Implementation of a Novel Electronic Patient-Directed Smoking Cessation Platform for Cancer Patients: Interrupted Time Series Analysis

Systematic Review of Smoking Cessation Interventions for Smokers Diagnosed with Cancer

The detrimental impact of smoking on health and wellbeing are irrefutable. Additionally, smoking is associated with the development of cancer, a reduction treatment outcomes and poorer health outcomes. Nevertheless, a significant number of people continue to smoke following a cancer diagnosis. Little is understood of the smoking cessation services provided to smokers with cancer or their engagement with them. This systematic review aimed to identify existing smoking cessation interventions for this cohort diagnosed with breast, head and neck, lung and cervical cancers (linked to risk). Systematic searches of Pubmed, Embase, Psych Info and CINAHL from 1 January 2015 to 15 December 2020 were conducted. Included studies examined the characteristics of smoking cessation interventions and impact on referrals and quit attempts. The impact on healthcare professionals was included if reported. Included studies were restricted to adults with a cancer diagnosis and published in English. No restriction was placed on study designs, and narrative data synthesis was conducted due to heterogeneity. A review protocol was registered on PROSPERO CRD 42020214204, and reporting adheres to PRISMA reporting guidelines. Data were screened, extracted in duplicate and an assessment of the quality of evidence undertaken using Mixed Methods Assessment Tool. 23 studies met the inclusion criteria, representing USA, Canada, England, Lebanon, Australia and including randomized controlled trials (9), observational studies (10), quality improvement (3), and one qualitative study. Hospital and cancer clinics [including a dental clinic] were the settings for all studies. 43% (10/23) of studies reported interventions for smokers diagnosed with head and neck cancer, 13% (3/23) for smokers diagnosed with lung cancer, one study provides evidence for breast cancer, and the remaining nine studies (39%) report on multiple cancers including the ones specified in this review. Methodological quality was variable. There were limited data to identify one optimal intervention for this cohort. Key elements included the timing and frequency of quit conversations, use of electronic records, pharmacotherapy including extended use of varenicline, increased counselling sessions and a service embedded in oncology departments. More studies are required to ensure tailored smoking cessation pathways are co-developed for smokers with a diagnosis of cancer to support this population.

Methods of Capturing Process Outcomes in Quality Improvement Trials: A Systematic Review

ABSTRACT

Healthcare quality can be measured by studying structure, processes, and outcomes. This study examines how trialists capture process outcomes in implementation trials to provide guidance for researchers and health professionals. Electronic databases were searched, and two researchers performed the title, abstract, and full-text selection. Only implementation studies involving nonpharmacological approaches were included. Data were extracted by one reviewer and checked for accuracy and completeness by a second reviewer. Study quality was independently assessed by two reviewers. Of the 3,186 articles screened, 24 studies matched our inclusion criteria. Most studies were cluster randomized control trials, followed by interrupted time series studies and stepped wedge studies. The population in the studies was diverse and settings included hospitals, community centers, residential aged care facilities, and primary care. The reporting of process measures across the included studies varied, and there was limited information about the mechanisms of data collection procedures. Nineteen studies extracted information about processes from electronic medical records, patient records, or chart reviews. The remaining five studies used staff surveys. Challenges remain in the practical aspect of data collection for measuring process outcomes, particularly outside of hospital settings or where processes are hard to capture in patient records.

Pivoting the Provision of Smoking Cessation Education in a Virtual Clinical World: The Princess Margaret Cancer Centre Experience

Continued smoking after a cancer diagnosis may be attributed to misbeliefs by both patients and healthcare providers on the value and benefit of quitting smoking on treatment outcomes. The perceived myths and misconceptions about the relationship between smoking and cancer may be readily dispelled with the provision of practical and pertinent education. However, busy clinics as well as the rapid move to virtual care due to the COVID-19 pandemic present several challenges with the provision of smoking cessation education. Here, we describe how the Princess Margaret Cancer Centre implemented innovative solutions to improve the delivery of education during the COVID-19 pandemic to better support patients and healthcare providers.

