Evidence map›Paper›PMID 35560685›Full record

ArticlePharmacoepidemiology and drug safety2022

Considerations for observational study design: Comparing the evidence of opioid use between electronic health records and insurance claims.

Jessica C Young, Nabarun Dasgupta, Til Stürmer, Virginia Pate, Michele Jonsson Funk

Abstract read
In one paragraph

Article in Pharmacoepidemiology and drug safety, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

5 authors.

Jessica C YoungCecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0003-2655-192X
Nabarun DasguptaInjury Prevention Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Til StürmerDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0002-9204-7177
Virginia PateDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Michele Jonsson FunkDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

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
UNC-CH TRAINING PROGRAM IN HEALTH SERVICES RESEARCHT32HS000032 · AHRQ · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HOLMES, GEORGE M · 1989 to 2024
$8.2M
Propensity scores and preventive drug use in the elderlyR01AG056479 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Til Sturmer · 2017 to 2026
$5.0M
Diversity within the Incidence, Prevalence, Treatment and Outcomes of Patients with IBDU01DP006369 · DP · CROHN'S AND COLITIS FDN OF AMERICA, INC. · PI HURTADO-LORENZO, ANDRES, KAPPELMAN, MICHAEL D · 2018 to 2022
$3.4M
Racial Differences in Treatment with Hysterectomy: a Multilevel InvestigationR01MD011680 · NIMHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ROBINSON, WHITNEY RAGAN · 2017 to 2021
$3.3M
Methods for Estimating Sex Differences in Safety and Effectiveness of DrugsR01HL118255 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI JONSSON FUNK, MICHELE LAURA · 2014 to 2017
$1.7M
Identifying opportunities to reduce unnecessary opioid exposure and prevent iatrogenic addiction after outpatient surgeryR36DA045885 · NIDA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI YOUNG, JESSICA C · 2018 to 2019
$143k
ACL HHS U01DP006369AHRQ HHS T32 HS000032NCATS NIH HHS UL1 TR002489NCCDPHP CDC HHS U01 DP006369NHLBI NIH HHS R01 HL118255NIA NIH HHS R01 AG056479NIDA NIH HHS R36 DA045885NIMHD NIH HHS R01 MD011680
6 · The paper itself

Abstract

purposePharmacoepidemiology studies often use insurance claims and/or electronic health records (EHR) to capture information about medication exposure. The choice between these data sources has important implications.

methodsWe linked EHR from a large academic health system (2015-2017) to Medicare insurance claims for patients undergoing surgery. Drug utilization was characterized based on medication order dates in the EHR, and prescription fill dates in Medicare claims. We compared opioid use documented in EHR orders to prescription claims in four time periods: 1) Baseline (182 days before surgery); 2) Perioperative period; 3) Discharge date; 4) Follow-up (90 days after surgery).

resultsWe identified 11 128 patients undergoing surgery. During baseline, 34.4% (EHR) versus 44.1% (claims) had evidence of opioid use, and 56.9% of all baseline use was reflected only in one data source. During the perioperative period, 78.8% (EHR) versus 47.6% (claims) had evidence of use. On the day of discharge, 59.6% (EHR) versus 45.5% (claims) had evidence of use, and 51.8% of all discharge use was reflected only in one data source. During follow-up, 4.3% (EHR) versus 10.4% (claims) were identified with prolonged opioid use following surgery with 81.4% of all prolonged use reflected only in one data source.

conclusionsWhen characterizing opioid exposure, we found substantial discrepancies between EHR medication orders and prescription claims data. In all time periods assessed, most patients' use was reflected only in the EHR, or only in the claims, not both. The potential for misclassification of drug utilization must be evaluated carefully, and choice of data source may have large impacts on key study design elements.

Indexed as

Observational Studies as TopicResearch DesignAgedAnalgesics, OpioidElectronic Health RecordsHumansInformation Storage and RetrievalMedicareOpioid-Related DisordersRetrospective StudiesUnited StatesAnalgesics, Opioiddata linkageEHRinsurance claimsopioidspharmacoepidemiology

Identifiers

PMID35560685
PMCPMC9271595

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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.