Tobacco Tracker: A New Tool to Support College Smoke and Tobacco Free Policies.

INTRODUCTION: University community members are critical to the success of their smoke and tobacco free (STF) policies. The present study evaluates changes in social enforcement-related attitudes and behaviors following introduction of a new online Tobacco Tracker tool in two university settings. METHODS: Campus wide surveys were administered to current students, faculty, and staff at two California public universities with 100% STF policies before (November 2018; N = 5078) and after (December 2019-January 2020; N = 4853) introduction of Tobacco Tracker in February 2019. Prospective surveillance reports over 12 months from Tobacco Tracker, a GIS tool for the campus community to report tobacco use and related litter that displays crowdsourced maps of hotspots, were analyzed. Outcomes included awareness and self-reported use of a tobacco reporting tool, readiness for policy social enforcement, an Intellectual Social Affective (ISA) Engagement scale, and environmental surveillance reports from Tobacco Tracker. RESULTS: In campus surveys, awareness of a tobacco reporting tool doubled (8.0%-16.9%, p < .0001), use of an online reporting tool tripled (1.1%-3.2%, p < .0001), and readiness to enforce the policy increased (p = .0008). ISA engagement did not change (p = .72). In Tobacco Tracker campus reports (N = 1163), active tobacco use was reported more frequently than tobacco-related litter. CONCLUSIONS: Tobacco Tracker is a promising tool for college communities to support STF policy. Introduction of Tobacco Tracker was associated with an increase in campus awareness and utilization of a reporting tool, readiness to enforce policy, and campus tobacco surveillance. Future research should determine how Tobacco Tracker may improve policy compliance. IMPLICATIONS: Tobacco Tracker is a promising tool for college communities to support smoke and tobacco free (STF) policy through active surveillance of smoking, vaping, and related litter on campus. Introduction of Tobacco Tracker was associated with changes in social enforcement-related attitudes and behaviors critical to realizing the preventive potential of STF policies. A crowdsourcing-based tool for monitoring tobacco use on college campuses can address a major barrier to social enforcement: discomfort confronting tobacco users. Further, it provides an alternative to punitive enforcement approaches and promises a sustainable solution to an infrastructure issue faced by many universities lacking resources to collect data on campus tobacco use and related litter.

Cigarette Smoking and Secondhand Smoke Exposure Before and After a Tobacco-Free Olympic Policy Period: Qingdao, China.

INTRODUCTION: We explored the impact of a temporary tobacco-free public policy for the 2008 Summer Olympics on the smoking prevalence and secondhand smoke exposure among the population of a co-hosting city, Qingdao, China. METHODS: The Qingdao Diabetes Survey was analyzed for 2006 (n = 4599) and 2009 (n = 4680), which are survey years before and after the tobacco-free Olympics public policy period (July 2007 to January 2009). We analyzed the differences in self-reported smoking prevalence and exposure to secondhand smoke at home and/or workplace, and compared odds of smoking by survey year and of exposure to secondhand smoke among nonsmokers. RESULTS: From 2006 to 2009, the male smoking prevalence declined from 51.4% (95% confidence interval [CI] = 49.0% to 53.9%) to 42.6% (95% CI = 40.2% to 45.1%), and the proportion of lighter smokers decreased more. Among nonsmokers, the secondhand smoke exposure rate declined from 62.2% (95% CI = 60.5% to 63.9%) to 56.8% (95% CI = 55.1% to 58.6%). Regression analyses show 34% lower odds of men smoking after Olympics (OR = 0.66, 95% CI = 0.57% to 0.77%). Rural residents and individuals who are not retired were more likely to smoke. Female nonsmokers report 17% less exposure to secondhand smoke after Olympics (OR = 0.83, 95% CI = 0.70% to 0.98%). Urban nonsmokers were more likely to be exposed than their rural counterparts. CONCLUSIONS: Smoking prevalence among men and secondhand smoke exposure among women significantly decreased in Qingdao, China, after the tobacco-free Olympics public policy period. As only the proportion of lighter smokers decreased, this may help explain why urban nonsmokers reported increased exposure. Unintended increased secondhand smoke exposure and cessation support need to be addressed in large-scale policy campaigns. IMPLICATIONS: Hosting the Olympic Games can help to initiate large-scale tobacco-free public policies for hosting cities. Although previous studies have demonstrated reduction in nonsmoker exposure to secondhand smoke, the impact on the hosting city's smoking prevalence or exposure rates is unclear. After the Olympic Games in Qingdao, China, smoking prevalence among men significantly decreased, mostly due to light smokers. Secondhand smoke exposure at home and/or workplace significantly decreased among female nonsmokers. Urban nonsmokers had an unintended consequence of increased secondhand smoke exposure after the tobacco-free Olympic policy period. Concurrent promotion of cessation support for heavier smokers may be needed.

A Lean Six Sigma Quality Improvement Project Improves Timeliness of Discharge from the Hospital.

BACKGROUND: Hospital overcrowding has become a widespread problem, with constrained bed capacity and admission bottlenecks having far-reaching negative impacts on quality and safety. Focus on timing of discharge may be the least disruptive and most effective way to address constrained bed capacity, yet there may be significant institution-specific barriers to implementation. METHODS: With the creation of a "Value Team," a 627-bed, tertiary care academic medical center embarked on a quality improvement (QI) project using Lean Six Sigma process improvement methodology. After defining the problems around timeliness of discharge, the team went through the steps in the Define, Measure, Analyze, Improve, Control (DMAIC) framework. Interventions, which were implemented on the basis of an in-depth analysis of barriers to the discharge process, included geographic cohorts of internal medicine physicians on specific hospital units and multidisciplinary huddles one day before anticipated discharge. RESULTS: After accounting for the concurrent trends in the control group, the percentage of discharge orders released by 10:00 a.m. increased by 21.3 points (p < 0.001; adjusted odds ratio [OR] = 2.62; 95% confidence interval [CI] = 1.91-3.59), and the percentage of patients discharged by noon increased by 7.5 points (p = 0.001; adjusted OR = 1.70; 95% CI 1.15-2.51). There were no significant changes in the 30-day readmission rate or length of stay. CONCLUSION: A QI program shaped by Lean Six Sigma principles and reinforced by clinician huddles and geographic cohorting was associated with earlier posting of discharge orders and physical discharge by noon.