1. MongoDB PostgreSQL SaaS http://www.checkqm.com Quality Measure Storage
User entered data
Screen Shots
SaaS
Amazon EC2

2. January, 2012 EMR Generated Data TDS (Legacy System) HL7 Feed
RN Documentation
Provider Documentation
TDS (Legacy System)
22 Years Patient Data
1.2M Patients
9M Records
Orders
Labs
Transcribed Results
Patient Record
HL7 Feed
Lab Results
Physiological Monitors
Ventilators
Transcribed Reports
Radiology Results
Endoscopy Results
Orders
External Data
Home Monitoring
Personal Health Record
Social Media
*Twitter
*Foursquare
*Yelp
*RSS & Blog

3. Big Data = Complete Data
The Electronic Medical Record is primarily transactional taking feeds from source systems via an interface engine.
The Enterprise Data Warehouse is a collection of data from the EMR and various source systems in the enterprise.
In both cases decisions are made concerning data acquisition.
Hadoop is capable of ingesting and storing healthcare data in total.

4. Big Data = Infrastructure
Low Cost of Entry & Scalable
Open Source
Commodity Hardware
UCI Hadoop Ecosystem
8 nodes
4 terabytes
Yahoo Hadoop Ecosystem
60K nodes
160 petabytes
Cloud Ready

5. Big Data = Interoperability
An Ecosystem that Supports
Hadoop (HDFS)
MongoDB (NoSQL)
Neo 4j (Graph Database)
Relational Data Base
MapReduce
JBoss Drools
Mahout

6. Limits of Current Ecosystem
The Electronic Medical Record is not up to the task of handling complex operations such as anomaly detection, machine learning, building complex algorithms or pattern set recognition.
Enterprise Data Warehouses (EDW) suffer from a latency factor of up to 24 hours. The EDW serves clinicians, operations, quality and research retrospectively as opposed to real time.

7. Data Information Knowledge Wisdom
Saritor
Data Information Knowledge Wisdom
A healthcare information ecosystem built on “Big Data” technologies capable of serving the needs of clinicians, operations, quality and research in real time and in one environment.
Able to ingest all healthcare generated data both internal and external.
Platform for advanced analytics such as early detection of sepsis & hospital acquired conditions. Prediction of potential readmissions. Complex algorithm and machine learning platform.

8. Health Care Data Sources
Legacy Systems
All HL7 Feeds (EMR source systems)
All EMR Initiated Data
Device Data (in one minute intervals)
Physiological Monitors
Ventilators
Smart Pumps
Real Time Location System
Hospital Sensors
Genomic Data
Home Monitoring
Social Media
Healthcare Organization Sentiment Analysis
Patient Engagement

9. Saritor Initial Functionality
Integration with EMR to View Legacy Data
30 Day Readmit Prediction (UCI Centric)
Early Sepsis Detection & Notification
Integration with UCI Clinical Intelligence Applications
Chronic Disease Scorecards
Home Monitoring Analytics
Social Media Sentiment Analysis

11. Algorithm Management Available Data Set
Input Data Attributes, Rules, Parameters
Input Data Attributes, Rules, Parameters
Training Data Set
Test Data Set
Hypothesis / Algorithm Model
(Core Engine with the Equations / Analysis)
Statistical
Techniques
Hypothesis / Algorithm Model
(Core Engine with the Equations/ Analysis)
Statistical
Techniques
Output / Results (Actual)
Output / Results (Actual)
Analyze Output for Model Behavior
(Actual versus Desired)
Analyze Output for Model Behavior
(Actual versus Desired)
Not Satisfactory
Satisfactory Result
Not Satisfactory
Satisfactory Result
Identify Improvements
Matches Expectation
Identify Improvements
Matches Expectation
Feedback and Refine the Model
Release for Testing the Model
Feedback and Refine the Model
Baseline the Pattern
Publish new version to Repository
Diagnosis
Patterns Repository

12. Quantified Self
Personal Informatics
mHealth

13. PHR Centric Health
HIE
Saritor
EMR

15. The difference between a vision and a hallucination
is that other people
can see the vision.
Marc Andreessen

16. Charles Boicey cboicey@uci.edu @N2InformaticsRN