Identifying hotspots in five year survival electronic health records of older adults

Ankit Agrawal, Jason Scott Mathias, David Baker, Alok Nidhi Choudhary

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Understanding the prognosis of older adults is a big challenge in healthcare research, especially since very little is known about how different comorbidities interact and influence the prognosis. Recently, a electronic healthcare records dataset of 24 patient attributes from Northwestern Memorial Hospital was used to develop predictive models for five year survival outcome. In this study we analyze the same data for discovering hotspots with respect to five year survival using association rule mining techniques. The goal here is to identify characteristics of patient segments where the five year survival fraction is significantly lower/higher than the survival fraction across the entire dataset. A two-stage post-processing procedure was used to identify non-redundant rules. The resulting rules conform with existing biomedical knowledge and provide interesting insights into prognosis of older adults. Incorporating such information into clinical decision making could advance person-centered healthcare by encouraging optimal use of healthcare services to those patients most likely to benefit.

Original languageEnglish (US)
Title of host publication2016 IEEE 6th International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509041992
DOIs
StatePublished - Dec 30 2016
Event6th IEEE International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2016 - Atlanta, United States
Duration: Oct 13 2016Oct 15 2016

Other

Other6th IEEE International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2016
CountryUnited States
CityAtlanta
Period10/13/1610/15/16

Keywords

  • Association rule mining
  • hotspots
  • older adults
  • prognosis

ASJC Scopus subject areas

  • Computer Science Applications
  • Computational Mathematics
  • Medicine (miscellaneous)
  • Biotechnology
  • Genetics
  • Health Informatics
  • Agricultural and Biological Sciences (miscellaneous)

Fingerprint Dive into the research topics of 'Identifying hotspots in five year survival electronic health records of older adults'. Together they form a unique fingerprint.

Cite this