CVS study: Early medication-fill patterns can predict future adherence

Results released this week from a study conducted by CVS Health Research Institute and Brigham and Women's Hospital researchers indicated that a patient's future medication-adherence behavior can be predicted by examining the patient's patterns of medication fills in the first few months after beginning chronic therapy.

"With the increasing availability of rich patient data, we can better anticipate how the patients we manage will take their medications," Dr. Niteesh Choudhry, associate physician at the Division of Pharmacoepidemiology and Pharmacoeconomics, a Brigham and Women's Hospital associate professor at Harvard Medical School and the study's senior author said. "This research shows that by focusing on a patient's initial, short-term medication filling behavior -- are they or are they not refilling their prescription on time during the first few months of therapy -- we can predict with great precision whether a patient will continue to take the medication as prescribed over the long term."

The study was based on data culled from more than 77,000 Medicare patients whose pharmacy benefits were administered by CVS/caremark. The study was conducted over a three-year period.

Patients were separated into six adherence classifications ranging from non-adherent to near-perfect adherence. The results indicated that patient patterns of initial medication filling in the first two to four months following initiation of a prescription accurately predicted future adherence behavior.

"This approach is helping us better target interventions to those patients who are most likely to benefit because trajectory modeling differentiates between patients who struggle with adherence at different times during their treatment," Dr. William Shrank, senior vice president and chief scientific officer for CVS Health and the study's co-author, said. "It can also be easily replicated and available to support a wide spectrum of payers and providers who are attempting to improve the quality and reduce the costs of health care. Increasingly, we are finding that, through better analytics, we can deliver the right intervention to the right patient at the right time."

Prior research showed that half of those who have long-term prescriptions for chronic conditions do not take their medicines as prescribed -- costing the U.S. nearly $300 billion and tens of thousands of lives each year.

To read the study in its entirety, visit http://www.ajmc.com/journals/issue/2015/2015-vol21-n9/Predicting-Adherence-Trajectory-Using-Initial-....