Background
Tobacco cessation after cancer diagnosis is critically important, given that smoking is a negative prognostic factor for cancer outcomes and an effect modifier for cancer treatment.1–13 Patients with cancer who abstain from smoking have better response to cancer treatments, higher survival rates, and reduced risk of secondary cancers compared with patients who continue to smoke.4–13 Smoking abstinence also decreases the number, severity, and frequency of adverse effects experienced as a result of cancer treatment.12–15 Given its impact on cancer outcomes, smoking cessation is now recognized as the fourth pillar of cancer care alongside surgery, radiotherapy, and chemotherapy.9
Multiple effective cessation treatments currently exist,16–18 but barriers to access lead to treatment underutilization.10,11,19–21 Cancer care programs rarely offer or provide treatments; thus, many patients with cancer receive no aid in their attempts at quitting.10,11,19–21 Improving patient outcomes requires the development and implementation of effective strategies to deploy cessation treatment within cancer care and healthcare more broadly. Across a range of healthcare domains, well-designed implementation strategies and system-level interventions have improved the reach of smoking cessation treatments.22–26
Electronic health record (EHR)–based practice improvement strategies have demonstrated utility in multiple populations and settings, including cancer care.27–35 Electronic alerts and decision support tools increase use of screening and referral, providing broader reach of effective interventions to patients.23,26,32,36–41 Assessment of tobacco use and cessation counseling referrals increased following implementation of EHR-enabled cessation tools; however, studies have not adequately examined the impact of these EHR-based strategies on the reach of a broader range of smoking cessation treatments, nor their effectiveness on cessation outcomes,31,33–35 marking an important scientific gap. Moreover, when EHR resources are primarily used to drive referrals to external resources, a high percentage of such referrals never result in treatment engagement.27,41,42 The current study addresses these gaps by examining an implementation strategy, a low-burden point-of-care tobacco treatment program (ELEVATE) to increase the reach of evidence-based cessation treatment and effectiveness on cessation outcomes.
Methods
Design and Setting
This research was conducted as part of the NCI Cancer Moonshot program through the Cancer Center Cessation Initiative (C3I).30,43 This study used a quasi-experimental design with pre/post comparisons as part of a quality improvement project to test the effect of ELEVATE on tobacco treatment and cessation outcomes among current smokers who visited outpatient oncology clinics within a large midwestern healthcare system.30
In prior research, we documented that clinicians did not refer patients who smoke to an in-house specialist, which motivated the development and implementation of the current point-of-care treatment program.30 As depicted in Figure 1, ELEVATE uses several strategies to address previously identified barriers.30 Importantly, the workflow facilitates coordination among multiple team members to deliver the following components of comprehensive smoking cessation treatment.
Barriers and strategies in implementing a low-burden point-of-care treatment program.
Citation: Journal of the National Comprehensive Cancer Network 20, 5; 10.6004/jnccn.2021.7333
Patients in ELEVATE clinics were roomed by the medical assistant, who used the EHR smoking module to (1) assess smoking status, (2) provide brief, scripted cessation advice to smokers, and (3) offer and refer patients to cessation counseling options (ie, phone-based quitline, text-based SmokefreeTXT, or app-based QuitStart), and then were seen by a physician, who was prompted by a best practice alert to use the EHR smoking module to efficiently prescribe cessation medications and encourage cessation. In usual care clinics, the EHR smoking module was unavailable; therefore, medical assistants used the EHR default function to document cessation care, and physicians followed standard prescribing procedures.
We used a pragmatic design, capitalizing on an EHR transition from Allscripts TouchWorks to Epic in medical oncology, internal medicine, and surgical oncology specialties in June 2018. At that time, the ELEVATE point-of-care smoking module, a workflow integrated within Epic designed to navigate the “5 As” (ask, advise, assess, assist, and arrange) of smoking cessation treatment, was implemented in medical oncology (a detailed description of ELEVATE components was presented in a recent publication).30 Therefore, we compared outcomes during preimplementation (January through May 2018) versus postimplementation (June through December 2018) periods in medical oncology. Internal medicine and surgical oncology did not implement ELEVATE, thereby serving as a contemporary comparison.
The Institutional Review Board at Washington University determined this project to be an evaluation of an institutional quality improvement, and therefore no Institutional Review Board approval or informed consent was required.
Population
Our population for analysis included adult tobacco smokers (aged ≥18 years) with completed outpatient clinical evaluation and management encounters in the ELEVATE setting (medical oncology) and usual care setting (internal medicine and surgical oncology) from January 2018 through June 2019.
In ELEVATE clinics, the preimplementation period included 17,642 unique patients who received care across 43,145 encounters, and the postimplementation period included 20,482 unique patients who received care across 54,972 encounters.
