Pharmacy-based Interventions to Reduce Primary Medication Nonadherence to Cardiovascular Medications

Abstract

BACKGROUND: Primary medication nonadherence (PMN) occurs when patients do not fill new prescriptions. Interventions to reduce PMN have not been well described. OBJECTIVES: To determine whether 2 pharmacy-based interventions could decrease PMN. DESIGN: Two sequential interventions with a control group were evaluated after completion. The automated intervention began in 2007 and consisted of phone calls to patients on the third and seventh days after a prescription was processed but remained unpurchased. The live intervention began in 2009 and used calls from a pharmacist or technician to patients who still had not picked up their prescriptions after 8 days. SUBJECTS: Patients with newly prescribed cardiovascular medications received at CVS community pharmacies. Patients with randomly selected birthdays served as the control population. MEASURES: Patient abandonment of new prescription, defined as not picking up medications within 30 days of initial processing at the pharmacy. RESULTS: The automated intervention included 852,612 patients and 1.2 million prescriptions, with a control group of 9282 patients and 13,178 prescriptions. The live intervention included 121,155 patients and 139,502 prescriptions with a control group of 2976 patients and 3407 prescriptions. The groups were balanced by age, sex, and patterns of prior prescription use. For the automated intervention, 4.2% of prescriptions were abandoned in the intervention group and 4.5% in the control group (P>0.1), with no significant differences for any individual classes of medications. The live intervention was used in a group that had not purchased prescriptions after 8 days and thus had much higher PMN. In this setting 36.9% of prescriptions were abandoned in the intervention group and 41.7% in the control group, a difference of 4.8% (P<0.0001). The difference in abandoned prescriptions for antihypertensives was 6.9% (P<0.0001) but for antihyperlipidemics was only 1.4% (P>0.1). CONCLUSIONS: Automated reminder calls had no effect on PMN. Live calls from pharmacists decreased antihypertensive PMN significantly, although many patients still abandoned their prescriptions.

Evaluation of pharmacy-based telephone interventions on medication pick-up rates: a retrospective, quality improvement study at charity outpatient clinics

“…Telephonic calls can be considered a cost‐effective and sustainable intervention to improve adherence . Live telephonic calls by a pharmacist or pharmacy technician reduced prescription abandonment (failure to pick‐up a prescription within 30 days of initial processing) by almost 5% while there was no improvement in abandonment in patients who received an automated call alone . Another study in patients with hypertension and diabetes found that a brief pharmacist telephone intervention identified barriers and improved adherence to medications among non‐adherent patients .…”

Assessing the relationship between pharmacy quality and healthcare cost for a commercially insured population

“…Therefore, as with healthcare quality more generally, quality measurement for pharmacies should encompass broad elements of quality. Despite this, studies on pharmacy quality estimate pharmacies' impact on process measures of care (Brennan et al, 2012;Fischer et al, 2014;Pringle et al, 2014) but ignore impact items like responsiveness, patient-centeredness, timeliness and efficiency. These concepts are important for a deeper understanding of the impact of pharmacies on healthcare quality, but cannot be measured easily using administrative claims databases and are not included in current pharmacy quality measurement systems (Deninger, 2015;EQuIPP, 2015a;Inland Empire Health Plan, 2014;Mascardo, 2016;Trygstad, 2015).…”

“…Estimates for rates of primary medication nonadherence (PMN) range from single digits to nearly 25% (Cheetham et al, 2013;Fischer et al, 2011;Fischer et al, 2014;Fischer et al, 2015;Jackson et al, 2014;Raebel et al, 2012;Shin et al, 2012). These estimates are for medications used to treat diseases including asthma, diabetes, hypertension, dyslipidemia and other conditions.…”

“…These estimates are for medications used to treat diseases including asthma, diabetes, hypertension, dyslipidemia and other conditions. Methods to evaluate PMN typically use e-prescribing data (Fischer et al, 2011;Fischer et al, 2014;Fischer et al, 2015;Jackson et al, 2014;Pharmacy Quality Alliance, 2013), but some studies have used prescribing and dispensing data from integrated care settings (Cheetham et al, 2013;Raebel et al, 2012;Shin et al, 2012). Estimates do not vary systematically over source of prescription data.…”

“…Variation does exist in the definition of what constitutes a new prescription, with studies requiring no identical or same-class prescription at either 180 days (Fischer et al, 2011;Fischer et al, 2014;Jackson et al, 2014;Raebel et al, 2012) or 365 days (Cheetham et al, 2013;Fischer et al, 2015;Shin et al, 2012) prior to an index prescription date. Studies also vary in the time window used to evaluate whether or not a prescription was picked up, with some studies using days (Raebel et al, 2012;Shin et al, 2012), others 30 days (Fischer et al, 2014;Fischer et al, 2015) and some 90 days (Cheetham et al, 2013;Jackson et al, 2014) or "never filled" (Fischer et al, 2011). The development of a standard measure for PMN with a 180 day look-back period and a 30 day definition for an unfilled prescription should increase consistency of methods used in PMN studies (Pharmacy Quality Alliance, 2013).…”