Prevalence and predictors of tobacco treatment in an academic medical center.
BACKGROUND
Hospitalized smokers are a large and important but undertreated population. Although effective strategies have been developed to enhance smoking cessation, many hospitalized smokers still fail to benefit from these services. A study was conducted to examine the reach of services within a hospital tobacco treatment program and to identify predictors of referral and treatment.


METHODS
Electronic medical records were downloaded for all 3,600 smokers admitted to a 475-bed academic medical center hospital in a one-year period.


RESULTS
More than one in four of identified smokers were referred to the specialty service and nearly one in five received treatment. Logistic regression models found that Joint Commission core measure status (heart failure, myocardial infarction, and pneumonia) was the strongest predictor of referral, followed by a history of smoking for more than 10 years. Conversely, smokers admitted for emergency medical services were less likely to be referred compared with those admitted electively. Patients treated on surgical, obstetric, and psychiatric services were less likely to be referred for tobacco treatment than those treated on medical services. Of those referred, smokers with longer lengths of stay and those admitted through the emergency department were more likely to actually receive services.


CONCLUSIONS
To capitalize on hospitalization as a "teachable moment," other subpopulations, such as psychiatric and obstetric patients, deserve attention. Tobacco treatment services must be fully integrated into hospital systems, configured to deliver care to all smokers, and reimbursed to ensure sustainability. This study's identification of underserved groups, determination of potential roadblocks to delivery of services, and suggestion of ways to disseminate treatment equitably to all smokers should prove helpful to policymakers.
Faseru
Babalola
B
Department of Preventive Medicine and Public Health, University of Kansas Medical Center and School of Medicine, Kansas City, Kansas, USA. bfaseru@kumc.edu
Yeh
Hung-Wen
HW
Ellerbeck
Edward E
EE
Befort
Christie
C
Richter
Kimber P
KP
D000046:Academic Medical Centers / Q000706:statistics & numerical data*; D057286:Electronic Health Records; D006305:Health Status Indicators; D006801:Humans; D007297:Inpatients / Q000193:education* / Q000523:psychology / Q000706:statistics & numerical data; D016015:Logistic Models; D019982:Organizational Case Studies; D012017:Referral and Consultation / Q000706:statistics & numerical data; D012907:Smoking / Q000523:psychology / Q000628:therapy; D016540:Smoking Cessation / Q000379:methods / Q000523:psychology / Q000706:statistics & numerical data*