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Low-Burden Strategies to Promote Smoking Cessation Treatment Among Patients With Serious Mental Illness.


ABSTRACT: Patients with serious mental illness have high smoking prevalence and early mortality. Inadequate implementation of evidence-based smoking cessation treatment in community mental health centers (CMHCs) contributes to this disparity. This column describes a study of the effects of quality improvement strategies on treatment and cessation outcomes among patients with serious mental illness at four CMHCs. Two low-burden strategies, decision support and academic detailing with data-driven feedback, were implemented in the CMHCs' clinics from 2014 to 2016. Pre- and postimplementation data from pharmacy and medical records were analyzed. The percentage of patients receiving cessation medication increased from 5% to 18% (p?.001), and smoking prevalence decreased from 57% to 54% (p?.001). This quality improvement approach holds great potential for increasing the level of smoking cessation care for patients treated in CMHC settings. Decision support and academic detailing with feedback may be effective strategies to promote best practices.

SUBMITTER: Chen LS 

PROVIDER: S-EPMC6280191 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Low-Burden Strategies to Promote Smoking Cessation Treatment Among Patients With Serious Mental Illness.

Chen Li-Shiun LS   Baker Timothy B TB   Korpecki Jeanette M JM   Johnson Kelly E KE   Hook Jaime P JP   Brownson Ross C RC   Bierut Laura J LJ  

Psychiatric services (Washington, D.C.) 20180601 8


Patients with serious mental illness have high smoking prevalence and early mortality. Inadequate implementation of evidence-based smoking cessation treatment in community mental health centers (CMHCs) contributes to this disparity. This column describes a study of the effects of quality improvement strategies on treatment and cessation outcomes among patients with serious mental illness at four CMHCs. Two low-burden strategies, decision support and academic detailing with data-driven feedback,  ...[more]

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