Long-Term Living: Data-Driven Decisions

February 10, 2016

Long-term care providers are using analytics tools to drive care quality, and Dan chatted with Long-Term Living’s David Raths on just how Medalogix can improve end-of-life care. Hereis the snippet featuringquotes from Dan inLong-Term Living‘s January/February 2016 cover story.

Data-Driven Decisions: LTC providers use analytics tools to drive care quality

by David Raths,Senior Contributing Editor to sister-brandHealthcare Informatics

One bright spot is the use of predictive analytics to identity areas that require more resources, such as identifying patients that may need additional care. Dan Hogan built his company, Nashville, Tenn.-based Medalogix LLC, based on the capability to use data and algorithms to identify residents more likely to be readmitted to the hospital. Then customers requested a tool to predict which residents are nearing the end of life and might benefit from a transfer to hospice or home health services.

Hogan’s team went back to the drawing board, taking the same data set it had been working with for readmissions, and analyzing it for patient mortality. “Right out of the gate the model was as if not more predictive than the readmission tool we had built,” he says. Hogan stresses that the tool is about identifying an elevated probability within a 180-day window, and focusing the attention of clinical resources so they can have that conversation early. “It is a clinical decision support aide,” he adds. “There is nothing black and white about it. It is all about elevated probabilities.”

Rolled out in 2013, the tool is used by 21 of the 50 largest home healthcare companies in the country, he says. “What we have seen on average is a 30 to 35 percent lift in hospice days. We are identifying more patients that are hospice-appropriate and we are identifying them earlier.”

*Originally published inLong-Term Living.

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