Measuring Public Reaction to Violence Against Doctors in China: Interrupted Time Series Analysis of Media Reports

Background

Violence against doctors in China is a serious problem that has attracted attention from both domestic and international media.

Objective

This study investigates readers’ responses to media reports on violence against doctors to identify attitudes toward perpetrators and physicians and examine if such trends are influenced by national policies.

Methods

We searched 17 Chinese violence against doctors reports in international media sources from 2011 to 2020. We then tracked back the original reports and web crawled the 19,220 comments in China. To ascertain the possible turning point of public opinion, we searched violence against doctors–related policies from Tsinghua University ipolicy database from 2011 to 2020, and found 19 policies enacted by the Chinese central government aimed at alleviating the intense patient–physician relationship. We then conducted a series of interrupted time series analyses to examine the influence of these policies on public sentiment toward violence against doctors over time.

Results

The interrupted time series analysis (ITSA) showed that the change in public sentiment toward violence against doctors reports was temporally associated with government interventions. The declarations of 10 of the public policies were followed by increases in the proportion of online public opinion in support of doctors (average slope changes of 0.010, P<.05). A decline in the proportion of online public opinion that blamed doctors (average level change of –0.784, P<.05) followed the declaration of 3 policies.

Conclusions

The government’s administrative interventions effectively shaped public opinion but only temporarily. Continued public policy interventions are needed to sustain the reduction of hostility toward medical doctors.

Strategies for Referring Cancer Patients in a Smoking Cessation Program

Most people who smoke and develop cancer are unable to quit smoking. To address this, many cancer centers have now opened smoking cessation programs specifically designed to help cancer patients to quit. An important question has now emerged—what is the most effective approach for engaging smokers within a cancer center in these smoking cessation programs? We report outcomes from a retrospective observational study comparing three referral methods—traditional referral, best practice advisory (BPA), and direct outreach—on utilization of the Duke Cancer Center Smoking Cessation Program. We found that program utilization rate was higher for direct outreach (5.4%) than traditional referral (0.8%), p < 0.001, and BPA (0.2%); p < 0.001. Program utilization was 6.4% for all methods combined. Inferring a causal relationship between referral method and program utilization was not possible because the study did not use a randomized design. Innovation is needed to generate higher utilization rates for cancer center smoking cessation programs.

Design and Pilot Implementation of an Electronic Health Record-Based System to Automatically Refer Cancer Patients to Tobacco Use Treatment

Continued tobacco use after cancer diagnosis is detrimental to treatment and survivorship. The current reach of evidence-based tobacco treatments in cancer patients is low. As a part of the National Cancer Institute Cancer Center Cessation Initiative, the Mayo Clinic Cancer Center designed an electronic health record (EHR, Epic^©)-based process to automatically refer ambulatory oncology patients to tobacco use treatment, regardless of intent to cease tobacco use(“opt out”). The referral and patient scheduling, accomplished through a best practice advisory (BPA) directed to staff who room patients, does not require a co-signature from clinicians. This process was piloted for a six-week period starting in July of 2019 at the Division of Medical Oncology, Mayo Clinic, Rochester, MN. All oncology patients who were tobacco users were referred for tobacco treatment by the rooming staff (n = 210). Of these, 150 (71%) had a tobacco treatment appointment scheduled, and 25 (17%) completed their appointment. We conclude that an EHR-based “opt-out” approach to refer patients to tobacco dependence treatment that does not require active involvement by clinicians is feasible within the oncology clinical practice. Further work is needed to increase the proportion of scheduled patients who attend their appointments.

Effectiveness of an Opt-Out Electronic Heath Record-Based Tobacco Treatment Consult Service at an Urban Safety Net Hospital

BACKGROUND

To address the burden of tobacco use in underserved populations, our safety net hospital developed a tobacco treatment intervention consisting of an "opt-out" electronic health record-based best practice alert + order set, which triggers consultation to an inpatient tobacco treatment consult (TTC) service for all hospitalized smokers.

