Discovery Park Undergraduate Research Internship Program

"Healthcare database exploration and analysis"

About the Project

Project Time & Type:
Fall 2010 - DURI
Research area(s):
healthcare, statistics
Project Description:
RCHE welcomes highly motivated undergraduate students to participate in database exploration and analyses using either the hospital readmission or the infusion pump project data. Hospital readmission reflects concern in both quality of care as well as unnecessary costs. Studies show that approximately 20 percent of patients are re-hospitalized within 30 days of discharge. By using large scale hospital and patient admission data, we are developing statistical models to predict risk for health deterioration and therefore hospital readmission. Medication errors related to intravenous (IV) infusion present the greatest potential for adverse drug events. Fortunately, the new generation of infusion pumps, specifically in this case the Smart Pump, incorporate multiple comprehensive libraries of drugs, usual concentrations, dosing units (e.g., mcg/kg/min, units/hr) and dose limits. Subsequently, it can capture and avert errors during pump operation. The infusion pump database consists of logs that identify the devices and medications or fluids, with descriptions of alerts, events, and errors from three hospitals over a five-year period. This project will explore the database, analyze and report on the medicine limits, overrides, usages and trends.
Expected Student Contributions:
Under the hospital readmission project, the student will have the opportunity to become familiar with the SAS environment, learn SAS programming, use SAS software to clean and manage large scale healthcare data, and prepare data for analyses. Further, the student will gain experience with statistical prediction models. By taking part in the infusion pump project, the student will become acquainted with data exploration, relevant graph and report generation, and infusion pump usage and possible trends. The determination of the specific project will be dependent on the availability of data at the start of the project.
Related Website(s):
None
Desired Qualifications:
Interest in healthcare related research, strong quantitative background, some experience with programming languages, and interest and willingness to learn a new programming language.
Estimated Weekly Hours:
10
Department awards independent research credits for this project?
Yes, 3 credit hours

Professor in Charge

Name:
Schultz, Mary
Deptartment/College:
hold/discovery park

Student Supervisor

Name:
Tian Zhiyi
Title:
Research Scientist

Cooperating Faculty

Name:
Ann Christine Catlin
Deptartment/College:
Rosen Center