Department Projects


Hydra/Linea Transformation

The DocGraph community has been using an online system called Linea for about a year to catalog healthcare data. Linea is extremely useful to DocGraph and other people interested in healthcare data, because it makes healthcare data more available and facilitates data sharing among departments. Linea came from a fork in Merck's Hydra project that was tailored for DocGraph's needs. Development of Hydra continued while the Linea version remained static. Our task was to merge the existing features of Linea with the new features of Hydra.

Developing Team Summer 2016:

Megan Biernat, Gabriel Fournier, Anna Lamoureux, Martin Nesbitt, Joshua Russett, John Vonelli, Nicholas Zambelli


Identifying Misclassifications of Doctors in Medicare Data

Medicare data is notorious for having incorrect information. Fred Trotter estimates that 30% of doctors inside the Medicare Bill data from 2014 recorded incorrect addresses. With that knowledge, we took the initiative to explore how many doctors could possibly be misclassified inside the 2014 Medicare Billing data.

Developing Team:

William Collins & Alec Gerhart



Home Healthkit

For patients who attend annual check ups, health data is recorded and an opinion of general health is given based on trends over time. This method results in data having long periods of time between new entries, making trends difficult to track. Our sensor platform allows a patient to run tests at home and upload the results to a server, allowing for an increase in testing frequency. The server is accessible anywhere the internet is available, allowing patients to run tests in a doctor’s office, at home, or while traveling.

Developing Team:

Megan Biernat, Gabriel Fournier, Anna Lamoureux, Martin Nesbitt, Andrew Reed, Joshua Russett, Michael Turnbach, John Vonelli, Nicholas Zambelli



MorningStar

MorningStar is a project intended to introduce CS students to health data visualization. It was originally assigned to a senior capstone class in the spring of 2015 where the students would use d3 and diabetic poke data to show poke ratios on the state and county level. The tool is now being developed so that users may upload their own data files and access web APIs such as the Census Bureau, Google, and the CDC.

Developing Team Summer 2015:

Megan Biernat, William Collins, Alec Gerhart, Anna Lamoureux, Steve MacDonald, Charles McDonald, Martin Nesbitt, Andrew Reed, Josh Russett, Michael Turnbach, John Vonelli

Senior Capstone Contributors Spring 2015:

Jason Boccuti, Steve Chakif, Lewis Cooper, Jon Diehl, Hansen Huang, Michael Vitone


OpenMRS

OpenMRS is an open source EMR used in over 23 countries throughout the world, including 400+ installations in Nigeria. The OpenMRS core supports a modular design, which allows our module to function as an optional add-on to an active instance of OpenMRS. The module supports parameterized queries to provide anonymized data. Users can obtain data from one or more instances of OpenMRS to aggregate data to answer questions about population health.

Developing Team Summer 2014:

Megan Biernat, Jason Boccuti, Steve Chakif, Lewis Cooper, Alec Gerhart, Charlie McDonald, Vincent Pillinger

Senior Capstone Contributors Spring 2014:

Myles Barros, David Cariello, Justin Dilts, Michael Eckhart, Nick Forouraghi, Karli Gnehm, Rachel Johnson, Jesse Perry, Alli Samson, Alek Szilagy