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.     

Eulerian Algorithms for Computing the Forward Finite Time Lyapunov Exponent Without Finite Difference upon the Flow Map

In this paper, effective Eulerian algorithms are introduced for the computation of the forward finite time Lyapunov exponent (FTLE) of smooth flow fields. The advantages of the proposed algorithms mainly manifest in two aspects. First, previous Eulerian approaches for computing the FTLE field are improved so that the Jacobian of the flow map can be obtained by directly solving a corresponding system of partial differential equations, rather than by implementing certain finite difference upon the flow map, which can significantly improve the accuracy of the numerical solution especially near the FTLE ridges. Second, in the proposed algorithms, all computations are done on the fly, that is, all required partial differential equations are solved forward in time, which is practically more natural. The new algorithms still maintain the optimal computational complexity as well as the second order accuracy. Numerical examples demonstrate the effectiveness of the proposed algorithms.     

不同针灸疗法治疗寻常痤疮的网状Meta分析＊

目的 采用网状Meta分析方法，评价针刺、火针、艾灸等不同针灸疗法对寻常痤疮（acne vulgaris， AC）临床有效率及复发率的影响。方法 计算机检索PubMed、Embase、Cochrane、Web of Science、CINAHL、中国知网（China National Knowledge Infrastructure， CNKI）、万方数据库（WanFang Data）、中国生物医学文献数据库（China Biology Medicine disc， CBM）和维普中文期刊服务平台（VIP Database），搜集针灸疗法治疗寻常痤疮的随机对照试验（randomized controlled trail， RCT），检索时间均为建库至2021年3月，文献筛选、资料提取及偏倚风险评价均由两名研究者独立进行。数据分析使用Stata16.0软件。结果 纳入42项RCT，共3911例寻常痤疮患者。数据分析结果显示，临床总有效率：艾灸、放血、放血+穴位注射、放血+针刺、火针优于西药（P<0.05），放血、放血+穴位注射、放血+针刺、火针、穴位埋线优于针刺疗法（P<0.05），放血+针刺疗法优于自血疗法（P<0.05），累计排序概率曲线下面积（surface under the cumulative，SUCRA）显示放血+针刺治疗寻常痤疮总有效率最高；复发率：放血疗法+穴位注射优于电针（P<0.05），SUCRA结果显示针刺+自血疗法治疗寻常痤疮复发率最低。结论 放血联合针刺疗法在提高总有效率上具有最好的疗效，针刺联合自血疗法可有效降低复发率，受纳入研究所限，以上结论尚需更多大样本、高质量RCT进一步验证。     

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.