Low Burden Strategies Are Needed to Reduce Smoking in Rural Healthcare Settings: A Lesson from Cancer Clinics

Abstract

Rural populations face significant smoking-related health disparities, such as a higher prevalence of lung cancer and cancer mortality, higher prevalence of smoking, and lower likelihood of receiving cessation treatment than urban counterparts. A significant proportion of health disparities in rural populations could be eliminated with low-barrier, easy-access treatment delivery methods for smoking cessation. In this study, we assessed treatment engagement among patients in rural and urban settings. Then, we examined the effect of an electronic health record-based smoking cessation module on patient receipt of evidence-based cessation care. As part of a quality improvement project, we retrospectively observed 479,798 unique patients accounting for 1,426,089 outpatient clinical encounters from June 2018–March 2019 across 766 clinics in the greater St. Louis, southern Illinois, and mid-Missouri regions. Smoking prevalence was higher in rural versus urban clinics (20.7% vs. 13.9%, 6.7% [6.3, 7.1], odds ratio = 1.6 [1.6, 1.6], p < 0.0001), and yet rural smokers were nearly three times less likely than their urban counterparts to receive any smoking cessation treatment after adjusting for patients clustering within clinics (9.6% vs. 25.8%, −16.2% [−16.9, −15.5], odds ratio = 0.304 [0.28, 0.33], p < 0.0001). Although not yet scaled up in the rural setting, we examined the effects of a low-burden, point-of-care smoking module currently implemented in cancer clinics. After adjusting for patient clustering within clinics, patients were more likely to receive smoking treatment in clinics that implemented the module versus clinics that did not implement the module (31.2% vs. 17.5%, 13.7% [10.8, 16.6], odds ratio = 2.1 [1.8, 2.6], p < 0.0001). The point-of-care treatment approach offers a promising solution for rural settings, both in and outside the context of cancer care.

A cascade of care for alcohol use disorder: Using 2015–2019 National Survey on Drug Use and Health data to identify gaps in past 12‐month care

“…We therefore advocate for increased engagement of this high‐risk population by implementing evidence‐based treatment in the primary care setting. Primary care can be an effective setting for team‐based AUD treatment at the point of care, facilitated by electronic health records, and this approach has constituted a highly promising model for smoking cessation and opioid use disorder treatment (Gunderson & Fiellin, 2008; Krantz & Mehler, 2004; National Institute on Drug Abuse, 2018; Ramsey et al, 2020; Ramsey et al, 2019a). This model may involve a team approach, with medical assistants or nurses conducting alcohol use assessment on every patient who presents for care facilitated by a prompt from the electronic health record, and providing brief advice about at‐risk alcohol use to those with problematic drinking, and nurses queuing an AUD medication order for the physician to prescribe.…”

A Cascade of Care for Alcohol Use Disorder: Using 2015-2018 National Survey on Drug Use and Health Data to Identify Gaps in Care

“…We therefore advocate for increased engagement of this high-risk population by implementing evidence-based treatment in the primary care setting. Primary care can be an effective setting for team-based AUD treatment at the-point-of-care, facilitated by electronic health records, and this approach has constituted a highly promising model for smoking cessation and opioid use disorder (Gunderson and Fiellin, 2008; Krantz and Mehler, 2004; National Institute on Drug Abuse, 2018; Ramsey et al, 2020; Ramsey et al, 2019a). This approach may involve a team of medical assistants and nurses conducting alcohol use assessment, providing brief advice about at risk alcohol use, and queuing an AUD medication order for the physician to prescribe.…”

Tobacco Use and Treatment among Cancer Survivors

“…Ramsey and colleagues [37] examined the treatment engagement of cancer patients in urban and rural settings with an EHR-based, low-burden tobacco cessation module by measuring patients' acceptance of treatment. The prevalence of smoking was higher and treatment engagement was lower in patients who received care in rural clinics.…”