News Feature | August 23, 2016

Predictive Analytics Can Help Coordinate Care

Christine Kern

By Christine Kerncontributing writer

Predictive Care Analytics

Medalogix founder Dan Hogan weighs in on the role of predictive analytics.

Care coordination, the intentional organization of patient care between two or more care providers, is linked to improved health outcomes which are especially important in today’s emerging value-based care system. Combined with predictive analytics, the process of making predictions based on current data, proper care coordination practices can greatly improve a patient’s overall experience, especially during end-of-life stages.

Unfortunately, according to a survey conducted by Nielsen Strategic Health Perspectives and the Council of Accountable Physician Practices (CAPP), just over half (51 percent) of the more than 30,000 respondents reported their doctors were not able to share information about their health or were aware of their medical history information prior to their appointments. Meanwhile, 37 percent of patients suffering from multiple chronic conditions said they had follow-ups or care management for their health, just slightly higher than the 36 percent for patients overall.

There is a real need for improved care coordination to boost health outcomes, according to Dan Hogan, founder of Nashville, TN-based Medalogix, predictive analytics can play an important role in doing just that. “Predictive analytics enables care providers to coordinate care proactively rather than reactively. Traditionally, care is coordinated from the top of the acuity ladder, the hospital or emergency room, down,” Hogan wrote in an email correspondence with Health IT Outcomes. “When we can predict 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.”

Care coordination is also shown to boost practice income through certain Medicare/Medicaid incentives, making it a win-win for patients and caregivers. Particularly when it comes to care for chronic conditions or end-of-life care, care coordination can help improve outcomes as well.

“One of the biggest misses in care coordination is in end-of-life care. Eighty percent of patients want to die at home and only 20 percent do,” explains Hogan. “Not only does this diminish care quality, it costs healthcare billions in avoidable hospital readmissions and prolonged intervention-based care. Medalogix Bridge is a predictive analytics technology that identifies which patients are likely to pass away within 180 days, or those who could benefit from hospice care. Equipped with this information, caregivers can ensure the right patients get access to the right care, in this case hospice care, at the right time — and that’s what care coordination is all about.”

Ultimately, Hogan says, “Predictive analytics can enhance care coordination because they allow for accurate prediction as to which patients could benefit from which type of care at what time. Without analytics clinicians use their experience, education and instinct to coordinate care and while this is a dynamic that has allowed us to build the best healthcare systems in the world, technology has evolved. 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.”