Association between smoking, and hospital readmission among inpatients with psychiatric illness at an academic inpatient psychiatric facility, 2000–2015

Abstract

Introduction Smoking rates are up to 2–4 times higher among individuals with mental illness. Hospital readmissions for patients with psychiatric illness within a year of discharge are also high, and there is limited evidence of associations between smoking and these readmissions. Methods This study was a secondary data analysis using clinical data of psychiatric inpatients with initial admissions between the years 2000 and 2015. Following a descriptive analysis, logistic regression models were fitted to explore relationships between smoking and psychiatric hospital readmission within 30 days and a year of discharge. Results A total of 5439 patients with average age of 30.18 ± 15.97 were identified. Of this number, 47.0% were current smokers and 53.0% were never smokers. Within 30 days of discharge, 11% of the current smokers were readmitted compared to 9% of never smokers. The primary diagnoses with highest proportion of smokers were, opioid or substance use disorders (80.0%), schizophrenia (70.7%), alcohol dependence (68.2%), and bipolar disorders (50.8%). About 31% of current smokers were readmitted within one year of discharge compared to 26% of never smokers. Adjusted odds ratios for readmission within 1-year of discharge were, bipolar disorders (1.41, p = 0.01), schizophrenia (2.33, p < 0.001), and opioid/substance dependence (1.55, p = 0.01). Conclusion Significant relationships exist between smoking and readmission for patients with psychiatric illness. Smokers are more likely to be readmitted within 30 days or one year after discharge. Interaction of smoking and certain specific diagnoses significantly increases readmission.

Electroconvulsive therapy is associated with lower readmission rates in patients with schizophrenia

“…A unique aspect of our study design, compared with prior retrospective studies, is the use of XGBoost and propensity score matching methods. With the development of machine learning algorithms, screening for critical risk factors that affect the disease course can be applied to medical diseases including psychiatric disease [20][21][22] . The XGBoost model achieves the best prediction modelling among the machine learning models and traditional regression models [23] .…”

Dying to Quit: Understanding the Burden of Tobacco in Psychiatric Patients—A Clinical Review

“…In one study, psychiatric inpatients who smoked had a 33% increased chance of readmission within a year of discharge compared with never-smokers, which represented 5.1% excess annual psychiatric readmissions. 25 These differences were illustrated in a randomized trial conducted by Prochaska and colleagues who recruited people who smoked from psychiatric inpatient hospitals into a smoking cessation program. Program participants had a 2-fold lower risk of rehospitalization than those who did not participate in the program (OR = 0.52).…”

“…Therefore, it is incumbent on psychiatrists to address the outsized effect that smoking has on patients with mental illness. (Journal of Psychiatric Practice 2024;30; [23][24][25][26][27][28][29][30][31] KEY WORDS: smoking, mental illness, tobacco, psychiatry, public health…”

A Critique on Psychiatric Inpatient Admissions for Suicidality in Youth

“…In numerous research assessments, LOS in a psychiatric hospital for suicidal behavior was not related to the rate of suicide attempts, self-harm, or NSSI after hospital discharge or readmissions (Fontanella, 2008;Green and Worrall-Davies, 2008;Kagabo et al, 2017;Ougrin et al, 2013), although older studies reported that a longer LOS was associated with worse outcomes (Gold et al, 1993;Pfeiffer and Strzelecki, 1990). Regardless, Pottick (1995) is on the mark writing that insurance pressures have had the greatest impact on inpatient LOS for suicidality in youth.…”