WOONSOCKET, R.I. — Researchers at CVS Caremark and Brigham and Women’s Hospital have found that a new approach to classifying patients by their long-term medication adherence behavior may be more accurate than traditional approaches.
Using an approach called group-based trajectory modeling, the research team followed more than 264,000 statin users over a 15-month period and created measures to account for different adherence behaviors. The researchers identified key groups into which various patients would fall based on these measures in an effort to predict and compare their long-term adherence patterns.
The findings were published in the September 2013 issue of Medical Care.
This method, which is based upon observed patterns of medication filling over time, allows researchers to more accurately capture and describe adherence compared with techniques that simply classify patients as adherent or not, using average levels of adherence. In addition, the trajectory patterns that are created should allow for more targeted interventions to address nonadherence. In this study, use of trajectory modeling was especially useful for accounting for variable patterns of intermittent and long-term adherence behaviors.
“Our findings could help facilitate research on medication adherence and medication effectiveness in a variety of ways,” stated Niteesh Choudhry, associate physician of the Division of Pharmacoepidemiology and Pharmacoeconomics at Brigham and Women's Hospital and associate professor at Harvard Medical School. “For example, by using group-based trajectory modeling, we could help identify patients with distinct patterns of adherence so that healthcare professionals could appropriately target interventions. In addition, data related to the quantity and timing of medication availability could help improve our understanding of the effects of nonadherence on clinical outcomes.”
Based on the study group, researchers categorized patients in to six distinct groups according to characteristics:
Group trajectory modeling also identified certain characteristics that impact medication adherence. For example, among the study participants, those patients with the best adherence were on average older, more likely to have a higher income, more likely to be a high school graduate and less likely to be black. In addition, those with the best adherence were more likely to be a Medicare Part D beneficiary or live in New England. Those with the lowest adherence rates tended to be generally younger, male and less likely to have an initial prescription that provided them with more than a 30-day supply of medication.
“CVS Caremark continues to engage in cutting-edge research using novel approaches to analyze data so we can better understand the adherence behaviors and needs of the patients we support, “ stated Troy Brennan, EVP and chief medical officer of CVS Caremark. “The use of trajectory models could help us more accurately identify patients at risk for medication nonadherence so we can develop and implement targeted interventions to help them stay on their medications for chronic health conditions.”
CVS Caremark stated that it plans to use these research results along with other key learnings to identify, develop and pilot interventions that will help improve medication adherence for the patients it supports. The company is currently evaluating and piloting a number of interventions that range from the development of models to predict a patients’ adherence behaviors in order to better target interventions; to the use of medication reminder devices to help combat forgetfulness; to digital interventions that engage patients to encourage adherence.
CVS Caremark has been working in a multi-year collaboration with Brigham and Women's Hospital to research pharmacy claims data in order to better understand patient behavior, particularly around medication adherence. Annual excess healthcare costs because of medication nonadherence in the United States have been estimated to be as much as $290 billion annually.
Get connected and follow us on LinkedIn for the most in-depth coverage of drug store news. Join the conversation.