Evidence map›Paper›PMID 32220412›Full record

ArticleJournal of substance abuse treatment2020

Using a health information technology survey to explore the availability of addiction treatment data in the electronic health records: A National Drug Abuse Treatment Clinical Trials Network study.

Li-Tzy Wu, Elizabeth H Payne, Kimberly Roseman, Ashley Case, Casey Nelson, Robert Lindblad

Open access · hybridAbstract read
In one paragraph

Article in Journal of substance abuse treatment, 2020. 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
0.7field-weighted citation impact, top 28% of its field
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, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

6 authors at 3 institutions in 1 country.

Li-Tzy WuDepartment of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA; Department of Medicine, Division of General Internal Medicine, Duke University School of Medicine, Durham, NC, USA; Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA; Center for Child and Family Policy, Sanford School of Public Policy, Duke University, Durham, NC, USA. Electronic address: litzy.wu@duke.edu.
Elizabeth H PayneThe Emmes Company, LLC, Rockville, MD, USA.
Kimberly RosemanDuke Clinical and Translational Science Institute, Duke University Medical Center, Durham, NC, USA.
Ashley CaseThe Emmes Company, LLC, Rockville, MD, USA.
Casey NelsonThe Emmes Company, LLC, Rockville, MD, USA.
Robert LindbladThe Emmes Company, LLC, Rockville, MD, USA.
Emmes (United States) · USClinical Research Institute · USDuke Medical Center · US

Funding

Project-003UG1DA040317 · NIDA · DUKE UNIVERSITY · PI WU, LI-TZY · 2015 to 2019
$9.0M
Substance Abuse & Treatment Gaps in Asians, Pacific Islanders & Multiple-race IndR01MD007658 · NIMHD · DUKE UNIVERSITY · PI WU, LI-TZY · 2013 to 2017
$1.8M
NIDA NIH HHS HHSN271201400028CNIDA NIH HHS HHSN271201500065CNIDA NIH HHS UG1 DA040317NIMHD NIH HHS R01 MD007658
6 · The paper itself

Abstract

backgroundHealthcare data from electronic health records (EHRs) and related health information technology (IT) tools are critical data sources for pragmatic clinical trials and observational studies aimed at producing real-world evidence. To unlock the full potential of such data to advance science, the data must be complete and in structured formats to facilitate research use.

methodsA Health IT survey was conducted within the National Drug Abuse Treatment Clinical Trials Network (CTN) to explore information related to data completeness and presence of unstructured data (e.g., clinical notes, free text) for conducting the EHR-based research for substance use disorders (SUDs). The analysis was based on 36 participants from 36 facilities located in 14 states and affiliated with the CTN.

resultsThe mean age of the participants (n = 34) was 48.0 years (SD = 9.8). Of the participants enrolled, 50.0% were female and 82.4% were white. Participants' facilities were from four census-defined regions (South 35.3%, Northeast 29.4%, West 20.6%, Midwest 11.8%, Missing 2.9%) and represented diverse settings. The EHR was used by all surveyed facilities including 17 different kinds of EHR platforms or vendors, and 17.6% (n = 6) of surveyed facilities also used a separate EHR for behavioral health care (e.g., SUD care). Paper records were also used by 76.5% of surveyed facilities for clinical care (e.g., for health risk appraisal questionnaires, substance use screening or assessment, check-in screening, substance use specific intervention/treatment or referral, or labs/testing). The prevalence of using a patient portal, practice management system, and mHealth for patient care was 76.5%, 50.0%, and 29.4%, respectively.

conclusionWhile results are descriptive in nature, they reveal the heterogeneity in the existing EHRs and frequent use of paper records to document patient care tasks, especially for SUD care. The use of a separate EHR for behavioral healthcare also suggests the challenge of obtaining complete EHR data to support research for SUDs. Much EHR development, integration, and standardization needs to be done especially in regard to SUD treatment to facilitate research across disparate healthcare systems.

Indexed as

Medical InformaticsSubstance-Related DisordersElectronic Health RecordsFemaleHumansInfant, NewbornResearch DesignSurveys and QuestionnairesClinical Trials NetworkCommon data elementsElectronic health recordsHealth information technologySubstance use disorder

Identifiers

PMID32220412
PMCPMC7134339
OpenAlexW3013897179

What OpenQuestion 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 OpenQuestion graph.