Evidence map›Paper›PMID 41931129›Full record

ArticleCancer causes & control : CCC2026

Comparing endocrine therapy adherence across EHR and claims data by race and ethnicity, language, and insurance.

Michelle O Sodipo, Alicia K Morgans, Lorelei A Mucci, Audra Hite Morris, Beza Tadess, Sebastien Haneuse, Erica T Warner

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Cancer causes & control : CCC, 2026. 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
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0citing papers in PubMed
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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

7 authors.

Michelle O SodipoDepartment of Epidemiology, Harvard T. H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02120, USA. msodipo@g.harvard.edu.ORCID http://orcid.org/0000-0001-5001-7298
Alicia K MorgansDana-Farber Cancer Institute, Boston, MA, USA.
Lorelei A MucciDepartment of Epidemiology, Harvard T. H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02120, USA.
Audra Hite MorrisClinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, Boston, MA, 02114, USA.
Beza TadessDepartment of Obstetrics and Gynecology, UW Medicine, Madison, WI, USA.
Sebastien HaneuseDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
Erica T WarnerClinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, Boston, MA, 02114, USA.ORCID http://orcid.org/0000-0002-2671-0313

Funding

Training Program in Cancer EpidemiologyT32CA009001 · NCI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI A. Heather Eliassen, Meir Stampfer · 1985 to 2026
$17.3M
MGH Executive Committee on Research Physician Scientist Development AwardNCI NIH HHS T32CA009001
6 · The paper itself

Abstract

purposeWe compared adherence measurements across electronic health records (EHRs) and claims data for 79 HR + breast cancer survivors, considering their race, ethnicity, language, and insurance status.

methodsAdherence was evaluated using the medication possession ratio (MPR) and proportion of days covered (PDC). The correlation between EHR and claims data was assessed with Spearman correlation coefficients, while Kaplan-Meier curves were employed to visualize and analyze the time to the first instance of non-adherence and the time to discontinuation.

resultsA total of 75 breast cancer patients receiving care at Massachusetts General Hospital (MGH) were identified. While there was a positive correlation, EHR data tended to overestimate adherence based on medication prescriptions, while claims data captured adherence through prescription fills. Kaplan-Meier analyses demonstrated differences in the time to first non-adherence between EHR and claims data sources, with observed variations based on language and insurance status.

conclusionOur findings suggest that EHR and claims data offer complementary insights into adherence measurement, and their integration could improve adherence assessment across diverse populations.

Indexed as

Antineoplastic Agents, HormonalBreast NeoplasmsDrug MonitoringElectronic Health RecordsMedication AdherenceAgedEthnicityFemaleHumansInsurance, HealthLanguageMiddle AgedRacial GroupsAntineoplastic Agents, HormonalBreast cancerElectronic health recordsEndocrine therapyHealth insurance claimsMedication adherence

Identifiers

PMID41931129

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.