Design and implementation of decision support for tobacco dependence treatment in an inpatient electronic medical record: a randomized trial

Bernstein, Steven L.; Rosner, June; DeWitt, Michelle; Tetrault, Jeanette M.; Hsiao, Allen; Dziura, James; Sussman, Scott; O’Connor, Patrick G.; Toll, Benjamín A.

doi:10.1007/s13142-017-0470-8

Cited by 36 publications

(37 citation statements)

References 10 publications

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“…[10][11][12] Most eReferral studies relied on team-based models and are focused on either inpatient or outpatient implementations rather than changes across a health care system or in specialty settings. 9,[13][14][15][16] Specialty services like oncology are important settings for promoting tobacco cessation. 17 When implementing new preventive strategies, best practice alerts (BPAs) are often recommended, 18 yet these may cause provider "alert fatigue."…”

Section: Background and Significancementioning

confidence: 99%

Health System Implementation of a Tobacco Quitline eReferral

et al. 2019

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Background Proactive referrals through electronic orders (eReferrals) can increase patient connection with tobacco quitlines. More information is needed on “real-world” implementation of electronic health record tools to promote tobacco cessation while minimizing provider burden. Objectives This paper examines the health system implementation of an eReferral to a tobacco quitline without best practice alerts in primary care, specialty, and hospital settings in an academic health system. Methods This is a prospective implementation study of a health system tobacco eReferral to a state quitline that was completed with an approach to minimize provider cognitive burden. Data are drawn from electronic health record data at University of California, Davis Health Systems (March 2013–February 2016). Results Over 3 years, 16,083 encounters with smokers resulted in 1,137 eReferral orders (7.1%). Treatment reach was 1.6% for quitline services and 2.3% for outpatient group classes. While the group classes were offered to outpatient smokers, the eReferral order was included in an outpatient order set and eventually an automated inpatient discharge order set; no provider alerts were implemented. Referrals were sustained and doubled after inpatient order set implementation. Among all first time eReferral patients, 12.2% had a 6 to 12 month follow-up visit at which they were documented as nonsmoking. Conclusion This study demonstrates a quitline eReferral order can be successfully implemented and sustained with minimal promotion, without provider alerts and in conjunction with group classes. Reach and effectiveness were similar to previously described literature.

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Section: Background and Significancementioning

confidence: 99%

Health System Implementation of a Tobacco Quitline eReferral

et al. 2019

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“…Main study results have been previously reported. 7 At 1 month, 960 (92.3%) participants were contacted by telephone; an additional 5 (0.4%) were deceased and 79 (7.6%) were lost to follow-up. Reasons for loss to follow-up were captured in a closed menu with four options: unreachable, refused to speak, incarceration, and mental health or substance abuse treatment.…”

Section: Resultsmentioning

confidence: 99%

“…We provide, as an example, a diagram from a trial recently completed by our group. 7 We found that this method yielded significant benefits in accuracy, staff use, and follow-up management.…”

Section: Objectivementioning

confidence: 86%

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Automated Generation of CONSORT Diagrams Using Relational Database Software

et al. 2019

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Background Investigators conducting prospective clinical trials must report patient flow using the Consolidated Standards of Reporting Trials (CONSORT) statement. Depending on how data are collected, this can be a laborious, time-intensive process. However, because many trials enter data electronically, CONSORT diagrams may be generated in an automated fashion. Objective Our objective was to use an off-the-shelf software to develop a technique to generate CONSORT diagrams automatically. Methods During a recent trial, data were entered into FileMaker Pro, a commercially available software, at enrollment and three waves of follow-up. Patient-level data were coded to automatically generate CONSORT diagrams for use by the study team. Results From August 2012 to July 2014, 1,044 participants were enrolled. CONSORT diagrams were generated weekly for study team meetings to track follow-ups at 1, 6, and 12 months, for 960 (92%), 921 (90%), and 871 (88%) participants who were contacted or deceased, respectively. Reasons for loss to follow-up were captured at each follow-up. Conclusion CONSORT diagrams can be generated using a standard software for any trial and can facilitate data collection, project management, and reporting.

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“…Clinical reminders and decision support systems within the EHR can also reduce clinician burden in providing TUT. These systems have been implemented in a variety of settings to improve adherence to TUT guidelines and are cost‐effective, sustainable, feasible, and acceptable . Computerized clinical reminders increase the likelihood of documentation, engagement in counseling, and medication prescriptions, and they require minimal training to implement .…”

Section: Resultsmentioning

confidence: 99%

Tobacco Use Assessment and Treatment in Cancer Patients: A Scoping Review of Oncology Care Clinician Adherence to Clinical Practice Guidelines in the U.S.

2018

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Background Smoking after a cancer diagnosis negatively impacts health outcomes; smoking cessation improves symptoms, side effects, and overall prognosis. The Public Health Service and major oncology organizations have established guidelines for tobacco use treatment among cancer patients, including clinician assessment of tobacco use at each visit. Oncology care clinicians (OCCs) play important roles in this process (noted as the 5As: Asking about tobacco use, Advising users to quit, Assessing willingness to quit, Assisting in quit attempts, and Arranging follow‐up contact). However, OCCs may not be using the “teachable moments” related to cancer diagnosis, treatment, and survivorship to provide cessation interventions. Materials and Methods In this scoping literature review of articles from 2006 to 2017, we discuss (1) frequency and quality of OCCs' tobacco use assessments with cancer patients and survivors; (2) barriers to providing tobacco treatment for cancer patients; and (3) the efficacy and future of provider‐level interventions to facilitate adherence to tobacco treatment guidelines. Results OCCs are not adequately addressing smoking cessation with their patients. The reviewed studies indicate that although >75% assess tobacco use during an intake visit and >60% typically advise patients to quit, a substantially lower percentage recommend or arrange smoking cessation treatment or follow‐up after a quit attempt. Less than 30% of OCCs report adequate training in cessation interventions. Conclusion Intervention trials focused on provider‐ and system‐level change are needed to promote integration of evidence‐based tobacco treatment into the oncology setting. Attention should be given to the barriers faced by OCCs when targeting interventions for the oncologic context. Implications for Practice This article reviews the existing literature on the gap between best and current practices for tobacco use assessment and treatment in the oncologic context. It also identifies clinician‐ and system‐level barriers that should be addressed in order to lessen this gap and provides suggestions that could be applied across different oncology practice settings to connect patients with tobacco use treatments that may improve overall survival and quality of life.

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Design and implementation of decision support for tobacco dependence treatment in an inpatient electronic medical record: a randomized trial

Abstract: www.ClinicalTrials.gov (NCT01691105).

Cited by 36 publications

References 10 publications

Health System Implementation of a Tobacco Quitline eReferral

Health System Implementation of a Tobacco Quitline eReferral

Automated Generation of CONSORT Diagrams Using Relational Database Software

Tobacco Use Assessment and Treatment in Cancer Patients: A Scoping Review of Oncology Care Clinician Adherence to Clinical Practice Guidelines in the U.S.

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