Assessing Electronic Nicotine Delivery Systems Use at NCI-Designated Cancer Centers in the Cancer Moonshot-funded Cancer Center Cessation Initiative

Cannabis, Tobacco Use, and COVID-19 Outcomes

Importance

It is unclear whether cannabis use is associated with adverse health outcomes in patients with COVID-19 when accounting for known risk factors, including tobacco use.

Objective

To examine whether cannabis and tobacco use are associated with adverse health outcomes from COVID-19 in the context of other known risk factors.

Design, Setting, and Participants

This retrospective cohort study used electronic health record data from February 1, 2020, to January 31, 2022. This study included patients who were identified as having COVID-19 during at least 1 medical visit at a large academic medical center in the Midwest US.

Exposures

Current cannabis use and tobacco smoking, as documented in the medical encounter.

Main Outcomes and Measures

Health outcomes of hospitalization, intensive care unit (ICU) admission, and all-cause mortality following COVID-19 infection. The association between substance use (cannabis and tobacco) and these COVID-19 outcomes was assessed using multivariable modeling.

Results

A total of 72 501 patients with COVID-19 were included (mean [SD] age, 48.9 [19.3] years; 43 315 [59.7%] female; 9710 [13.4%] had current smoking; 17 654 [24.4%] had former smoking; and 7060 [9.7%] had current use of cannabis). Current tobacco smoking was significantly associated with increased risk of hospitalization (odds ratio [OR], 1.72; 95% CI, 1.62-1.82; P < .001), ICU admission (OR, 1.22; 95% CI, 1.10-1.34; P < .001), and all-cause mortality (OR, 1.37, 95% CI, 1.20-1.57; P < .001) after adjusting for other factors. Cannabis use was significantly associated with increased risk of hospitalization (OR, 1.80; 95% CI, 1.68-1.93; P < .001) and ICU admission (OR, 1.27; 95% CI, 1.14-1.41; P < .001) but not with all-cause mortality (OR, 0.97; 95% CI, 0.82-1.14, P = .69) after adjusting for tobacco smoking, vaccination, comorbidity, diagnosis date, and demographic factors.

Conclusions and Relevance

The findings of this cohort study suggest that cannabis use may be an independent risk factor for COVID-19-related complications, even after considering cigarette smoking, vaccination status, comorbidities, and other risk factors.

How is nicotine vaping product (e-cigarette) use monitored in primary care electronic health records in the United Kingdom? An exploratory analysis of Clinical Practice Research Datalink (CPRD)

BACKGROUND

Electronic health records (EHRs) could identify long-term health effects of nicotine vaping. We characterised the extent to which vaping is recorded in primary care EHRs in the UK, on a population level.

METHODS

We performed descriptive analysis of Clinical Practice Research Datalink (CPRD), primary care electronic health records of 25% of the UK population (~ 16 million patients). Patients aged ≥ 18 years whose vaping status was recorded using medical codes between 2006 and 2022 were identified. We reported the frequency of vaping codes; their distribution by patient age, gender, and ethnicity; trends in vaping recording over time (including interrupted time series analyses); and transitions in patient smoking status.

RESULTS

Seven medical codes indicated current or former vaping, from 150,114 patients. When their vaping status was first recorded, mean patient age was 50.2 years (standard deviation: 15.0), 52.4% were female, and 82.1% were White. Of those recorded as currently vaping, almost all (98.9%) had records of their prior smoking status: 55.0% had been smoking, 38.3% had stopped smoking, 5.6% had never smoked. Of those who were smoking prior to being recorded as vaping, more than a year after the vaping record, over a third (34.2%) were still smoking, under a quarter (23.7%) quit smoking, 1.7% received a 'never smoked' status, and there was no smoking status for 40.4%. The 'e-cigarette or vaping product use-associated lung injury' (EVALI) outbreak was significantly associated with a declining trend in new records of current vaping between September 2019 and March 2020; and an immediate significant increase in new records of former vaping, followed by a declining trend.

CONCLUSIONS

Few patients are being asked about vaping. Most who vape had smoked, and many quit smoking after starting vaping. To enable electronic health records to provide stronger evidence on health effects, we recommend improved completeness, accuracy and consistency.

Monitoring the Implementation of Tobacco Cessation Support Tools: Using Novel Electronic Health Record Activity Metrics

BACKGROUND

Clinical decision support (CDS) tools in electronic health records (EHRs) are often used as core strategies to support quality improvement programs in the clinical setting. Monitoring the impact (intended and unintended) of these tools is crucial for program evaluation and adaptation. Existing approaches for monitoring typically rely on health care providers' self-reports or direct observation of clinical workflows, which require substantial data collection efforts and are prone to reporting bias.

OBJECTIVE

This study aims to develop a novel monitoring method leveraging EHR activity data and demonstrate its use in monitoring the CDS tools implemented by a tobacco cessation program sponsored by the National Cancer Institute's Cancer Center Cessation Initiative (C3I).

