The Effect of an Inpatient Smoking Cessation Treatment Program on Hospital Readmissions and Length of Stay
Bibliographic record
Abstract
BACKGROUND Most clinical research involving tobacco dependence treatment is related to outpatient interventions and focuses on health outcomes. Inpatient smoking cessation treatment has been found to be cost‐effective in the Canadian healthcare system, but the finding's applicability to US health systems is unclear. OBJECTIVE The objective of this study is to estimate the impact of an inpatient tobacco cessation treatment program on 30‐day readmission rates and length of stay (LOS). METHODS Participants were 28,994 patients admitted to the hospital between July 2012 and July 2014. Smokers were identified through the electronic medical records system and were offered cessation treatment. Program effects were estimated by using a difference‐in‐differences approach, comparing all smokers to all nonsmokers before versus after introduction of the program. Readmission rates were modeled by using probit regression; LOS was modeled by using truncated negative binomial regression. Models controlled for age, sex, race, payer, hospital department, severity of illness, and intensive care unit days. RESULTS The hospital‐initiated smoking cessation intervention had no significant effect on 30‐day readmission rates or LOS. Other control variables had the expected signs and were statistically significant. CONCLUSIONS The evaluation of an inpatient tobacco dependence treatment did not find significant short‐term changes in healthcare utilization in the first 30 days after initial hospitalization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".