Evidence map›Paper›PMID 33913205›Full record

ArticlePharmacoepidemiology and drug safety2021

Linkage of public health and all payer claims data for population-level opioid research.

Sara E Hallvik, Nazanin Dameshghi, Sanae El Ibrahimi, Michelle A Hendricks, Christi Hildebran, Carissa J Bishop, Scott G Weiner

Abstract read
In one paragraph

Article in Pharmacoepidemiology and drug safety, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

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

10 citing papers in PubMed.

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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.

Sara E HallvikDepartment of Research & Evaluation, Comagine Health, Portland, Oregon, USA.ORCID 0000-0003-1501-9129
Nazanin DameshghiDepartment of Research & Evaluation, Comagine Health, Portland, Oregon, USA.
Sanae El IbrahimiDepartment of Research & Evaluation, Comagine Health, Portland, Oregon, USA.ORCID 0000-0002-7825-5121
Michelle A HendricksDepartment of Research & Evaluation, Comagine Health, Portland, Oregon, USA.
Christi HildebranDepartment of Research & Evaluation, Comagine Health, Portland, Oregon, USA.
Carissa J BishopDepartment of Research & Evaluation, Comagine Health, Portland, Oregon, USA.
Scott G WeinerDepartment of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.

Funding

Using a Novel Comprehensive Linked Dataset to Determine Early Predictors of Opioid OverdoseR01DA044167 · NIDA · BRIGHAM AND WOMEN'S HOSPITAL · PI WEINER, SCOTT GORDON · 2018 to 2022
$2.6M
NIDA NIH HHS R01 DA044167
6 · The paper itself

Abstract

objectiveOur objective is to describe how we combine, at an individual level, multiple administrative datasets to create a Comprehensive Opioid Risk Registry (CORR). The CORR will characterize the role that individual characteristics, household characteristics, and community characteristics have on an individual's risk of opioid use disorder or opioid overdose. DATA SOURCES: Study data sources include the voluntary Oregon All Payer Claims Database (APCD), American Community Survey Census Data, Oregon Death Certificate data, Oregon Hospital Discharge Data (HDD), and Oregon Prescription Drug Monitoring (PDMP) Data in 2013-2018. STUDY

designTo create the CORR we first prepared the APCD data set by cleaning and geocoding addresses, creating a community grouper and adding census indices, creating household grouper, and imputing patient race. Then we deployed a probabilistic linkage methodology to incorporate other data sources maintaining compliance with strict data governance regulations. DATA COLLECTION/EXTRACTION

methodsAdministrative datasets were obtained through an executed data use agreement with each data owner. The APCD served as the population universe to which all other data sources were linked. PRINCIPAL

findingsThere were 3 628 992 unique people in the APCD over the entire study period. We identified 968 767 unique households in 2013 and 1 209 236 in 2018, and geocoded patient addresses representing all census tracts in Oregon. Census, death certificate, HDD, and PDMP datasets were successfully linked to this population universe.

conclusionsThis methodology can be replicated in other states and may also apply to a broad array of health services research topics.

Indexed as

Opioid-Related DisordersPrescription Drug Monitoring ProgramsAnalgesics, OpioidData ManagementHumansPublic HealthUnited StatesAnalgesics, Opioidadministrative datahealth services researchlinkageopioidspharmacoepidemiology

Identifiers

PMID33913205
PMCPMC8172471

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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.