Evidence map›Paper›PMID 33574500›Full record

ArticleNPJ digital medicine2021

Internet search and medicaid prescription drug data as predictors of opioid emergency department visits.

Sean D Young, Qingpeng Zhang, Jiandong Zhou, Rosalie Liccardo Pacula

Abstract read
In one paragraph

Article in NPJ digital medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Potential Effects of Digital Inequality on Treatment Seeking for Opioid Use Disorder.International journal of mental health and addiction · 2023
    Article
  2. Article
  3. The role of social media in monitoring COVID-19 vaccine uptake.Journal of evaluation in clinical practice · 2022
    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

4 authors.

Sean D YoungDepartment of Emergency Medicine, University of California, Irvine, CA, USA. syoung5@hs.uci.edu.ORCID http://orcid.org/0000-0001-6052-4875
Qingpeng ZhangSchool of Data Science, City University of Hong Kong, Kowloon, Hong Kong SAR, China.
Jiandong ZhouSchool of Data Science, City University of Hong Kong, Kowloon, Hong Kong SAR, China.
Rosalie Liccardo PaculaThe Sol Price School of Public Policy and Leonard D. Schaeffer Center for Health Policy & Economics, University of Southern California, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0002-6145-9865

Funding

Optimal Methods for Estimating Policy Effect Heterogeneity in Opioid Policy ResearchP50DA046351 · NIDA · RAND CORPORATION · PI BRADLEY D STEIN · 2018 to 2026
$20.8M
Adapting the HOPE Online Support Intervention to Increase MAT Uptake Among OUD PatientsR33AT010606 · NCCIH · UNIVERSITY OF CALIFORNIA-IRVINE · PI YOUNG, SEAN · 2020 to 2021
$3.5M
Mining real-time social media big data to monitor HIV: Development and Ethical IssuesR01AI132030 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI YOUNG, SEAN · 2017 to 2020
$3.4M
Mining real-time social media big data to monitor HIV: Development and Ethical IssuesR56AI125105 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI CONDIE, TYSON, WANG, WEI · 2016 to 2016
$671k
Adapting the HOPE Online Support Intervention to Increase MAT Uptake Among OUD PatientsR61AT010606 · NCCIH · UNIVERSITY OF CALIFORNIA-IRVINE · PI YOUNG, SEAN · 2019 to 2019
$374k
NCCIH NIH HHS R33 AT010606NCCIH NIH HHS R61 AT010606NIAID NIH HHS R01 AI132030NIAID NIH HHS R56 AI125105NIDA NIH HHS P50 DA046351
6 · The paper itself

Abstract

The primary contributors to the opioid crisis continue to rapidly evolve both geographically and temporally, hampering the ability to halt the growing epidemic. To address this issue, we evaluated whether integration of near real-time social/behavioral (i.e., Google Trends) and traditional health care (i.e., Medicaid prescription drug utilization) data might predict geographic and longitudinal trends in opioid-related Emergency Department (ED) visits. From January 2005 through December 2015, we collected quarterly State Drug Utilization Data; opioid-related internet search terms/phrases; and opioid-related ED visit data. Modeling was conducted using least absolute shrinkage and selection operator (LASSO) regression prediction. Models combining Google and Medicaid variables were a better fit and more accurate (R

Identifiers

PMID33574500
PMCPMC7878816

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.