Assessments
Identifying Smokers
We analyzed smoking cessation treatment and treatment effectiveness outcomes among patients who were documented as tobacco smokers or actively receiving cessation treatment during any visit in the respective periods.30,44
Outcomes
We evaluated 2 primary outcomes: reach and effectiveness. Reach was defined by proportion of current smokers exposed to any of the components of evidence-based treatment (brief advice, referral to counseling, or medication) as determined by documented point-of-care delivery of the brief cessation advice script, referral to quitline, SmokefreeTXT, or QuitStart apps, and prescription of smoking cessation medication. Although not included in the formal treatment reach analyses, we separately report the proportion of current smokers who were offered counseling, as a secondary reach outcome. Effectiveness was defined as the proportion of current smokers who quit smoking, assessed by self-reported (not biochemically confirmed) smoking status at the last follow-up outpatient encounter within the 6-month period after the preimplementation and postimplementation periods.
Statistical Analysis
Our analysis involved the primary comparison of pre-ELEVATE versus post-ELEVATE in medical oncology. Our analysis also involved 2 secondary comparisons: parallel comparisons of the preimplementation and postimplementation periods in the usual care settings of (1) internal medicine, in order to establish a contemporary comparison with other medicine clinics, and (2) surgical oncology, in order to establish a contemporary comparison with other oncology clinics.
We modeled the 2 primary outcomes of reach and effectiveness using chi-square tests and the generalized estimating equation (GEE) Poisson regression methodology, adjusting for age, sex, race, and repeated patients within departments. This approach was used because some patients received care in medical oncology (ELEVATE) clinics during both preimplementation and postimplementation periods, and some patients received care in both medical oncology (ELEVATE) and internal medicine and surgical oncology (usual care) clinics. We also modeled secondary outcomes of smoking status assessment as well as the association between treatment receipt and smoking cessation.
Of note, all smokers with missing data on follow-up smoking status in the subsequent 6 months were coded as continued smoking (failed smoking cessation).
All analyses were conducted using R version 3.5.3 (R Foundation for Statistical Computing) and SAS 9.3 and 9.4M6 (SAS Institute Inc).
Results
Demographics
Population demographics for smokers (n=3,238) across ELEVATE clinics at the preimplementation period (January through May 2018) and postimplementation period (June through December 2018) are presented in Table 1.
Sample Demographics of Smokers in Medical Oncology
Smoking Status Assessment
In ELEVATE clinics, the proportions of assessment increased from 44.3% in the preimplementation period to 92.4% in the postimplementation period (chi square, 10,459; df=1; P<.001). In this medical oncology setting, 3,238 patients (pre: n=808; post: n=2,430) were identified as smokers, and 23,490 (pre: n=7,002; post: n=16,488) were identified as nonsmokers.
In usual care clinics, the proportions of assessment increased from 81.4% in the preimplementation period to 85.6% in the postimplementation period (chi square, 360.19; df=1; P<.001). In the internal medicine setting, 9,719 patients (pre: n=3,827; post: n=5,892) were identified as smokers, and 84,720 (pre: n=35,641; post: n=49,079) were identified as nonsmokers. In the surgical oncology setting, 694 patients (pre: n=119; post: n=575) were identified as smokers, and 5,866 (pre: n=740; post: n=5,126) were identified as nonsmokers.
Clinic Smoking Prevalence
During the preimplementation period, smoking prevalence could not be accurately determined due to low levels of assessment (44.3% and 81.4% in ELEVATE and usual care clinics, respectively). During the postimplementation period, because assessment levels were higher (>85%), smoking prevalence was estimated to be 12.8% in ELEVATE clinics and 10.7% in usual care clinics.
Reach
Pre-/Post-ELEVATE Comparison: Increase in Reach of Smoking Cessation Treatment
In GEE Poisson analyses, we observed an increase in smoking cessation treatment reach among smokers from the pre-ELEVATE to the post-ELEVATE period, adjusting for patient demographics and repeated patients within departments (1.6%–27.9%; difference, 26.3%; relative risk [RR], 16.9 [95% CI, 9.8–29.2]; P<.001) (Figure 2, Table 2). During the post-ELEVATE period, smokers were most likely to receive the treatment components of counseling offered (27.1%), followed by brief advice (20.5%; supplemental eTable 1, available with this article at JNCCN.org).
Increase in reach and effectiveness in medical oncology (pre-ELEVATE vs post-ELEVATE). This figure includes the proportions and 95% confidence intervals of assessed smokers who received treatment (reach, % treated) and assessed smokers who successfully quit smoking (effectiveness, % quit) during the pre‐ELEVATE (n=808) and post‐ELEVATE (n=2,430) periods in the medical oncology setting.
