Evidence map›Paper›PMID 39607302›Full record

ArticleJournal of the American Geriatrics Society2025

Defining key deprescribing measures from electronic health data: A multisite data harmonization project.

Sascha Dublin, Ladia Albertson-Junkans, Thanh Phuong Pham Nguyen, Juliessa M Pavon, S Nicole Hastings, Matthew L Maciejewski, Allison Willis, Lindsay Zepel, Sean Hennessy, Kathleen B Albers and 6 more

Abstract readMulticenter Study
In one paragraph

Article in Journal of the American Geriatrics Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Trial
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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

16 authors.

Sascha DublinKaiser Permanente Washington Health Research Institute, Seattle, Washington, USA.ORCID 0000-0002-6649-3659
Ladia Albertson-JunkansKaiser Permanente Washington Health Research Institute, Seattle, Washington, USA.
Thanh Phuong Pham NguyenUniversity of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.ORCID 0000-0003-3589-764X
Juliessa M PavonDuke University School of Medicine, Durham, North Carolina, USA.ORCID 0000-0002-9047-0051
S Nicole HastingsDuke University School of Medicine, Durham, North Carolina, USA.
Matthew L MaciejewskiDuke University School of Medicine, Durham, North Carolina, USA.
Allison WillisUniversity of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Lindsay ZepelDepartment of Population Health Sciences, Duke University, Durham, North Carolina, USA.
Sean HennessyUniversity of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Kathleen B AlbersKaiser Permanente Colorado Institute for Health Research, Aurora, Colorado, USA.
Danielle MoweryUniversity of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Amy G ClarkDepartment of Population Health Sciences, Duke University, Durham, North Carolina, USA.
Sunil ThomasUniversity of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Michael A SteinmanDivision of Geriatrics, University of California San Francisco, San Francisco, California, USA.ORCID 0000-0002-9564-9480
Cynthia M BoydDivision of Geriatric Medicine and Gerontology and Center for Transformative Geriatric Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Elizabeth A BaylissKaiser Permanente Colorado Institute for Health Research, Aurora, Colorado, USA.

Funding

Resource Core 3 - Metabolomics CoreP30AG028716 · NIA · DUKE UNIVERSITY · PI Sarah B. Peskoe · 2006 to 2026
$24.6M
U.S. Deprescribing Research NetworkR24AG064025 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI BOYD, CYNTHIA MELINDA, STEINMAN, MICHAEL A. · 2019 to 2023
$9.9M
The U.S. Deprescribing Research NetworkR33AG086944 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI CYNTHIA Melinda BOYD, MICHAEL A. STEINMAN · 2024 to 2026
$2.5M
Midcareer Development Award in Neuroaging and Geriatric Pharmacoepidemiology ResearchK24AG075234 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Allison Willis · 2022 to 2026
$808k
Deprescribing Central Nervous System Medications in Hospitalized Older AdultsK23AG058788 · NIA · DUKE UNIVERSITY · PI PAVON, JULIESSA M · 2019 to 2023
$797k
NIA NIH HHS 1K23 AG058788-03NIA NIH HHS K23 AG058788NIA NIH HHS K24 AG075234NIA NIH HHS P30 AG028716NIA NIH HHS R24 AG064025NIA NIH HHS R24AG064025NIA NIH HHS R33 AG086944VA RCS 10-391
6 · The paper itself

Abstract

backgroundStopping or reducing risky or unneeded medications ("deprescribing") could improve older adults' health. Electronic health data can support observational and intervention studies of deprescribing, but there are no standardized measures for key variables, and healthcare systems have differing data types and availability. We developed definitions for chronic medication use and discontinuation based on electronic health data and applied them in a case study of benzodiazepines and Z-drugs in five diverse US healthcare systems.

methodsWe conducted a retrospective cohort study of adults age 65+ from 2017 to 2019 with chronic benzodiazepine or Z-drug use. We determined whether sites had access to medication orders and/or dispensings. We developed definitions for chronic use and discontinuation using both data types. Discontinuation definitions were based on (1) gaps in medication availability during follow-up or (2) not having medication available at a fixed time point. We examined the impact of varying the gap length and requiring a 30-day period without orders/dispensings ("halo") around the fixed time point. We compared results derived from orders versus dispensings at one site.

resultsApproximately 1.6%-2.6% of older adults had chronic benzodiazepine/Z-drug use (total N = 6775, ranging from 431 to 2122 across sites). Depending on the definition and site, the proportion discontinuing use during 12 months ranged from 6% to 49%. Requiring a longer gap or a 30-day "halo" resulted in lower estimates. At one site, only 56% of those with chronic use defined from orders also qualified based on dispensings, and the discontinuation rate at 180 days was 20% from orders versus 32% from dispensings.

conclusionsRequiring a gap of ≥90 days or a "halo" around a time point may more accurately capture discontinuation than using a shorter gap or no halo. Orders data underestimate discontinuation compared to dispensings. Work is needed to adapt these definitions for other drug classes and settings.

Indexed as

BenzodiazepinesDeprescriptionsElectronic Health RecordsAgedAged, 80 and overFemaleHumansMalePolypharmacyRetrospective StudiesUnited StatesBenzodiazepinesbenzodiazepinesdeprescribingelectronic health recordsmeasurementmedication discontinuation

Identifiers

PMID39607302
PMCPMC12278905

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.