A Randomized Telephone Intervention Trial to Reduce Primary Medication Nonadherence

Fischer, Michael; Jones, James B.; Wright, Eric A.; Loan, Ryan P Van; Xie, Jing; Gallagher, Lauren; Wurst, Aaron M.; Shrank, William H.

doi:10.18553/jmcp.2015.21.2.124

Cited by 26 publications

(28 citation statements)

References 25 publications

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“…Although automated telephone reminders and letters have been shown to improve PNA to statins, 25 personal calls from patients' physicians did not result in further improve PNA. 26 Therefore, improvement in PNA may require tailored solutions that would be infeasible for use across all patients.…”

Section: Discussionmentioning

confidence: 99%

Time to Filling of New Prescriptions for Chronic Disease Medications Among a Cohort of Elderly Patients in the USA

et al. 2018

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Section: Discussionmentioning

confidence: 99%

Time to Filling of New Prescriptions for Chronic Disease Medications Among a Cohort of Elderly Patients in the USA

et al. 2018

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“…40 Real-time monitoring of pharmacy claims data could be used to intervene upon people who are no longer filling their ARV drug prescriptions and to offer adherence and other support. 41 …”

Section: Discussionmentioning

confidence: 99%

Do Persons Living with HIV Continue to Fill Prescriptions for Antiretroviral Drugs during a Gap in Care? Analysis of a Large Commercial Claims Database

Byrd

Bush

Gardner

2017

J Int Assoc Provid AIDS Care

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The significance of a gap in HIV care depends, at least partially, on whether patients continue to fill prescriptions for antiretroviral (ARV) drugs during the gap in care. We used a billing claims database to determine the proportion of persons who filled 1 prescription for ARV drugs during a gap in care (no clinic visit in >6 months). Persons were stratified into 3 groups: “never” (prescriptions never filled), “sometimes” (prescriptions filled >0%-<100% of months), and “always” (prescriptions filled monthly). Logistic regression analyses were conducted to determine factors associated with “never” filling ARV drugs. Of 14 308 persons, 69% (n = 9817), 13% (n = 1928), and 18% (n = 2563) “never,” “sometimes,” and “always” filled ARV drugs during the gap in care. Persons aged 18 to 29 years (odds ratio [OR] = 1.56, 95% confidence interval [CI] 1.39–1.74), women (OR = 1.67, CI 1.52–1.83), and persons from the Northeast region of the United States (OR = 1.86, CI 1.69–2.03) were more likely to never fill ARV drugs than persons aged ≥30 years, men, and persons outside the Northeast, respectively. Efforts should be made to minimize gaps in care, emphasize importance of therapy, and provide adherence support.

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“…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.…”

Section: B1 Primary Medication Nonadherencementioning

confidence: 99%

“…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.…”

Section: B1 Primary Medication Nonadherencementioning

confidence: 99%

“…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).…”

Section: B1 Primary Medication Nonadherencementioning

confidence: 99%

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

Urick¹

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Background: In response to high cost and inadequate quality, the healthcare system is in the midst of a transition from paying for volume to paying for value. Billions of dollars could be saved through more effective medication use, and evidence supports the role of the community pharmacist in lowering healthcare cost and improving healthcare quality through medication optimization. Despite this, value-based payment models for community pharmacies are rare, and those that do exist have not been critically evaluated and implementation in a commercially insured population is rare. Objective: The first objective was to design and test a conceptual model of pharmacy value. The second objective was to evaluate variation in the value community pharmacies provide a commercial insurer by assessing the relationship between attributed patients' healthcare quality and cost. Methods: This study used prescription and medical claims data for 2012 and 2013 from a large commercial insurer in Iowa and South Dakota. Patients were attributed to the pharmacy filling the majority of their prescriptions. Pharmacies' weekly prescription volume and Sunday prescription filling behavior were used as structural measures of healthcare quality. Percent of days covered (PDC) metrics for beta-blockers, statins, renin-angiotensin system antagonists and non-insulin diabetes agents were used as process metrics. Pharmacies were excluded if the denominator for any PDC metric was less than 15. Outcome metrics consisted of a non-trauma, non-cancer, unplanned hospitalization rate and a non-trauma ED visit rate. Cost impact was categorized into pharmaceutical, medical, and total cost of care. High quality pharmacies with typical or low associated costs or low cost pharmacies with typical to high quality were identified as high value and vice versa for low value. All metrics were risk-adjusted using mixed effect models with a random pharmacy intercept. The ratio between observed and expected quality scores was used for v quality scoring. Quality outliers were identified by comparing the 95% CI around pharmacies' risk-adjusted scores to the all-pharmacy risk-adjusted score mean. A t-test was used to assess variation in pharmacy value. Results: There were 171 pharmacies and 74,581 patients eligible for scoring on all quality metrics. Mixed effects models observed a small but significant impact of pharmacy on process and outcome healthcare quality. No relationship between structures and processes, processes and outcomes was detected. Ten pharmacies were scored as high quality and nine as low quality. Similar numbers were identified for cost outliers, and significant variation in value was detected. Implications/conclusions: Results support the hypothesis that high and low value pharmacies exist. A well-designed value-based payment model could be used to create incentives for pharmacists to enhance care for commercially insured patients, but validation is needed to ensure that incentives are aligned appropriately. vi

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A Randomized Telephone Intervention Trial to Reduce Primary Medication Nonadherence

Abstract: BACKGROUND: Primary medication nonadherence (PMN), defined as patients not picking up an initial prescription, can limit the effectiveness of therapy for chronic conditions. Effective interventions to reduce PMN have not been widely studied or implemented.

Cited by 26 publications

References 25 publications

Time to Filling of New Prescriptions for Chronic Disease Medications Among a Cohort of Elderly Patients in the USA

Time to Filling of New Prescriptions for Chronic Disease Medications Among a Cohort of Elderly Patients in the USA

Do Persons Living with HIV Continue to Fill Prescriptions for Antiretroviral Drugs during a Gap in Care? Analysis of a Large Commercial Claims Database

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

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