METHODS

We developed EHR-based metrics to monitor the implementation of two CDS tools: (1) a screening alert reminding clinic staff to complete the smoking assessment and (2) a support alert prompting health care providers to discuss support and treatment options, including referral to a cessation clinic. Using EHR activity data, we measured the completion (encounter-level alert completion rate) and burden (the number of times an alert was fired before completion and time spent handling the alert) of the CDS tools. We report metrics tracked for 12 months post implementation, comparing 7 cancer clinics (2 clinics implemented the screening alert and 5 implemented both alerts) within a C3I center, and identify areas to improve alert design and adoption.

RESULTS

The screening alert fired in 5121 encounters during the 12 months post implementation. The encounter-level alert completion rate (clinic staff acknowledged completion of screening in EHR: 0.55; clinic staff completed EHR documentation of screening results: 0.32) remained stable over time but varied considerably across clinics. The support alert fired in 1074 encounters during the 12 months. Providers acted upon (ie, not postponed) the support alert in 87.3% (n=938) of encounters, identified a patient ready to quit in 12% (n=129) of encounters, and ordered a referral to the cessation clinic in 2% (n=22) of encounters. With respect to alert burden, on average, both alerts fired over 2 times (screening alert: 2.7; support alert: 2.1) before completion; time spent postponing the screening alert was similar to completing (52 vs 53 seconds) the alert, and time spent postponing the support alert was more than completing (67 vs 50 seconds) the alert per encounter. These findings inform four areas where the alert design and use can be improved: (1) improving alert adoption and completion through local adaptation, (2) improving support alert efficacy by additional strategies including training in provider-patient communication, (3) improving the accuracy of tracking for alert completion, and (4) balancing alert efficacy with the burden.

CONCLUSIONS

EHR activity metrics were able to monitor the success and burden of tobacco cessation alerts, allowing for a more nuanced understanding of potential trade-offs associated with alert implementation. These metrics can be used to guide implementation adaptation and are scalable across diverse settings.

Cardiotoxicity of Electronic Cigarettes and Heat-Not-Burn Tobacco Products-A Problem for the Modern Pediatric Cardiologist

Electronic nicotine delivery systems (ENDS) have become increasingly popular among adolescents, either as an alternative to conventional cigarettes (CCs) or as a newly acquired recreational habit. Although considered by most users as a safer option for nicotine intake, these devices pose significant health risks, resulting in multisystem damage. Heat-not-burn products, which, unlike ENDS, contain tobacco, are also alternatives to CCs that consumers use based on the idea that their safety profile is superior to that of cigarettes. Recent studies in the USA and EU show that adolescents are particularly prone to using these devices. Pediatric cardiologists, as well as other healthcare professionals, should be aware of the complications that may arise from acute and chronic consumption of these substances, considering the cardiovascular damage they elicit. This article summarized the known data about the impact of ENDS on the cardiovascular system, with emphasis on the pathophysiological and molecular changes that herald the onset of systemic lesions alongside the clinical cardiovascular manifestations in this scenario.

Assessment of formal tobacco treatment and smoking cessation in dual users of cigarettes and e-cigarettes

BACKGROUND

The utility of electronic cigarettes ('e-cigarettes') as a smoking cessation adjunct remains unclear. Similarly, it is unclear if formal tobacco treatment (pharmacotherapy and/or behavioural support) augments smoking cessation in individuals who use both cigarettes and e-cigarettes.

METHODS

We performed a longitudinal cohort study of adult outpatients evaluated in our tertiary care medical centre (6/2018-6/2020). E-cigarette use, smoking status and formal tobacco treatment (deterrent pharmacotherapy and/or behavioural support) were assessed in 6-month blocks (eg, cohort 1 (C1)=6/2018-12/2018, C2=1/2019-6/2019 and so on) using our electronic health record. We assessed the relationship between e-cigarette use (either with or without formal tobacco treatment) and point prevalence of smoking cessation at 6 and 12 months.

RESULTS

111 823 unique patients were included in the study. The prevalence of dual use of cigarettes and e-cigarettes increased significantly over the study period (C1=0.8%; C2=1.1%; C3=1.8%; C4=2.3%; p<0.001). The prevalence of smoking cessation at 12 months was higher among e-cigarette users (20.8%) compared with non-users (16.8%) (risk difference, 4.0% (95% CI 2.5% to 5.5%); adjusted relative risk (aRR) 1.354, 95% CI 1.252 to 1.464, p<0.0001). Further, among dual users of cigarettes and e-cigarettes, the prevalence of smoking cessation at 12 months was higher among individuals who received tobacco treatment (29.1%) compared with individuals who did not receive tobacco treatment (19.6%) (risk difference, 9.5% (95% CI, 4.6% to 14.4%); aRR 1.238, 95% CI 1.071 to 1.432, p=0.004).

INTERPRETATION

These results suggest that dual users of cigarettes and e-cigarettes benefit from formal tobacco treatment. Clinicians should consider offering formal tobacco treatment to such patients, though future trials are needed.