Risk Adjustment: Making the Most of Payment Opportunities

August 24 2016 | by SCIO Health Analytics in Risk Adjustment

H. Jackson Browne, Jr., author of the inspirational bestseller, Life’s Little Instruction Book, which contained 511 reminders about how to live a happy and rewarding life, once said: "Nothing is more expensive than a missed opportunity."

Healthcare organizations can relate to this truism, as many are missing the opportunity to collect additional reimbursement through risk adjusted payments, which offer increased payments for treating patients with one or more chronic conditions. For example, if Medicare Advantage normally pays $800 per member per month (pmpm) to the health plan, risk adjustment for a member who has diabetes with complications might be three times that amount.


Health Reform: Will it Really Affect Whether or Not Patients Undergo Surgery?

August 17 2016 | by Dr. Kevin Keck in Health Analytics

Under fee-for-service payment models, making the decision to move forward with many surgeries – such as total knee replacements – was not a difficult one to make.

Here’s an example of how it would commonly unfold: A patient experiences knee pain. The patient receives a prescription for painkillers. The condition deteriorates, and MRI is obtained and eventually the patient undergoes the total knee replacement as a matter of course. Because such surgeries were profitable for hospitals and orthopedists under the long-held fee-for-service model, no one bats an eye.


Payers and Providers: 3 reasons to get together

July 11 2016 | by Rose Higgins in Health Analytics

"Two heads are better than one." It's a common axiom that is widely accepted.

Healthcare payers and providers, however, have traditionally been a bit reluctant to embrace the concept in the past, as they preferred to tread their own paths while working to improve care, enhance patient experiences and reduce costs.


Intuition vs. Analytics: Polar opposites or one and the same?

July 04 2016 | by David Hom in Health Analytics

Intuition is often thought of as a somewhat magical, innate personal quality that some people are born with – and others lack. When people make decisions based on intuition, we assume that they are moving forward based on some type of “gut feeling.” Analytics, on the other hand, is often thought of as hard science. When people make decisions based on analytics, they are moving forward based on data that has been scrutinized and studied, explored and examined – again and again.


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