Opioid Epidemic & Readmission Analytics

Opioid Epidemic & Readmission Analytics

Northrop Grumman is a US Government Contractor. For this reason, this project is only open to students who are U.S. Citizens.

At Northrop Grumman, our work with cutting-edge technology is driven by something human: the lives our technology protects. It’s not the systems that drive us: it’s the soldier our systems bring home. It’s not just the equipment that motivates us: it’s the people our equipment protects. It’s not the innovation that gets us up in the morning: it’s whom those innovations serve. We’re united by our work to help people. And that mission makes our team even stronger.

Opioid abuse is among the deadliest population health crisis in America, with opioid-related overdoses taking an average of 44 lives each day. There have been a number of solutions suggested including research into abuse-deterrent opioids, an expansion of safe drug disposal programs, and increased use of alternative methods of pain control.   In addition, providers are also encouraged to be more responsible when prescribing pain management drugs.   Yet despite these efforts, the epidemic is getting worse.   One of the factors that is believed to be key in reducing the impact of the epidemic is analytics.

The student team will utilize a range of predictive data analytic techniques, including machine learning, to investigate opioid policy questions across a range of fields, including Supply Chain, Patient Treatment and Predictive Causality.

More Information

 

Students who successfully match to this project team will be required to sign the following two documents in January 2018:

Click here to view Student IP Agreement

Click here to view NDA

How to Apply

Project Features

  • Skill level All levels
  • Students 5-7 Students
  • Likely Majors BME, CS, DATA, IOE, , , MIDAS, , , SI, , STATS
  • Course Substitutions Honors, Data Science, MIDAS, IOE Capstone, IOE Grad
  • IP & NDA Required? Yes
  • Summer Opportunity See Complete Description for Details
  • Data Analytics (1 – 2 Students)

    Model Development on large datasets, applied statistics, basic machine learning

    • Data Science, IOE, Health informatics, Statistics, MIDAS
  • Application Coding (1-2 Students)

    General coding of analytic algorithms, database design, and data cleaning and an interest in data analytics

    • Computer Science
  • Advanced Analytics (2 – 3 Students)

    Advanced machine learning and data analytics techniques

    • Computer Science, EE, Data Science, MIDAS
  • Clinical Knowledge (2 students)

    Knowledge of clinical health environments and common measurements, with basic computer coding and/or quantitative skills.

    • Public Health, Nursing, Health Informatics, Biomedical Engineering

Faculty Mentor: Kerby Shedden
Professor of Statistics, Biostatistics, Director of CSCAR
Kerby Shedden received his PhD in Statistics from UCLA in 1999 and joined the University of Michigan the same year. His research interests include genomics, genetics, and other areas of life science where large and complex data arise. He also is interested in computational statistics and statistical software development. He participates in many collaborative research efforts including biomarker screening for cancer and kidney disease outcomes, cell-based screening for understanding the behavior of chemical probes in cells, and genetic association analysis for longitudinal traits.
 
Sponsor Mentor: Sanjiv Desai
M.D.
Sanjiv Desai has served since 2013 as the Chief Solutions Architect and Physician Informaticist for the Life Sciences Program, and as the Principal Investigator for Personalized Health Care Research and Development effort. He has broad professional experience and deep understanding of the healthcare and technology industries. Over the years, he has served in several leadership roles including solutions architect, clinical advisor, principal investigator, as well as technical and project manager.
 
Executive Sponsor Mentor: Sam Shekar
M.D.
Sam Shekar is the Northrop Grumman Chief Medical Officer. He provides strategic clinical direction for the Health Division and serves as an adviser to health organizations, customers and partners on medical and public health issues. He is a former US Public Health Service executive with service/expertise in NIH, HRSA, CMS and CDC over a twenty-year career. He received his medical and public health degrees from the University of Michigan.