Primary care-based smoking cessation treatment and subsequent healthcare service utilisation: a matched cohort study of smokers using linked administrative healthcare data

Abstract

BackgroundNo research has assessed the individual-level impact of smoking cessation treatment delivered within a general primary care patient population on multiple forms of subsequent healthcare service use.ObjectiveWe aimed to compare the rate of outpatient visits, emergency department (ED) visits and hospitalisations during a 5-year follow-up period among smokers who had and had not accessed a smoking cessation treatment programme.MethodsThe study was a retrospective matched cohort study using linked demographic and administrative healthcare databases in Ontario, Canada. 9951 patients who accessed smoking cessation services between July 2011 and December 2012 were matched to a smoker who did not access services, obtained from the Canadian Community Health Survey, using a combination of hard matching and propensity score matching. Outcomes were rates of healthcare service use from index date (programme enrolment or survey response) to March 2017.ResultsAfter controlling for potential confounders, patients in the overall treatment cohort had modestly greater rates of the outcomes: outpatient visits (rate ratio (RR) 1.10, 95% CI: 1.06 to 1.14), ED visits (RR 1.08, 95% CI: 1.03 to 1.13) and hospitalisations (RR 1.09, 95% CI: 1.02 to 1.18). Effect modification of the association between smoking cessation treatment and healthcare service use by prevalent comorbidity was found for outpatient visits (p=0.006), and hospitalisations (p=0.050), but not ED visits.ConclusionsPatients who enrolled in smoking cessation treatment offered through primary care clinics in Ontario displayed a modest but significantly greater rate of outpatient visits, ED visits and hospitalisations over a 5-year follow-up period.

Cancer Risk Following Smoking Cessation in Korea

“…In sensitivity analysis, the inclusion of sick quitters almost was not possible because we included quitters (past smokers) who had already stopped smoking before baseline. This trend aligns with the well-documented phenomenon of escalated medical use and associated expenses among those who have just quit …”

Short-term effects of national smoking cessation service on smoking-related disease prevalence and healthcare costs: Experience from the National Health Insurance Service Smoking Cessation Intervention Program in Korea

“…In these perspectives, a few studies suggested a decrease in some healthcare costs in the year postsmoking cessation treatment, but these findings resulted from the limited study design and target population, such as the comparison of smokers with or without inpatient tobacco dependence treatment during the hospitalization or the comparison of varenicline versus NRT users without comparison to the non-treated group 20,21 . While some previous studies, including two recently published studies from Ontario, Canada, based on the longitudinal followup design using real-world measurement of the healthcare cost linked with administrative healthcare data, showed an increase in or relatively higher medical utilization and cost among the smoking cessation service users [22][23][24][25] . One study reported higher total healthcare costs in the treatment cohort pre-and post-treatment periods 24 , and another study identified a significantly greater rate of outpatient visits, emergency department visits and hospitalizations among patients who enrolled in smoking cessation treatment offered through primary care clinics over a 5-year follow-up period 25 .…”

Effect of a Community-Based Hepatitis B Virus Infection Detection Combined with Vaccination Program in China

“…The propensity score was calculated using the method of multivariate logistic regression, and the following covariates were included in the multivariate logistic regression model as factors affecting an individual who participated in the HBVIDV program: age, gender, education level, employment condition, economic level, self-rated socioeconomic status, living area, multimorbidity, and self-rated health condition. The missing data of categorical covariates were coded as the "Missing" category and were included in the propensity score matching analysis [20]. After the propensity score was estimated, a 1:1 match without replacement was performed using nearest neighbor matching with a 0.2 SD caliper width.…”