiver’s decision-making process that accounts for millions of patient experiences, understanding their outcomes and steering the right care to the patients that the evidence supports are likely to improve with any specific intervention.