Finding patterns of chronic disease and medication prescriptions from a large set of electronic health records by Ricard Gavaldà

1. Finding patterns of chronic disease and
medication prescriptions from a large set of
electronic health records
Ricard Gavaldà (UPC)
Joint work with Martí Zamora (UPC), Ester Amado,
Sílvia Cordomí, Esther Limón, and Juliana Ribera (ICS)
3rd Graph-TA, March 18th, 2015
gavalda@cs.upc.edu

2. Context
Population aging in developed countries
Chronic disease, polymedication
5% of population uses over 50% of resources
Main concerns of Institut Català de la Salut:
Understand the landscape
Define useful indicators
Prior to define policies

3. The database
ICS primary care visits, Barcelona, 2013
1.6M potential patients, 0.5M actually present
12M health annotations (diagnostics, tests, findings)
7M medication prescriptions

4. Current prototype
Navigate graph of diagnostics
Display strength of associations
Find k-ary associations among diagnostics (syndromes)
Find rules relating diagnostics and medications
Flag unexplained medications, untreated diagnostics

5. Future functionalities
Predictive analytics
Temporal evolution of patients
More data quality checks
Differential analysis (e.g., geographic, sociodemographic)
Build rational prescription schedules
. . .