Data as an effective tool to boost medication adherence

Medication adherence remains a major obstacle to saving lives, controlling costs and improving the quality of healthcare.

Statistics show that nearly three of five American adults take at least one daily medication and separate data tell us that from 2000 to 2012, the proportion of people taking five or more prescription medications had doubled.

A recent report, “Adherence and Health Care Cost,” estimated between 20% and 50% of patients are noncompliant with drug therapy. Additionally, poor medication adherence following hospitalization costs the U.S. healthcare system roughly $100 billion annually, according to a New England Journal of Medicine study.

Through their accessibility and relationships with their patients, pharmacists already play a vital role in achieving positive health outcomes such as fewer hospitalizations, less disease progression, and fewer co-morbidities. How could pharmacists use data to improve medication adherence without disrupting their workflow and unnecessarily expending time and resources?

A study showed that while 20% of healthcare outcomes are determined by medical treatment, 50% rely on social determinants. To be more effective, we need to understand all factors involved in medication adherence to help pharmacists gain more insight about the patients they serve.

Part of the solution lies in public records data on patients that focus on social determinants of health categories identified by the Centers for Disease Control and Prevention: social and community context, neighborhood and built environment, economic stability and education.

Among these categories alone, there are hundreds of clinically validated attributes that correlate with health outcomes, including medication adherence, prescription costs, hospitalizations, stress and motivation to care for one’s own health. For example, increased community involvement is correlated to more spending on prescriptions — more active in community, more active in one’s own care. Meanwhile, patients living in higher crime areas tend to have lower medication adherence — these patients may avoid leaving home for fear of one’s safety.

These data points — which can be combined into predictive health scores — can help pharmacists prioritize time and resources more efficiently and improve health outcomes for patients.

The socioeconomic information helps fill in the missing pieces in solving the puzzle of medication adherence. It can alert pharmacists to higher-risk patients who may require a more in-depth consultation. Pharmacy chains can use the same data to identify and analyze the level of engagement and resources most appropriate for a particular neighborhood, city, state or region. Access within the workflow to this level of socioeconomic data could help a pharmacist drill down to the individual patient level to determine the likelihood of adherence and can be used to flag specific, more at-risk patients to help better achieve the proper level of care.

Current data being collected for other uses, such as on unfilled prescriptions, could be applied to achieving better medication adherence by cross-checking unclaimed prescriptions with a patient’s socioeconomic information allowing the pharmacist to tailor outreach.

According to the Department of Health and Human Services’ Agency for Healthcare Research and Quality, “Tracking medication adherence through health IT will be a critical advance in giving physicians and other healthcare providers the tools they need to provide better care for their patients.”

Additionally, with the evolution of value-based care initiatives, increasing medication adherence through the analysis of the data at our fingertips is a way to prevent readmissions. This makes it even more important for pharmacies to understand the patient in a holistic way.

Bobbie Riley is the vertical market lead, pharmacy, at LexisNexis Risk Solutions - Health Care; Erin Benson is director of market planning and engagement at LexisNexis Risk Solutions – Health Care; and Bill Frank is senior solutions consultant, LexisNexis Risk Solutions – Health Care.