Medicine and Health Sciences Commons^™

Investigating Interactive Methods In Remote Chestfeeding Support For Lactation Consulting Professionals In Brazil, Jessica De Souza, Cinthia Calsinski, Kristina Chamberlain, Franceli L. Cibrian, Edward Jay Wang

Engineering Faculty Articles and Research

Objective: Lactation consultants (LCs) positively impact chestfeeding rates by providing in-person support to struggling parents. In Brazil, LCs are a scarce resource and in high demand, risking chestfeeding rates across many communities nationwide. The transition to remote consultations during the COVID-19 pandemic made LCs face several challenges to solve chestfeeding problems due to limited technical resources for management, communication, and diagnosis. This study investigates the main technological issues LCs have in remote consultations and what technology features are helpful for chestfeeding problem-solving in remote settings.

Methods: This paper implements qualitative investigation through a contextual study (n = 10) and …

Time-To-Event Modeling For Hospital Length Of Stay Prediction For Covid-19 Patients, Yuxin Wen, Md. Fashiar Rahman, Yan Zhuang, Michael Pokojovy, Honglun Xu, Peter Mccaffrey, Alexander Vo, Eric Walser, Scott Moen, Tzu-Liang Bill Tseng

Engineering Faculty Articles and Research

Providing timely patient care while maintaining optimal resource utilization is one of the central operational challenges hospitals have been facing throughout the pandemic. Hospital length of stay (LOS) is an important indicator of hospital efficiency, quality of patient care, and operational resilience. Numerous researchers have developed regression or classification models to predict LOS. However, conventional models suffer from the lack of capability to make use of typically censored clinical data. We propose to use time-to-event modeling techniques, also known as survival analysis, to predict the LOS for patients based on individualized information collected from multiple sources. The performance of six …