RESEARCH QUESTION

We sought to understand if the intervention would increase patient-level outcomes (receipt of tobacco treatment during hospitalization and at discharge; 6-month smoking abstinence) and improve hospital-wide performance on tobacco treatment metrics.

DESIGN AND METHODS

We conducted two retrospective quasi-experimental analyses to examine effectiveness of the TTC service. Using a pragmatic design and multivariable logistic regression, we compared patient-level outcomes of receipt of nicotine replacement therapy and 6-month quit rates between smokers seen by the service (n = 505) and eligible smokers not seen because of time constraints (n = 680) between July 2016 and December 2016. In addition, we conducted an interrupted time series analysis to examine the effect of the TTC service on hospital-level performance measures, comparing reported Joint Commission measure rates for inpatient (Tob-2) and postdischarge (Tob-3) tobacco treatment preimplementation (January 2015-June 2016) vs postimplementation (July 2016-December 2017) of the intervention.

RESULTS

Compared with inpatient smokers not seen by the TTC service, smokers seen by the TTC service had higher odds of receiving nicotine replacement during hospitalization (260 of 505 [51.5%] vs 244 of 680 [35.9%]; adjusted ORs [AOR], 1.93 [95% CI, 1.5-2.45]) and at discharge (164 of 505 [32.5%] vs 84 of 680 [12.4%]; AOR, 3.41 [95% CI, 2.54-4.61]), as well as higher odds of 6-month smoking abstinence (75 of 505 [14.9%] vs 68 of 680 [10%]; AOR, 1.48 [95% CI, 1.03-2.12]). Hospital-wide, the intervention was associated with a change in slope trends for Tob-3 (P < .01), but not for Tob-2.

INTERPRETATION

The "opt-out" electronic health record-based TTC service at our large safety net hospital was effective at improving both patient-level outcomes and hospital-level performance metrics, and could be implemented at other safety net hospitals that care for hard-to-reach smokers.

Identifying Lung Cancer Risk Factors in the Elderly Using Deep Neural Networks: Quantitative Analysis of Web-Based Survey Data

BACKGROUND

Lung cancer is one of the most dangerous malignant tumors, with the fastest-growing morbidity and mortality, especially in the elderly. With a rapid growth of the elderly population in recent years, lung cancer prevention and control are increasingly of fundamental importance, but are complicated by the fact that the pathogenesis of lung cancer is a complex process involving a variety of risk factors.

OBJECTIVE

This study aimed at identifying key risk factors of lung cancer incidence in the elderly and quantitatively analyzing these risk factors' degree of influence using a deep learning method.

METHODS

Based on Web-based survey data, we integrated multidisciplinary risk factors, including behavioral risk factors, disease history factors, environmental factors, and demographic factors, and then preprocessed these integrated data. We trained deep neural network models in a stratified elderly population. We then extracted risk factors of lung cancer in the elderly and conducted quantitative analyses of the degree of influence using the deep neural network models.

RESULTS

The proposed model quantitatively identified risk factors based on 235,673 adults. The proposed deep neural network models of 4 groups (age ≥65 years, women ≥65 years old, men ≥65 years old, and the whole population) achieved good performance in identifying lung cancer risk factors, with accuracy ranging from 0.927 (95% CI 0.223-0.525; P=.002) to 0.962 (95% CI 0.530-0.751; P=.002) and the area under curve ranging from 0.913 (95% CI 0.564-0.803) to 0.931(95% CI 0.499-0.593). Smoking frequency was the leading risk factor for lung cancer in men 65 years and older. Time since quitting and smoking at least 100 cigarettes in their lifetime were the main risk factors for lung cancer in women 65 years and older. Men 65 years and older had the highest lung cancer incidence among the stratified groups, particularly non-small cell lung cancer incidence. Lung cancer incidence decreased more obviously in men than in women with smoking rate decline.

