PPADS: Physician-PArent Decision-Support for NICU Dr. Monique Frize, O.C., P. Eng., FIEEE Systems and Computer Engineering (SCE), Carleton University Erika Bariciak, MD Children’s Hospital of Eastern Ontario (CHEO) Jeff Gilchrist, PhD Adjunct professor, SCE, Carleton University Frize Bariciak Gilchrist Medinfo 2013
Content Objectives (CDR, ANN, PPADS) Methodology Results Conclusion and Future Work Frize Bariciak Gilchrist Medinfo 2013
Objectives Collect data from NICU patients in real-time and store in Clinical Data Repository Adapt our outcome estimation system to processing real-time data Develop PPADS: A decision-support module for physicians and a module for parents. Frize Bariciak Gilchrist Medinfo 2013
Clinical Data Repository Design Database uses open source MySQL and Entity- Attribute-Value format + time (EAVT). Confidential information separated from data for research. Study ID is used to associate patient ID with research data in an anonymous way Frize Bariciak Gilchrist Medinfo 2013
Clinical Data Repository Frize Bariciak Gilchrist Medinfo 2013
Outcome estimations Decision Trees and Artificial Neural Network Estimating Mortality Using real time data and summary data. Frize Bariciak Gilchrist Medinfo 2013
Methodology 1. Evaluation of CDR: storage, speed, complexity and pilot survey at hospital (MeMeA 2013) 2. Outcome estimations Collected 85 million data points from 634 infants in NICU 2010 and 2011 Admission (12 hrs), 24 hrs, 48 hrs 5x2 cross validation approach Pre-processing and ANN analysis 3. Developed PPADS: Physician module and Parent module Frize Bariciak Gilchrist Medinfo 2013
Results--CDR CDR was better performing than the single EAV and the Multi-data type in terms of storage space, speed and complexity of query. Pilot test at CHEO with over 75 researchers and physicians: very positive results. Frize Bariciak Gilchrist Medinfo 2013
Results– Outcome estimation Best results were obtained with data collected at 48 hours after admission. Mortality estimations: Specificity of 99 %; sensitivity of 63%; PPV of 73%; and NPV of 98%... which meet our clinician’s expectations. Frize Bariciak Gilchrist Medinfo 2013
Results-- PADS PPADS: Identified criteria and mode of operation Examined standards, applied IPDAS Usability 8 parents and 5 neonatologists with very positive results. Frize Bariciak Gilchrist Medinfo 2013
PPADS: Physician-Parent Decision Support Frize Bariciak Gilchrist Medinfo 2013
Physician Module Summary Page Frize Bariciak Gilchrist Medinfo 2013
Parent Module Patient management decision – Families bear: Emotional consequences Financial consequences Collaborative care decisions Frize Bariciak Gilchrist Medinfo 2013
Parent Account Home Page Current condition Current treatments Outcome predictions Decision support aid Glossary Frize Bariciak Gilchrist Medinfo 2013
Home Page Parents Frize Bariciak Gilchrist Medinfo 2013
Outcome Estimation Example Frize Bariciak Gilchrist Medinfo 2013
Decision-Support Process Frize Bariciak Gilchrist Medinfo 2013
Conclusion and Future Work CDR design de-identifies data automatically, uses opens- source tools and easy to collect, store, and retrieve data. ANN performs better than Decision Trees; expanding to predict other outcomes (Length of stay, duration ventilation, IVH, BPD, NEC, ROP) with alerts. – Future work: add input variables to improve performance. – Add warnings and alerts and perform usability study. PPADS well received by physicians and parents – Next phase: parents of infant who died; then randomised clinical trial with parents of babies in NICU – More types of decisions will be added. Frize Bariciak Gilchrist Medinfo 2013
Contact Information Monique Frize, P. Eng., O.C., FIEEE Distinguished Professor, Carleton University Systems and Computer Engineering Ottawa Ontario Canada Frize Bariciak Gilchrist Medinfo 2013