How can hospitals change practice to better implement smoking cessation interventions? A systematic review

Smoking cessation reduces the risk of death, improves recovery, and reduces the risk of hospital readmission. Evidence and policy support hospital admission as an ideal time to deliver smoking-cessation interventions. However, this is not well implemented in practice. In this systematic review, the authors summarize the literature on smoking-cessation implementation strategies and evaluate their success to guide the implementation of best-practice smoking interventions into hospital settings. The CINAHL Complete, Embase, MEDLINE Complete, and PsycInfo databases were searched using terms associated with the following topics: smoking cessation, hospitals, and implementation. In total, 14,287 original records were identified and screened, resulting in 63 eligible articles from 56 studies. Data were extracted on the study characteristics, implementation strategies, and implementation outcomes. Implementation outcomes were guided by Proctor and colleagues' framework and included acceptability, adoption, appropriateness, cost, feasibility, fidelity, penetration, and sustainability. The findings demonstrate that studies predominantly focused on the training of staff to achieve implementation. Brief implementation approaches using a small number of implementation strategies were less successful and poorly sustained compared with well resourced and multicomponent approaches. Although brief implementation approaches may be viewed as advantageous because they are less resource-intensive, their capacity to change practice in a sustained way lacks evidence. Attempts to change clinician behavior or introduce new models of care are challenging in a short time frame, and implementation efforts should be designed for long-term success. There is a need to embrace strategic, well planned implementation approaches to embed smoking-cessation interventions into hospitals and to reap and sustain the benefits for people who smoke.     

Quantitative interpretation of utterances and movements from videoed interactions between rheumatology nurses and patients commencing methotrexate: a pilot study

Clinical Rheumatology - Educating patients about methotrexate is a core role of rheumatology nurses. We have previously reported the scoring of videoed interviews of rheumatology nurses educating...     

The social vulnerability metric (SVM) as a new tool for public health

Objective

To derive and validate a new ecological measure of the social determinants of health (SDoH), calculable at the zip code or county level.

Data Sources and Study Setting

The most recent releases of secondary, publicly available data were collected from national U.S. health agencies as well as state and city public health departments.

Study Design

The Social Vulnerability Metric (SVM) was constructed from U.S. zip-code level measures (2018) from survey data using multidimensional Item Response Theory and validated using outcomes including all-cause mortality (2016), COVID-19 vaccination (2021), and emergency department visits for asthma (2018). The SVM was also compared with the existing Centers for Disease Control and Prevention's Social Vulnerability Index (SVI) to determine convergent validity and differential predictive validity.

Data Collection/Extraction Methods

The data were collected directly from published files available to the public online from national U.S. health agencies as well as state and city public health departments.

Principal Findings

The correlation between SVM scores and national age-adjusted county all-cause mortality was r = 0.68. This correlation demonstrated the SVM's robust validity and outperformed the SVI with an almost four-fold increase in explained variance (46% vs. 12%). The SVM was also highly correlated (r ≥ 0.60) to zip-code level health outcomes for the state of California and city of Chicago.

Conclusions

The SVM offers a measurement tool improving upon the performance of existing SDoH composite measures and has broad applicability to public health that may help in directing future policies and interventions. The SVM provides a single measure of SDoH that better quantifies associations with health outcomes.