Evidence map›Paper›PMID 38849888›Full record

ArticleAddiction science & clinical practice2024

Using 42 CFR part 2 revisions to integrate substance use disorder treatment information into electronic health records at a safety net health system.

Alexandra R Tillman, Emily Bacon, Brooke Bender, Dean McEwen, Joshua Blum, Matthew Hoag, Kenneth A Scott, Rachel Everhart, Rebecca Hanratty, Laura J Podewils and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Addiction science & clinical practice, 2024. 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. 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

13 authors.

Alexandra R TillmanDenver Health and Hospital Authority, 777 Bannock Street, Denver, CO, 80204, USA. alexandra.tillman@dhha.org.ORCID 0000-0001-5699-6466
Emily BaconDenver Health and Hospital Authority, 777 Bannock Street, Denver, CO, 80204, USA.
Brooke BenderDenver Health and Hospital Authority, 777 Bannock Street, Denver, CO, 80204, USA.
Dean McEwenDenver Health and Hospital Authority, 777 Bannock Street, Denver, CO, 80204, USA.
Joshua BlumDenver Health and Hospital Authority, 777 Bannock Street, Denver, CO, 80204, USA.
Matthew HoagDenver Health and Hospital Authority, 777 Bannock Street, Denver, CO, 80204, USA.
Kenneth A ScottDenver Health and Hospital Authority, 777 Bannock Street, Denver, CO, 80204, USA.
Rachel EverhartDenver Health and Hospital Authority, 777 Bannock Street, Denver, CO, 80204, USA.
Rebecca HanrattyDenver Health and Hospital Authority, 777 Bannock Street, Denver, CO, 80204, USA.
Laura J PodewilsDenver Health and Hospital Authority, 777 Bannock Street, Denver, CO, 80204, USA.
Carolina CloseDenver Health and Hospital Authority, 777 Bannock Street, Denver, CO, 80204, USA.
John MillsDenver Health and Hospital Authority, 777 Bannock Street, Denver, CO, 80204, USA.
Arthur J DavidsonDenver Health and Hospital Authority, 777 Bannock Street, Denver, CO, 80204, USA.

Funding

CTSA INFRASTRUCTURE FOR PEDIATRIC RESEARCHUL1RR025780 · NCRR · UNIVERSITY OF COLORADO DENVER · PI SOKOL, RONALD J. · 2008 to 2011
$61.3M
Agency for Healthcare Research and Quality R18HS027389NCRR NIH HHS UL1 RR025780
6 · The paper itself

Abstract

backgroundRegulations put in place to protect the privacy of individuals receiving substance use disorder (SUD) treatment have resulted in an unintended consequence of siloed SUD treatment and referral information outside of the integrated electronic health record (EHR). Recent revisions to these regulations have opened the door to data integration, which creates opportunities for enhanced patient care and more efficient workflows. We report on the experience of one safety-net hospital system integrating SUD treatment data into the EHR.

methodsSUD treatment and referral information was integrated from siloed systems into the EHR through the implementation of a referral order, treatment episode definition, and referral and episode-related tools for addiction therapists and other clinicians. Integration was evaluated by monitoring SUD treatment episode characteristics, patient characteristics, referral linkage, and treatment episode retention before and after integration. Satisfaction of end-users with the new tools was evaluated through a survey of addiction therapists.

resultsAfter integration, three more SUD treatment programs were represented in the EHR. This increased the number of patients that could be tracked as initiating SUD treatment by 250%, from 562 before to 1,411 after integration. After integration, overall referral linkage declined (74% vs. 48%) and treatment episode retention at 90-days was higher (45% vs. 74%). Addiction therapists appreciated the efficiency of having all SUD treatment information in the EHR but did not find that the tools provided a large time savings shortly after integration.

conclusionsIntegration of SUD treatment program data into the EHR facilitated both care coordination in patient treatment and quality improvement initiatives for treatment programs. Referral linkage and retention rates were likely modified by a broader capture of patients and changed outcome definition criteria. Greater preparatory workflow analysis may decrease initial end-user burden. Integration of siloed data, made possible given revised regulations, is essential to an efficient hub-and-spoke model of care, which must standardize and coordinate patient care across multiple clinics and departments.

Indexed as

Electronic Health RecordsReferral and ConsultationSafety-net ProvidersSubstance-Related DisordersAdultConfidentialityFemaleHumansMale42 CFR Part 2Data integrationElectronic health recordHub-and-spokeSubstance use disorder treatment

Identifiers

PMID38849888
PMCPMC11157711

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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.