Evidence map›Paper›PMID 36977494›Full record

ArticleNicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco2023

Implementation, Maintenance, and Outcomes of an Electronic Referral to a Tobacco Quitline Across Five Health Systems.

Elisa K Tong, Shu-Hong Zhu, Christopher M Anderson, Mark V Avdalovic, Alpesh N Amin, Allison L Diamant, Timothy W Fong, Brian Clay, Robert El-Kareh, Sujatha Sankaran and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Trial
  2. Article
  3. Representativeness of Electronic Referral to Smoking Treatment Trials in Adult Primary Care.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2025
    Article
  4. Article
  5. 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

14 authors.

Elisa K TongDepartment of Internal Medicine, University of California, Davis, Sacramento, CA, USA.ORCID 0000-0002-8326-4524
Shu-Hong ZhuThe Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, USA.ORCID 0000-0002-4149-3441
Christopher M AndersonMoores Cancer Center, University of California, San Diego, La Jolla, CA, USA.ORCID 0000-0002-1801-6604
Mark V AvdalovicDepartment of Internal Medicine, University of California, Davis, Sacramento, CA, USA.
Alpesh N AminDepartment of Medicine, University of California, Irvine, Irvine, CA, USA.
Allison L DiamantDepartment of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Timothy W FongDepartment of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA.
Brian ClayDepartment of Medicine, University of California, San Diego, La Jolla, CA, USA.
Robert El-KarehDepartment of Medicine, University of California, San Diego, La Jolla, CA, USA.
Sujatha SankaranDepartment of Medicine, University of California, San Francisco, San Francisco, CA, USA.
Catherine BonniotSmoking Cessation Leadership Center, University of California, San Francisco, San Francisco, CA, USA.
Carrie A KirbyMoores Cancer Center, University of California, San Diego, La Jolla, CA, USA.
Antonio MayoralMoores Cancer Center, University of California, San Diego, La Jolla, CA, USA.
Linda SarnaSchool of Nursing, University of California, Los Angeles, Los Angeles, CA, USA.

Funding

CALIFORNIA QUITLINE CAPACITYU58DP004038 · DP · CALIFORNIA DEPARTMENT OF PUBLIC HEALTH · PI HAGAMAN, TONIA · 2012 to 2013
$4.8M
NCCDPHP CDC HHS U18 DP006136NCCDPHP CDC HHS U58 DP004038
6 · The paper itself

Abstract

introductionElectronic referral (e-referral) to quitlines helps connect tobacco-using patients to free, evidence-based cessation counseling. Little has been published about the real-world implementation of e-referrals across U.S. health systems, their maintenance over time, and the outcomes of e-referred patients. AIMS AND

methodsBeginning in 2014, the University of California (UC)-wide project called UC Quits scaled up quitline e-referrals and related modifications to clinical workflows from one to five UC health systems. Implementation strategies were used to increase site readiness. Maintenance was supported through ongoing monitoring and quality improvement programs. Data on e-referred patients (n = 20 709) and quitline callers (n = 197 377) were collected from April 2014 to March 2021. Analyses of referral trends and cessation outcomes were conducted in 2021-2022.

resultsOf 20 709 patients referred, the quitline contacted 47.1%, 20.6% completed intake, 15.2% requested counseling, and 10.9% received it. In the 1.5-year implementation phase, 1813 patients were referred. In the 5.5-year maintenance phase, volume was sustained, with 3436 referrals annually on average. Among referred patients completing intake (n = 4264), 46.2% were nonwhite, 58.8% had Medicaid, 58.7% had a chronic disease, and 48.8% had a behavioral health condition. In a sample randomly selected for follow-up, e-referred patients were as likely as general quitline callers to attempt quitting (68.5% vs. 71.4%; p = .23), quit for 30 days (28.3% vs. 26.9%; p = .52), and quit for 6 months (13.6% vs. 13.9%; p = .88).

conclusionsWith a whole-systems approach, quitline e-referrals can be established and sustained across inpatient and outpatient settings with diverse patient populations. Cessation outcomes were similar to those of general quitline callers. IMPLICATIONS: This study supports the broad implementation of tobacco quitline e-referrals in health care. To the best of our knowledge, no other paper has described the implementation of e-referrals across multiple U.S. health systems or how they were sustained over time. Modifying electronic health records systems and clinical workflows to enable and encourage e-referrals, if implemented and maintained appropriately, can be expected to improve patient care, make it easier for clinicians to support patients in quitting, increase the proportion of patients using evidence-based treatment, provide data to assess progress on quality goals, and help meet reporting requirements for tobacco screening and prevention.

Indexed as

Smoking CessationDelivery of Health CareHealth BehaviorHotlinesHumansReferral and Consultation

Identifiers

PMID36977494
PMCPMC10202632

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.