Evidence map›Paper›PMID 38556843›Full record

ArticlePharmacoepidemiology and drug safety2024

Validating claims-based definitions for deprescribing: Bridging the gap between clinical and administrative data.

Joshua D Niznik, Shahar Shmuel, Virginia Pate, Carolyn T Thorpe, Laura C Hanson, Colleen Rice, Jennifer L Lund

Abstract read
In one paragraph

Article in Pharmacoepidemiology and drug safety, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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

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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

7 authors.

Joshua D NiznikDivision of Geriatric Medicine, University of North Carolina at Chapel Hill, School of Medicine, Chapel Hill, North Carolina, USA.ORCID 0000-0003-1466-5751
Shahar ShmuelDepartment of Epidemiology, University of North Carolina at Chapel Hill, Gillings School of Global Public Health, Chapel Hill, North Carolina, USA.ORCID 0000-0003-1726-1875
Virginia PateDepartment of Epidemiology, University of North Carolina at Chapel Hill, Gillings School of Global Public Health, Chapel Hill, North Carolina, USA.
Carolyn T ThorpeDivision of Pharmaceutical Outcomes and Policy, University of North Carolina at Chapel Hill, Eshelman School of Pharmacy, Chapel Hill, North Carolina, USA.
Laura C HansonDivision of Geriatric Medicine, University of North Carolina at Chapel Hill, School of Medicine, Chapel Hill, North Carolina, USA.
Colleen RiceTranslational and Clinical Sciences Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Jennifer L LundDepartment of Epidemiology, University of North Carolina at Chapel Hill, Gillings School of Global Public Health, Chapel Hill, North Carolina, USA.ORCID 0000-0002-1108-0689

Funding

Re-Entry Supplement: Investigation of Oral Microbial Enzymes for the Detection and Treatment of Periodontal DiseaseUL1TR002489 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, SHAHEEN, NICHOLAS J · 2018 to 2022
$48.6M
North Carolina Translational and Clinical Sciences Institute (NC TraCS)UM1TR004406 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI NICHOLAS J SHAHEEN · 2023 to 2026
$37.5M
Propensity scores and preventive drug use in the elderlyR01AG056479 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Til Sturmer · 2017 to 2026
$5.0M
Deprescribing Bisphosphonates in Older Nursing Home Residents with DementiaK08AG071794 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI NIZNIK, JOSHUA DAVID · 2021 to 2025
$724k
NCATS NIH HHS UL1 TR002489NCATS NIH HHS UM1 TR004406NIA NIH HHS K08 AG071794NIA NIH HHS R01 AG056479NIH HHS
6 · The paper itself

Abstract

backgroundLimited research has evaluated the validity of claims-based definitions for deprescribing.

objectivesEvaluate the validity of claims-based definitions of deprescribing against electronic health records (EHRs) for deprescribing of benzodiazepines (BZDs) after a fall-related hospitalization.

methodsWe used a novel data linkage between Medicare fee-for-service (FFS) and Part D with our health system's EHR. We identified patients aged ≥66 years with a fall-related hospitalization, continuous enrollment in Medicare FFS and Part D for 6 months pre- and post-hospitalization, and ≥2 BZD fills in the 6 months pre-hospitalization. Using a standardized EHR abstraction tool, we adjudicated deprescribing for a sub-sample with a fall-related hospitalization at UNC. We evaluated the validity of claims-based deprescribing definitions (e.g., gaps in supply, dosage reductions) versus chart review using sensitivity and specificity.

resultsAmong 257 patients in the overall sample, 44% were aged 66-74 years, 35% had Medicare low-income subsidy, 79% were female. Among claims-based definitions using gaps in supply, the prevalence of BZD deprescribing ranged from 8.2% (no refills) to 36.6% (30-day gap). When incorporating dosage, the prevalence ranged from 55.3% to 65.8%. Among the validation sub-sample (n = 47), approximately one-third had BZDs deprescribed in the EHR. Compared to EHR, gaps in supply from claims had good sensitivity, but poor specificity. Incorporating dosage increased sensitivity, but worsened specificity.

conclusionsThe sensitivity of claims-based definitions for deprescribing of BZDs was low; however, the specificity of a 90-day gap was >90%. Replication in other EHRs and for other low-value medications is needed to guide future deprescribing research.

Indexed as

DeprescriptionsMedicareAgedBenzodiazepinesElectronic Health RecordsFemaleForecastingHospitalizationHumansMaleUnited StatesBenzodiazepinesdeprescribinggeriatricsMedicaremethodsstudy design

Identifiers

PMID38556843
PMCPMC11145562

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.