Healthcare

Predicting the outcome of malpractice lawsuits

Application Area: 

Project Details

Term: 

2005

Students: 

Andrea Chod, David Hofberg, John Jepsen, Christine Nguyen, Eric Zirofsky

University: 

UMD

Presentation: 

Judgment or settlement is an important consideration for professional reputation of doctors in malpractice lawsuits.

The project aim is to build a model for predicting the outcome of a malpractice suit: whether it will result in a settlement or judgment, using data from the National Practitioner Data Bank

Understanding Health Insurance Coverage in the US

Application Area: 

Project Details

Term: 

2007

Students: 

Jason Davis, Clarette Kim, Hari Kosaraju, Scott Wood

University: 

UMD

Presentation: 

Report: 

Our goal was to use explanatory data mining techniques to better understand the characteristics of the U.S. population that lack health insurance. Our results will be used to inform health policy and business officials as they develop strategies to address the uninsured population.

Predicting Delays in the Operating Room

Application Area: 

Project Details

Term: 

2007

Students: 

Chris Low, Igor Nakshin, Xinyang Zou

University: 

UMD

Presentation: 

Report: 

According to Press Ganey’s Physician’s Office and Outpatient Pulse 2007, a widely used report
in health care industry, on time appointment performance in ambulatory surgery is one of the
most important factors with respect to patient satisfaction. However, how to best optimize the
O.R. scheduling has been a long standing, highly debated issue within the healthcare industry.

Quality-of-care factors that differentiate hospitals in the Northeast vs. other regions

Application Area: 

Project Details

Term: 

2008

Students: 

Kenyon Crowley, Selim Geron, Shih-Heng Hung, Seth Kelly, Liz Slobasky

University: 

UMD

Presentation: 

Report: 

The goal of this analysis is to look at the characteristics of U.S. hospitals to see if hospitals in certain geographical regions shared common features, particularly in the Northeast versus other areas of the country. The data used were taken from the HIMSS Analytics Database, which comprises data from over 5,000 hospitals. Specifically, we focused on variables relating to finances, quality of care and service metrics, and types of technology used by the facility.

Factors Driving Reproductive Health Supply Costs in Developing Countries

Application Area: 

Project Details

Term: 

2009

Students: 

Jeffrey Chia-Chieh Hong, John Geraghty, Joseph Lee, Khalil Qasimi, Emma Spight

University: 

UMD

Presentation: 

Report: 

Due to lack of technical expertise and resources John Snow, Inc. (JSI) has had difficulty understanding the Reproductive Health Interchange database and creating a more cost efficient contraceptive procurement process. Our goal was to use explanatory data mining techniques to gain a better understanding of the driving input variables and suggest alternative procurement strategies.

Quality-of-care factors in U.S. nursing homes

Application Area: 

Project Details

Term: 

2009

Students: 

Erica Eisenhart, Alon Gotesman, Audra Johnson, Ben Meadema, Shalin Saini

University: 

UMD

Presentation: 

Report: 

Thousands of Americans reside in nursing homes across the US, with facilities spanning a wide range of sizes, occupancy rates, staffing levels and expertise, available services, business models and managerial expertise. This great variability between each facility results in a highly divergent quality levels, creating a substantial challenge for families across the country: which home should they choose for their elderly relatives.

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