Merck adherence tool measures risk

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Asking consumers to gauge their non-adherence risk, Merck has added a one-minute survey dubbed the Adherence Estimator to its education and awareness site,

The three-question survey groups patients into low, medium and high risk for non-adherence to a newly prescribed medicine. It aims to keep patients on treatment by providing information specific to their concerns.

“Our studies point specifically to three health beliefs that are the best predictors” of who may or may not take their prescribed medical treatment, said Merck VP, US medical affairs Sethu Reddy, MD. The Adherence Estimator sums up those three beliefs by asking patients to give yes or no responses to the following assertions: “I worry that my prescription medication will do more harm than good to me;” “I am convinced of the importance of my prescription medication;” “I feel financially burdened by my out-of-pocket expenses for my prescription medication.”

It's an early effort to build an algorithm for predicting non-adherence, opening the door to  preemptive intervention by drug companies, healthcare professionals and health insurers.

“It's the best practical tool we've seen because it's so simple,” said Jay Bolling, president and CEO of Roska Healthcare Advertising. “If you ask people to fill out a 30-question survey, forget it.”

A study of the survey, designed by Merck's Colleen McHorny and Abhijit Gadkari, found it a better predictor of non-adherence than of adherence. It pegged non-adherers 88% of the time, but was right only 59% of the time in picking adherers from a group of 100 patients.

Another snag in this approach is that the EMR infrastructure isn't there to support automated reporting, but it suggests that the system could keep patients on treatment and out of the ER once it is. “If it's not almost automatic it can be hard for the office to act on it,” says Bolling. “But if I'm a nurse looking at a patient's EMR and it shows that patient is likely to be non-adherent, I can spend extra time on that patient.”
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