CVS Health Research Institute Study Finds that Initial Prescription Fills Can Accurately Predict Long-term Medication Adherence

Approach can help quickly identify patients most likely to benefit from interventions to improve medication adherence

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Sep 21, 2015, 08:30 ET

WOONSOCKET, R.I., Sept. 21, 2015 /PRNewswire/ -- A new study by researchers at the CVS Health (NYSE:CVS) Research Institute and Brigham and Women's Hospital provides evidence that patients' patterns of medication fills in the first few months after starting on a chronic therapy accurately predict future medication adherence behavior. The study, published in The American Journal of Managed Care, suggests that this approach may help quickly identify those patients most likely to benefit from medication adherence interventions.

"With the increasing availability of rich patient data, we can better anticipate how the patients we manage will take their medications," said Niteesh Choudhry, MD, PhD, associate physician, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and associate professor, Harvard Medical School and the study's senior author. "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 included claims data from more than 77,000 Medicare beneficiaries that began taking a statin or statin combination drug over a three year period and whose pharmacy benefits are administered by CVS/caremark, the pharmacy benefit management company of CVS Health. Based on patterns of prescription filling over the year following therapy initiation, the researchers used group-based trajectory models to classify patients into six adherence trajectories–ranging from non-adherent to near-perfect adherence–to help capture both duration and intensity of medication taking. The results showed that patient patterns of initial medication filling in the first two to four months following initiation of a prescription accurately predicted future adherence behavior, allowing precise prediction of the patterns of medication taking over the subsequent year.

This research helps to further validate group-based trajectory modeling as an accurate approach to classify patient medication adherence behaviors. This study builds on a growing body of peer-reviewed literature developed through the research partnership between Brigham and Women's Hospital and the CVS Health Research Institute. Previous studies by these research partners have demonstrated that the group-based trajectory model offers greater precision than other sophisticated computational approaches to predict adherence after initially describing this methodology in a publication in the journal Medical Care in 2013.

"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," said William Shrank, MD, MSHS, senior vice president and Chief Scientific Officer, CVS Health and study co-author. "It can also be easily replicated and available to support a wide spectrum of payors 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."

Research shows that half of people 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. As a pharmacy innovation company, CVS Health is using advanced analytics to more effectively target medication adherence interventions, improve health outcomes and reduce health care costs. In fact, CVS Health recently launched the Vulnerable Patient Index (VPI), a tool that uses pharmacy claims data to risk-stratify patients and identify CVS/caremark members most likely to generate high total health care costs resulting from poor medication adherence or unsafe use of complex regimens. By leveraging rich claims databases to better understand risk and to anticipate patient behaviors, CVS Health is better positioned to manage the health of populations by delivering tailored interventions that address individual patient medication use challenges.

The CVS Health Research Institute is focused on contributing to the body of scientific knowledge related to pharmacy and health care through research collaborations with external academic institutions, participation in federally-funded research, analysis and sharing of CVS Health data sources and coordination of pilot programs and initiatives. This analysis is part of a multi-year research collaboration with Brigham and Women's Hospital to better understand patient behavior, particularly around medication adherence. CVS Health Research Institute findings support a continuous quality improvement environment, which encourages product innovation and development to benefit CVS Health patients, clients and their members.

To read the study, click the following link: http://www.ajmc.com/journals/issue/2015/2015-vol21-n9/Predicting-Adherence-Trajectory-Using-Initial-Patterns-of-Medication-Filling

About CVS Health
CVS Health (NYSE: CVS) is a pharmacy innovation company helping people on their path to better health. Through its 7,800 retail drugstores, nearly 1,000 walk-in medical clinics, a leading pharmacy benefits manager with more than 70 million plan members, and expanding specialty pharmacy services, the Company enables people, businesses and communities to manage health in more affordable, effective ways. This unique integrated model increases access to quality care, delivers better health outcomes and lowers overall health care costs. Find more information about how CVS Health is shaping the future of health at www.cvshealth.com.