Citation: Journal of the National Comprehensive Cancer Network 20, 5; 10.6004/jnccn.2021.7333
Reach: Pre-ELEVATE Versus Post-ELEVATE Comparison in Medical Oncology
Effectiveness
Pre-/Post-ELEVATE Comparison: Increase in Effectiveness on Cessation
In GEE Poisson analyses, we observed an increase in smoking cessation among smokers from the pre-ELEVATE to the post-ELEVATE period, adjusting for patient demographics and repeated patients within departments (12.0% vs 17.2%; difference, 5.2%; RR, 1.3 [95% CI, 1.1–1.5]; P=.002) (Figure 2, Table 3). Compared with pre-ELEVATE, a significantly higher proportion of medical oncology patients who had been documented as smokers at some point during the post-ELEVATE period had documented cessation by the end of the subsequent 6-month follow-up period.
Effectiveness: Pre-ELEVATE versus Post-ELEVATE Comparison in Medical Oncology
Treatment is Associated With Increased Smoking Cessation
Importantly, smoking cessation at follow-up visits was higher among treated versus untreated smokers in both pre-ELEVATE (30.8% vs 11.7%; difference, 19.1%; RR, 2.52 [95% CI, 1.1–6.0]; P=.035) and post-ELEVATE periods (35.6% vs 10.1%; difference, 25.5%; RR, 3.47 [95% CI, 2.9–4.1]; P<.001) (Table 4). During the post-ELEVATE period, smoking cessation was highest among patients receiving brief advice (36.3%), followed by those receiving medication (34.9%), referred to counseling (14.1%), and offered counseling (12.8%) (supplemental eTable 1).
Effectiveness Stratified by Receipt of Treatment in Medical Oncology
Usual Care Contemporary Comparisons
Internal Medicine
Demographics
To establish a contemporary comparison within other medicine services in which ELEVATE was not implemented, we reported reach and effectiveness of smoking cessation treatment in internal medicine clinics. Population demographics for smokers (n=9,719) across internal medicine clinics in the preimplementation (January through May 2018) and postimplementation (June through December 2018) periods are presented in supplemental eTable 2.
Reach
In GEE Poisson analyses, we observed an increase in smoking cessation treatment reach among smokers in internal medicine from the preimplementation to the postimplementation period, adjusting for patient demographics and repeated patients within departments (2.8%–12.0%; difference, 9.2%; RR, 4.2 [95% CI, 3.4–5.1]; P<.001) (supplemental eTable 3). Of note, however, the relative increase in reach was 4 times greater with ELEVATE (in medical oncology) compared with this usual care setting (internal medicine; supplemental eFigure 1).
Effectiveness
In GEE Poisson analyses, we did not observe a change in smoking cessation among smokers in internal medicine from the preimplementation to the postimplementation period, adjusting for patient demographics and repeated patients within departments (9.2% vs 8.2%; difference, 1.0%; RR, 0.9 [95% CI, 0.84–1.06]; P=.296) (supplemental eTable 4). Compared with the preimplementation period, there was no difference in the proportion of internal medicine patients who had been documented as smokers at some point during the postimplementation period and had documented cessation by the end of the subsequent 6-month follow-up period. Importantly, this is in contrast to the significant increase in effectiveness found with ELEVATE (in medical oncology; supplemental eFigure 2).
Surgical Oncology
Demographics
To establish a contemporary comparison within other oncology services in which ELEVATE was not implemented, we reported reach and effectiveness of smoking cessation treatment in surgical oncology clinics. Population demographics for smokers (n=694) across surgical oncology clinics in the preimplementation and postimplementation periods are presented in supplemental eTable 5.
Reach
In frequency analyses, we observed that smoking cessation treatment reach in surgical oncology was 0.0% during the preimplementation period and 11.8% in the postimplementation period (chi square, 14.292; df=1; P<.001) (supplemental eFigure 1).
Effectiveness
In GEE Poisson analyses, we did not observe a change in smoking cessation among smokers in surgical oncology from the preimplementation to the postimplementation period, adjusting for patient demographics and repeated patients within departments (10.9% vs 9.9%; difference, 1.0%; RR, 0.86 [95% CI, 0.48–1.5]; P=.593) (supplemental eTable 6). This is in contrast to the significant increase in effectiveness found with ELEVATE (in medical oncology; supplemental eFigure 2).
Discussion
This study presents evidence that ELEVATE, a low-burden point-of-care tobacco treatment program, increased reach and effectiveness of evidence-based cessation treatment as part of cancer care among current smokers in outpatient medical oncology settings. In this pragmatic study, we observed that ELEVATE was associated with increased assessment of smoking, treatment receipt, and smoking cessation using a pre/post comparison, approximately 6 months before and after implementation of ELEVATE. In contemporary comparisons with other medicine (internal medicine) and oncology (surgical oncology) services in which ELEVATE was not implemented, we again observed improved outcomes in ELEVATE clinics compared with usual-care medicine and oncology settings.
