Evidence map›Paper›PMID 41409678›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Measuring Adherence to Multiple Medications Using Guideline-Directed Medical Therapy as a Model.

Eli Reynolds, Xiyue Li, Amrita Mukhopadhyay, Samrachana Adhikari, Carine E Hamo, Adam Berman, Morgan E Grams, Saul Blecker

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Eli ReynoldsDepartment of Internal Medicine, New York University Langone Health.ORCID 0000-0002-4320-0366
Xiyue LiDepartment of Population Health, New York University Langone Health.ORCID 0000-0001-7331-8544
Amrita MukhopadhyayDepartment of Population Health, New York University Langone Health.ORCID 0000-0002-7768-459X
Samrachana AdhikariDepartment of Population Health, New York University Langone Health.ORCID 0000-0001-9954-5999
Carine E HamoDepartment of Population Health, New York University Langone Health.
Adam BermanDepartment of Population Health, New York University Langone Health.
Morgan E GramsDepartment of Population Health, New York University Langone Health.ORCID 0000-0002-4430-6023
Saul BleckerDepartment of Internal Medicine, New York University Langone Health.ORCID 0000-0003-4460-1046

Funding

Addressing antihypertensive medication adherence through EHR-enabled teamlets in primary care - Resubmission - 1R01HL156355 · NHLBI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI BLECKER, SAUL B., MANN, DEVIN M · 2021 to 2025
$4.0M
Generalizable prediction of medication adherence in heart failureR01HL155149 · NHLBI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ADHIKARI, SAMRACHANA, BLECKER, SAUL B. · 2021 to 2025
$3.9M
Impact of Restrictive Drug Coverage Policies on Heart Failure CareK23HL171636 · NHLBI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Amrita Mukhopadhyay · 2024 to 2026
$597k
NHLBI NIH HHS K23 HL171636NHLBI NIH HHS R01 HL155149NHLBI NIH HHS R01 HL156355
6 · The paper itself

Abstract

Background: There is no gold standard for measuring adherence to a complex medication regimen. Heart failure is a chronic disease state that requires multiple medications for optimal control, known as guideline-directed-medical therapy (GDMT), and can be used a model to explore approaches to assessing multi-medication adherence. We aimed to compare seven proportion of days covered (PDC) measures for assessing adherence to multiple GDMT medications and to evaluate their association with clinical outcomes. Methods: We conducted a large, single center, retrospective cohort study of 34,603 patients with heart failure who filled a GDMT prescription between April 2021 and July 2022. The primary outcomes were the seven PDC-based adherence measures derived from electronic health record and pharmacy data. PDC was defined as the proportion of days in which patients had possession of GDMT medications. Our secondary outcome was the combined clinical outcome of ED visits, hospitalizations, and death. Results: The seven measures provided a wide range of measured PDC adherence. Using the strictest measure, 'each' (>= 80% of days with each drug available) 54% of patients were considered adherent, compared with 73% measured adherence for the least restrictive measure, 'at least one'. Variability increased with increasing number of medications across all non-average based measures. For example, using the 'all' measure (a more restrictive PDC measure) adherence ranged from 0.53 to 0.41 with increasing number of GDMT prescriptions. Higher PDC for each of the seven measures was associated with increased number of ED, visits, hospitalizations, and death. There was no association with the combined outcome in patients with heart failure with reduced ejection fraction. Conclusions and Relevance: There was a wide variability in adherence measures for assessing adherence to GDMT depending on the measure used. This variability has significant implications for the policy, clinical, and intervention context to which the measure is applied.

Indexed as

adherenceGDMTheart failuremedication adherencemultiple medicationsproportion of days coveredproportion of days covered (PDC)

Identifiers

PMID41409678
PMCPMC12706614

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.