Identifying hotspots in five year survival electronic health records of older adults
| Autor: | Alok Choudhary, Jason S. Mathias, Ankit Agrawal, David W. Baker |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Gerontology
Biomedical knowledge Association rule learning business.industry Health records computer.software_genre Survival outcome 03 medical and health sciences 0302 clinical medicine Clinical decision making 030220 oncology & carcinogenesis Health care Medicine 030211 gastroenterology & hepatology Data mining business computer |
| Zdroj: | ICCABS |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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