Evidence map›Paper›PMID 41067255›Full record

ArticleAmerican journal of epidemiology2026

Identifying observable medication use time in administrative databases: a tutorial using nursing home residents.

Daniel A Harris, Adam D'Amico, Hemalkumar B Mehta, Lori A Daiello, Sarah D Berry, Charles E Leonard, Yu-Chia Hsu, Douglas Kiel, Kaleen N Hayes, Melissa Riester and 4 more

Abstract read
In one paragraph

Article in American journal of epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Drug-Drug Interactions in Nursing Home Residents With vs Without Dementia.Journal of the American Medical Directors Association · 2026
    Observational
  2. Article
  3. Article
  4. Article
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

14 authors.

Daniel A HarrisDepartment of Epidemiology, College of Health Sciences, University of Delaware, Newark, DE, United States.
Adam D'AmicoCenter for Gerontology and Healthcare Research,School of Public Health, Brown University, Providence, RI, United States.
Hemalkumar B MehtaCenter for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.
Lori A DaielloDepartment of Health Services, Policy, and Practice, School of Public Health, Brown University, Providence, RI, United States.
Sarah D BerryHinda and Arthur Marcus Institute for Aging Research, Hebrew Senior Life, Boston, MA, United States.
Charles E LeonardDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.ORCID 0000-0002-5092-9657
Yu-Chia HsuDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Douglas KielHinda and Arthur Marcus Institute for Aging Research, Hebrew Senior Life, Boston, MA, United States.ORCID 0000-0001-8474-0310
Kaleen N HayesDepartment of Health Services, Policy, and Practice, School of Public Health, Brown University, Providence, RI, United States.ORCID 0000-0002-1122-0071
Melissa RiesterCenter for Gerontology and Healthcare Research,School of Public Health, Brown University, Providence, RI, United States.ORCID 0000-0003-2196-0134
Jimmie E RobertsHinda and Arthur Marcus Institute for Aging Research, Hebrew Senior Life, Boston, MA, United States.
Laura ReichDepartment of Epidemiology, School of Public Health, Brown University, Providence, RI, United States.
Peyton FreeDepartment of Epidemiology, College of Health Sciences, University of Delaware, Newark, DE, United States.
Andrew R ZulloDepartment of Health Services, Policy, and Practice, School of Public Health, Brown University, Providence, RI, United States.ORCID 0000-0003-1673-4570

Funding

Drug interactions involving psychoactive drugsR01AG060975 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Charles Edward Leonard · 2019 to 2026
$3.9M
Clinically Significant Drug Interactions among Nursing Home Residents with ADRDR01AG077620 · NIA · BROWN UNIVERSITY · PI Andrew Reis Zullo · 2022 to 2026
$3.5M
Medications and the Risk of Motor Vehicle Crashes in Older AdultsR01AG065722 · NIA · BROWN UNIVERSITY · PI ZULLO, ANDREW REIS · 2020 to 2023
$2.1M
NIA NIH HHS R01 AG060975NIA NIH HHS R01AG060975NIA NIH HHS R01 AG065722NIA NIH HHS R01 AG077620NIA NIH HHS R01AG077620
6 · The paper itself

Abstract

Nursing home (NH) residents are an important population for pharmacoepidemiologic research due to their prevalence of multimorbidity and polypharmacy. Medicare claims are commonly used to study medication use in this population, but medications dispensed during hospitalizations or post-acute care are unobservable due to bundled payment structures. We developed algorithms to identify NH days when medication dispensings can be observed in claims. Using a cohort of NH residents in the United States from 2013 to 2020, we linked Medicare fee-for-service (FFS) claims with Minimum Data Set clinical assessments. NH days were classified as "observable medication use time" if residents were enrolled in Medicare parts A, B, and D were not receiving post-acute care and were not hospitalized. Among 12.3 million NH residents and 2.7 billion NH days, 1.1 billion days (72.4% of Medicare-enrolled days and 39.6% of all NH days) were identified as observable medication use time. Within the first 100 days of NH admission, 27.3% of days were medication-observable, increasing to 89.4% after 100 days. On average, we identified 68% more person-time, and 51% more residents, compared to standard 100-day definitions for "long-stay" NH residents. Our algorithms enhance researchers' ability to measure medication exposure time, improving the validity of pharmacoepidemiologic studies.

Indexed as

Nursing HomesPharmacoepidemiologyAgedAged, 80 and overAlgorithmsDatabases, FactualFee-for-Service PlansFemaleHumansMaleMedicarePolypharmacyUnited Statesagingbiasepidemiologic methodsMedicarepharmacoepidemiology

Identifiers

PMID41067255
PMCPMC12809372

What OpenQuestion holds

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LicenceCC BY
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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.