Evidence map›Paper›PMID 31663457›Full record

ArticleJournal of managed care & specialty pharmacy2019

Closing the Gap: Identifying Rates and Reasons for Nonadherence in a Specialty Population.

Dominic Paolella, Elizabeth Cherry, Jacob A Jolly, Joshua DeClercq, Leena Choi, Autumn Zuckerman

Abstract read
In one paragraph

Article in Journal of managed care & specialty pharmacy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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  9. Development, implementation, and evaluation of a health outcomes and research program at an integrated health-system specialty pharmacy.American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Dominic PaolellaBelmont University College of Pharmacy, Nashville, Tennessee.
Elizabeth CherryVanderbilt Specialty Pharmacy, Vanderbilt University Medical Center, Nashville, Tennessee.
Jacob A JollyVanderbilt Specialty Pharmacy, Vanderbilt University Medical Center, Nashville, Tennessee.
Joshua DeClercqVanderbilt Specialty Pharmacy, Vanderbilt University Medical Center, Nashville, Tennessee.
Leena ChoiVanderbilt Specialty Pharmacy, Vanderbilt University Medical Center, Nashville, Tennessee.
Autumn ZuckermanVanderbilt Specialty Pharmacy, Vanderbilt University Medical Center, Nashville, Tennessee.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdherence to specialty and nonspecialty medications is often calculated using pharmacy claims data. However, specialty medication regimens are complex and may require periods of intentional gaps in therapy. Common adherence calculations are insufficient in identifying reasons for gaps in therapy. Because adherence reporting is a growing measure of quality care for specialty pharmacy accreditation and payer and manufacturer contracts, a better understanding of the rates and reasons for nonadherence within a specialty population is needed.

objectiveTo identify rates and reasons for misidentified and true nonadherence in patients who are prescribed specialty medications.

methodsA single center, retrospective cohort study was conducted using pharmacy claims data between March 2017 and February 2018. Medication adherence was calculated using proportion of days covered (PDC). Electronic medical records of a random 10% sample of nonadherent patients (PDC < 80%) were manually reviewed to identify reasons for nonadherence. Patients were then classified as either (a) misidentified as nonadherent (i.e., a provider-directed discontinuation or disruption of treatment that varies from the prescribed administration schedule or transfer of the prescription to an external pharmacy) or (b) truly nonadherent (discontinuation or disruption of treatment that varies from the prescribed administration instruction that is not directed or recommended by the provider or health care team).

resultsOf the 7,488 included prescription records from 18 specialty areas, 1,059 met criteria for nonadherence. 105 prescription records (representing 105 unique patients) were manually reviewed; most of these patients (58%) were truly nonadherent, driven by inability to contact patients for refills (59%). However, 40% were misidentified as nonadherent, most due to provider-directed medication holding (69%). Two percent of patients were nonadherent for unknown reasons.

conclusionsMany patients classified as nonadherent based on pharmacy claims experienced gaps in therapy due to medically appropriate reasons. Methods to better measure and identify true nonadherence are needed to efficiently and adequately affect specialty medication adherence behavior. DISCLOSURES: This study received funding support from CTSA Award No. UL1 TR002243 from the National Center for Advancing Translational Sciences. Study findings and conclusions are solely the responsibility of the authors and do not necessarily represent official views of the National Center for Advancing Translational Sciences or the National Institutes of Health. Zuckerman reports research support from Sanofi and Gilead Sciences, unrelated to this study. The other authors have nothing to disclose. A poster based on the data from this study was presented at AMCP Nexus 2018 on October 24, 2018, in Orlando, FL.

Indexed as

Drug MonitoringAdultAgedElectronic Health RecordsFemaleHepatitis CHIV InfectionsHumansMaleMedication Therapy ManagementMiddle AgedOutpatient Clinics, HospitalPharmacy Service, HospitalPulmonary Arterial HypertensionRetrospective StudiesUnited States

Identifiers

PMID31663457
PMCPMC10398139

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.