Simulation Study: Clinical Center Esslingen—Process Analysis in the Emergency Department

2013 ◽  
pp. 529-550
Author(s):  
Corinna Klink ◽  
Daniel Denkert ◽  
Mario Vargheamidis ◽  
Nils Kern ◽  
Tobias Lörch
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Shan Jiang ◽  
Joshua L. Warren ◽  
Noah Scovronick ◽  
Shannon E. Moss ◽  
Lyndsey A. Darrow ◽  
...  

Abstract Background Short-term associations between extreme heat events and adverse health outcomes are well-established in epidemiologic studies. However, the use of different exposure definitions across studies has limited our understanding of extreme heat characteristics that are most important for specific health outcomes or subpopulations. Methods Logic regression is a statistical learning method for constructing decision trees based on Boolean combinations of binary predictors. We describe how logic regression can be utilized as a data-driven approach to identify extreme heat exposure definitions using health outcome data. We evaluated the performance of the proposed algorithm in a simulation study, as well as in a 20-year time-series analysis of extreme heat and emergency department visits for 12 outcomes in the Atlanta metropolitan area. Results For the Atlanta case study, our novel application of logic regression identified extreme heat exposure definitions that were associated with several heat-sensitive disease outcomes (e.g., fluid and electrolyte imbalance, renal diseases, ischemic stroke, and hypertension). Exposures were often characterized by extreme apparent minimum temperature or maximum temperature over multiple days. The simulation study also demonstrated that logic regression can successfully identify exposures of different lags and duration structures when statistical power is sufficient. Conclusion Logic regression is a useful tool for identifying important characteristics of extreme heat exposures for adverse health outcomes, which may help improve future heat warning systems and response plans.


2012 ◽  
Vol 38 (4) ◽  
pp. 322-328 ◽  
Author(s):  
Zhen Zeng ◽  
Xiaoji Ma ◽  
Yao Hu ◽  
Jingshan Li ◽  
Deborah Bryant

2015 ◽  
Vol 22 (2) ◽  
pp. 318-323 ◽  
Author(s):  
Rahul C. Basole ◽  
Mark L. Braunstein ◽  
Vikas Kumar ◽  
Hyunwoo Park ◽  
Minsuk Kahng ◽  
...  

Abstract Health care delivery processes consist of complex activity sequences spanning organizational, spatial, and temporal boundaries. Care is human-directed so these processes can have wide variations in cost, quality, and outcome making systemic care process analysis, conformance testing, and improvement challenging. We designed and developed an interactive visual analytic process exploration and discovery tool and used it to explore clinical data from 5784 pediatric asthma emergency department patients.


2020 ◽  
Vol 10 (4) ◽  
pp. 91
Author(s):  
Kelsey J. Hart ◽  
Denise Gormley

The emergency department to intensive care unit nurse handoff process was found to be inefficient in a Midwest community hospital, resulting in prolonged admission times. The purpose of this project was to determine if implementation of a standardized bedside nurse handoff process would affect admission efficiency. Efficiency of nurse handoff, efficiency of emergency department to intensive care unit admissions, and rates of intensive care unit patient boarding in the emergency department were examined. A task force composed of staff nurses developed a standardized bedside nurse handoff process following guidelines from the literature. This new handoff process incorporated the evidence-based concepts of bedside report, standardization, and electronic medical record. Stakeholder and staff buy-in were obtained, and the process was implemented. Outcomes were evaluated six months prior to- and one-year post-implementation of the standardized bedside handoff process. Analysis of one-year post-implementation data revealed an improvement in average handoff time by 15 minutes, an improvement in average admission time by 17 minutes, and a reduction in intensive care unit patient boarding by 19.5%. By improving efficiency of the nurse handoff process, and therefore the admission process, the findings of this project have the potential to reduce patient boarding and improve the quality of patient care. This quality improvement project also contributes to a gap in the current body of evidence pertaining to interdepartmental nurse handoffs.


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