This EHR-facilitated, point-of-care cessation program increases reach in several ways. First, it eliminates the time-related barriers of scheduling, traveling, and attending separate in-person appointments, and the financial barriers of transportation costs. Reducing barriers to treatment access is especially important for patients with cancer who typically have many appointments.45,46 Programs such as 1-800-Quit Now and SmokefreeTXT reach out to patients after provider referral, and patients are not burdened with making another appointment. In addition, EHR guidance and features help systematize the offer and referral to treatment, as shown in previous research.27,41,42 Once developed in an EHR system, this program is scalable across healthcare clinics that use similar workflows.
Importantly, we confirmed the value of evidence-based smoking cessation treatment among patients with cancer. Compared with untreated smokers, treated smokers were 3 times more likely to achieve cessation, highlighting the importance of maximizing treatment reach to current smokers in cancer care. Furthermore, our findings support prior research that even low-intensity intervention components including brief advice are effective, although the achievement of cessation was greater with brief advice than what might be expected from prior research and may reflect some degree of real-world selection bias.47,48 However, due to limited sample sizes, we did not conduct significance testing to show higher effectiveness for brief advice than medication; therefore, we recommend caution in interpreting this finding. Nevertheless, these results highlight the potential for medical assistants and nurses to provide these critical interventions to promote smoking cessation in patients with cancer. Medical assistants, prompted by an EHR script, provided brief advice to smokers, and this brief advice was effective in promoting successful smoking cessation.
The current findings are important given the underutilization of tobacco treatment overall among patients with cancer, which is the driving force behind the Cancer Moonshot C3I initiative.9,10 There are few randomized controlled trials of smoking interventions in patients with cancer, and most pragmatic trials involve relatively intense intervention.11,49 The current pragmatic trial shows that receiving even one of several tobacco treatments, not requiring specialized in-house dedicated cessation personnel or counselors, produced significant increases in smoking cessation. However, although this study shows increases in reach and smoking cessation compared with usual care, more work is clearly needed to address tobacco treatment reach and effectiveness in this context.
There are limitations in this study. First, smoking abstinence was self-reported by patients and not biochemically verified. During pre- and post-ELEVATE periods, follow-up assessments were conducted in 65% to 68% of ELEVATE patients. Taking a conservative approach, we coded all those with missing follow-up smoking status as active smoking, which may have underestimated actual cessation levels. Therefore, we conducted sensitivity analyses to maximize identification of smoking status. For ELEVATE, we compared the current assumption of 0% quit among patients missing (17.2%) with an assumed 5% quit among those missing (18.8%) and an assumed 10% quit among those missing (20.5%). These sensitivity analyses suggest that our smoking cessation estimates are robust across these assumptions.
Second, because of the nature and design of this quality improvement project, it was not practical to randomize clinics into intervention and usual care groups. We acknowledge that ELEVATE comprised medical oncology and usual care comprised internal medicine and surgical oncology. Compared with ELEVATE, the usual care population included a greater proportion of females and younger adults, which could limit the added value of the contemporary comparisons. Importantly though, levels of treatment receipt and cessation were similar between groups during the preimplementation periods. In addition, due to a relatively low proportion of patients assessed for smoking in medical oncology, there was greater opportunity for improvement in assessment among ELEVATE clinics compared with usual care clinics. Of note, however, the postimplementation assessment in ELEVATE clinics (92.4%) surpassed that of usual care clinics (85.6%), mitigating the concerns of a ceiling effect in usual care.
Third, we acknowledge that improvements in treatment reach could have been due in part to temporal and secular confounders such as the EHR platform transition or treatment practice changes over time. We added contemporary comparisons within other medicine and oncology settings to offset these confounders. By using both pre/post and contemporary comparisons, we mitigate potential concerns inherent in each analysis. Nevertheless, as with quasi-experimental studies, caution must be taken in making causal inferences.
This point-of-care approach enables smoking cessation care for patients who regularly visit outpatient cancer clinics. For patients who rarely receive in-person oncology or broader healthcare, future studies may consider a care manager for outreach to extend the benefits of the ELEVATE program. Studies on the optimization, scalability, and sustainability of ELEVATE are also needed. Finally, it will be important to conduct long-term follow-up of patients with cancer who quit smoking to better understand the long-range positive impact of cessation on responses to cancer treatment, reduced adverse effects of treatment, reduced risk of secondary cancer, and increased survival.
Conclusions
ELEVATE, a low-burden point-of-care intervention, was associated with increased reach and effectiveness of smoking cessation treatment. Overall levels of smoking cessation were higher among patients in clinics with ELEVATE and were especially high among patients who also received cessation treatment. By demonstrating an effective, low-burden approach using extant cancer care personnel, we are optimistic that these findings will help oncology programs remediate historically poor records of tobacco intervention and improve implementation of the fourth pillar of cancer care.
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