CONCLUSIONS

This study demonstrated a quantitative method to identify risk factors of lung cancer in the elderly. The proposed models provided intervention indicators to prevent lung cancer, especially in older men. This approach might be used as a risk factor identification tool to apply in other cancers and help physicians make decisions on cancer prevention.

Exploring Tobacco Use and Smoking Cessation Best Practices From the Perspectives of Individuals With Lung Cancer and Health Care Professionals

BACKGROUND

Lung cancer patients who continue to smoke after diagnosis are at increased risk of treatment toxicity, residual/recurrent disease, future malignancies, and all-cause mortality. Guidelines including those from National Comprehensive Cancer Network and Cancer Care Ontario advocate for screening, counseling, and access to smoking cessation services for all cancer patients; however, barriers from both patient and health care professional (HCP) perspectives contribute to lack of implementation.

OBJECTIVE

The objective of this study was to identify the different perspectives among patients and HCPs in how the promotion of person-centred approaches may be used when offering smoking cessation services to patients who are receiving care within a regional cancer centre.

METHODS

Qualitative data were generated using various methods, including focus groups with HCPs and interviews with patients. In total, 16 HCPs participated in three focus groups: including nine radiation therapists, five registered nurses, one registered dietitian, and one physiotherapist. Of 55 patients accrued, 19 were interviewed. Both focus groups and interviews were audio recorded, and the recordings were transcribed verbatim. Transcripts were then analyzed using narrative thematic analysis to define and identify themes.

RESULTS

The identified themes were categorized into three topic areas: knowledge (eg, impact of smoking on illness and why they should not smoke); individual decision to quit (eg, motivators), and the social unacceptability of smoking (eg, the public perception of smoking over the last 40 years). HCP-identified themes included identification of smokers, triggers to start a conversation, approach, gaps and barriers to cessation, rationale for cessation, and judgment. Patient-identified themes included knowledge, individual decision to quit, and the social unacceptability of smoking.

CONCLUSION

Understanding patient and HCP perspectives on smoking cessation will help influence practice to ensure that patients are not judged, assumptions are not made, and individualized and person-centred care is provided. HCP awareness of these themes and the patient perspective may challenge assumptions and values.

Implementation of a comprehensive smoking cessation program in cancer care

Background

Quitting smoking after a cancer diagnosis maximizes treatment-related effects, improves prognosis, and enhances quality of life. However, smoking cessation (sc) services are not routinely integrated into cancer care. The Princess Margaret Cancer Centre implemented a digitally-based sc program in oncology, leveraging an e-referral system (cease) to screen all new ambulatory patients, provide tailored education and advice on quitting, and facilitate referrals.

Methods

We adopted the Framework for Managing eHealth Change to guide implementation of the sc program by integrating 6 key elements: governance and leadership, stakeholder engagement, communication, workflow analysis and integration, monitoring and evaluation, and training and education.

Results

Incorporating elements of the Framework, we used extensive stakeholder engagement and strategic partnerships to establish a sc program with organizational and provincial accountability. Existing electronic patient-reported assessments were changed to integrate cease. Clinic audits and staff engagement allowed for analysis of workflow, ongoing monitoring and evaluation that aided in establishing a communication strategy, and development of cancer-specific education for patients and health care providers. From April 2016 to March 2018, 22,137 new patients were eligible for screening. Among those new patients, 13,617 (62%) were screened, with 1382 (10%) being current smokers and 532 (4%) having recently quit (within 6 months). Of the current smokers and those who had recently quit, all were advised to quit or to stay smoke-free, and 380 (20%) accepted referral to a sc counselling service.

Conclusions

Here, we provide a comprehensive practice blueprint for the implementation of digitally based sc programs as a standard of care within comprehensive cancer centres with high patient volumes.

Impact of the Knowledge Translation Research Network's grants program in cancer knowledge translation

Ten years ago, the Knowledge Translation Research Network (KT-Net) grants program funded its first study in cancer knowledge translation (KT). [...]