Subgrouping Ulcerative Colitis Patients using Administrative Claims Data

Approximately 3 million patients in the US have been diagnosed with Ulcerative Colitis, a chronic inflammatory disease affecting the colon. Uncovering patient subgroups could improve treatment guidelines and help physicians choose an appropriate treatment plan for a patient. Here, we outline a Python implementation to generate a cohort from a dataset in the OMOP Common Data Model (CDM), propose a patient timeline visualization tool, create and analyze a cohort of Ulcerative Colitis patients using a claims dataset. We extract patient features and use dimensionality reduction techniques along with clustering to identify patient subgroups. We observe four patient subgroups consisting of distinct patient characteristics, most prominently age, insurance type, sex, and type of initial conventional therapy prescription.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2021

Author dc:creator

• Berlin, Heather

Advisor dc:contributor.advisor

• Szolovits, Peter

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright MIT

Licence dc:rights.uri

• http://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/139132

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/139132