Healthcare Analytics, Population Health Management, Healthcare Big Data

Claims Big Data Analytics Flags Medication Non-Adherence Rates

Pharmacy claims data may help providers identify medication non-adherence among chronic disease patients, a new study suggests.

Claims data is often cited as a goldmine for emerging big data analytics strategies, due to their comprehensive and generally standardized nature.  Coupled with diagnostic information and clinical notes found in EHRs, researchers can fill in knowledge gaps and generate new actionable insights unavailable from narrower datasets. 

Medication non-adherence and big data analytics

Pharmacy claims data may be particularly helpful with the widespread problem of medication non-adherence, says a new study published in the American Journal of Managed Care

By pairing aggregated pharmacy records with EHR data on newly diagnosed hypertension patients, researchers were able to identify primary non-adherence rates, as well as flag those patients more likely to deviate from their treatment regimens.

Medication non-adherence is a significant financial and clinical burden on providers and patients alike.  With costs totaling nearly $337 billion in 2013, non-adherence can derail chronic disease management programs and produce suboptimal patient outcomes.  Identifying patients at higher risk of becoming non-adherent is an important first step towards reducing this critical population health management issue.

But previous research may not have truly addressed the root of the problem, says the study team from Thomas Jefferson University and Christiana Care.  “Traditionally, claims-based measures have focused on adherence after filling at least 1 prescription,” the study says, which is called “secondary adherence.” 

Filling a prescription without taking the pills is certainly problematic, but never making the trip to the pharmacy in the first place may be an even bigger concern.  These patients are “primary non-adherents,” and comprise up to 30 percent of those given an initial prescription for an antihypertensive medication.

“Primary nonadherence research has relied largely on pharmacy claims within integrated delivery systems or health plans,” the study explains.  “Historically, providers in most primary care practices, particularly those in multi-payer environments, do not have access to these data to identify or monitor for nonadherence.”

“The recent adoption of electronic-prescribing (e-prescribing) systems has made prescription fill information increasingly available to providers within their native electronic health record (EHR),” the team continues. “This access to aggregated, multi-payer pharmacy data creates an opportunity to identify and address primary nonadherence in clinical practice, possibly even in real time.”

The study examined EHR and claims data from more than 100,000 patients in fourteen northern Delaware primary care practices.  The practices shared the same EHR system, which includes complete problem lists, prescription information, allergy data, office notes, and diagnostic test results.  The providers had been using EHR-based e-prescribing technology for at least a year before the 2011 to 2012 study period.

The researchers defined “primary non-adherence” as failing to fill a new antihypertensive prescription within 30 days of receipt. 

Only 791 patients met the study criteria.  Two-thirds of those patients filled their prescription within the first thirty days – the majority of those patients visited the pharmacy on the same day that the medication was prescribed.

Patients with higher blood pressure were more likely to fill their prescriptions in a timely manner, while those with less alarming vitals were more likely to delay or fail to acquire their medications.  “The association may indicate a perceived lack of urgency, particularly given the asymptomatic nature of hypertension, although this is not clear from our data,” the team says. “Specific interventions for those with lower grades of hypertension may need to include education on the importance of adherence to prevent worsening hypertension.”

Patients who were older, on Medicare, or juggling a higher number of medications were also less likely to fill their prescriptions appropriately.  Patients whose EHR and claims data contained a higher number of medication discrepancies were more likely to be non-adherent, as well.

The results are “consistent with previous literature suggesting that medication nonadherence may increase as competing comorbidities, particularly with active symptoms, take precedence over asymptomatic conditions such as hypertension,” the study says. “Although the evidence for association of primary nonadherence with comorbidity is mixed, with some evidence suggesting increased primary nonadherence with a higher medication burden, our study and others suggest the opposite.”

While the study acknowledges that some of its findings will require further review and research, the team notes that “aggregated claims data within the native EHR could serve as the foundation to more appropriately identify patients demonstrating nonadherence in real time in clinical practice.”

“Our findings suggest that the increased availability of medication fill histories in clinical practice can provide objective insight into a patient’s medication adherence, and may provide a foundation for targeted interventions to improve primary non-adherence,” they concluded.
 

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