Operations Research, Systems Engineering and Industrial Engineering Commons^™

Extracting Patterns In Medical Claims Data For Predicting Opioid Overdose, Ryan Sanders

Graduate Theses and Dissertations

The goal of this project is to develop an efficient methodology for extracting features from time-dependent variables in transaction data. Transaction data is collected at varying time intervals making feature extraction more difficult. Unsupervised representational learning techniques are investigated, and the results compared with those from other feature engineering techniques. A successful methodology provides features that improve the accuracy of any machine learning technique. This methodology is then applied to insurance claims data in order to find features to predict whether a patient is at risk of overdosing on opioids. This data covers prescription, inpatient, and outpatient transactions. Features created …

A Computational Simulation Model For Predicting Infectious Disease Spread Using The Evolving Contact Network Algorithm, Buyannemekh Munkhbat

Masters Theses

Commonly used simulation models for predicting outbreaks of re-emerging infectious diseases (EIDs) take an individual-level or a population-level approach to modeling contact dynamics. These approaches are a trade-off between the ability to incorporate individual-level dynamics and computational efficiency. Agent-based network models (ABNM) use an individual-level approach by simulating the entire population and its contact structure, which increases the ability of adding detailed individual-level characteristics. However, as this method is computationally expensive, ABNMs use scaled-down versions of the full population, which are unsuitable for low prevalence diseases as the number of infected cases would become negligible during scaling-down. Compartmental models use …

Performance Study Of An Unconventional Breathresponse Papr Against A N95 Ffr And Conventional Paprs, Huihui Yang

Graduate Theses, Dissertations, and Problem Reports

Healthcare workers (HCWs) are the first responders when infectious pathogens occur. Powered air-purifying respirators (PAPRs) are one of the most widely used personal protective equipment for healthcare workers. Currently, few studies have been performed with HCWs in the actual healthcare work environments to assess discomforts, acceptance and protective efficiency towards wearing and use of PAPRs. The main purpose of this dissertation was to introduce and assess a brand new unconventional PAPR (Koken breath-response PAPR). The protection performance and user preferance of this unconventional PAPR were studided and compared to that of a N95 FFR and traditional PAPRs.

Firstly, a laboratory …

Analysis Of User Preference With N95 And Powered Air-Purifying Respirators In A Healthcare Work Environment, Brittany Renee Carver

Graduate Theses, Dissertations, and Problem Reports

For those working in the healthcare field, personal protective equipment is vital. Healthcare workers are often first responders when it comes to dealing with patients who are infected or when a disease outbreak occurs. The Occupational Safety and Health Administration (OSHA) requires all healthcare operations to provide employee protection against blood borne pathogens. With the increase of life-threatening disease outbreaks, such as SARS in 2003 and Ebola in 2014, it is of the upmost importance to make sure respirators are best suited for users and acceptable for long term use. It has been shown through previous studies that due to …