webinar: electronic health records (ehrs) and mongodb - advancing the data platform for the future

Agenda

•  Who is NewWave? •  Why Mongo? •  How NewWave Uses Mongo •  NewWave’s Road Map •  Questions?

NewWave Telecom & Technologies, Inc. www.newwave-technologies.com

Who is NewWave? �  Established provider of innovative IT services,

solutions and support since 2004. �  SEI CMMI Maturity Level II Company �  8(a) Small Business, MBE Certified �  GSA IT Schedule 70 & 8(a) STARS II

�  Outstanding history in supporting Federal Healthcare Programs for years

�  Reputation for providing commercial and federal government clients reliable, cost effective technical solutions


Federal Emergency Management Agency (FEMA) •  Workman Compensation Claims Management

Department of Health and Human Services

•  Center of Medicaid and Medicare Services (CMS) •  Quality Net Identity Management (QIMS) •  Data Management (DM) IDIQ

•  Electronic Health Records •  Research, Data and Information System

(RDIS) IDIQ •  Data Collection Task •  MCSIS – Information Sharing System

NewWave Customers NewWave Telecom & Technologies, Inc. www.newwave-technologies.com

Current Projects Provider Screening Challenge (Crowdsourcing)

“To develop a multi-state, multi-program provider screening application capable of risk scoring, credential validation, identity authentication, and sanction checks, while lowering burden on providers and reducing administrative and infrastructure expenses for States and federal programs”

•  To operate in a cloud-based environment •  Federal Healthcare is looking for “reliable, scalable, and

cost-effective” software to improve screening of providers across state and program lines


Innovation Lab NewWave Telecom & Technologies, Inc. www.newwave-technologies.com

Current Projects Transformed Medicaid Statistical Information System

“Evaluate the final multi-state, multi-program provider screening application capable of risk scoring, credential validation, identity authentication, and sanction checks technical solution and provide information technology (IT) technical assistance for States implementing and piloting this solution”

•  To provide IT technical assistance (TA) including working with states as it relates to their state system requirements, IT system builds, and associated interfaces


Pre-Mongo Physical Architecture – Electronic Health Records

Load Balancer

IBM HTTP Server

IBM HTTP Server

WebSphere WebSphere

Oracle DB2 Oracle DB2

Oracle DB2

•  Traditional Architecture •  Not easily scalable

Health Information Technology and the Big Data

�  Making data available in real or near-real time �  Processing data without much moving around �  No need to replace with bigger and powerful servers; just add nodes to the

existing infrastructure

The need and the trends

“If US healthcare were to use big data creatively and effectively to drive efficiency and quality, the sector could create more than $300 billion in value every year. Two-thirds of that would be in the form of reducing US healthcare expenditure by about 8 percent.” - McKinsey

…and so MongoDB


Why Mongo? File Storage: •  GridFS ETL Data: •  Built-in aggregation framework for

simple applications •  Integrates with Hadoop for complex

data aggregation using Map/Reduce Versatility: •  Cloud-friendly •  Java-friendly Schema-free: •  Agile

Cost

Performance

Availability

Compa5bility


{

“_id” : ObjectId("4efa8d2b7d284dad101e4bc9"), “providerName” : “Dave Dawson”, “specialty” : “ Internal Medicine”

} {

“_id” : ObjectId("4efa8d2b7d284dad101e4bc9”), “providerName” : “Steve Towson”, “specialty” : “ Physical Therapy”, “fileName” : “ xray.jpg”

}

Why Mongo Over RDBMS? ü  Design-as-you-go

ü  Agile Methodology

Why Mongo Over RDBMS?

ü  For Applications requiring high performance and scalability without compromising on functionality

How We Use Mongo? •  Storing Electronic Health Records •  Mongo provides a convenient, powerful and

robust way to store structured/unstructured data

•  Leverage the use of GridFS to store large files, that are stored as chunks.

•  Integrate with Hadoop and “BI tool” to analyze data from local and external stores using Map/Reduce framework in Mongo.

MongoDB

Hadoop

NETEZZA TERADATA

Oracle IBM

MongoDB MongoDB

Electronic Health Data ApplicaWon


Architecture Diagram

Camel

HTML 5

JQuery

Ac5vi5-‐BPM/ Drools Open Geo

Elas5c Search

HTTP

MongoDB

Ac5ve MQ

GridFS

FTP

File

JMS

Spring Framework

Spring Security

Spring Security

Hadoop

Spring Data


SMTP

EHR Requirement: Efficient Data Exchange

Camel

Spring Data

MongoDB

FTP

File

JMS

The Need •  Exchange data smoothly and securely among

different actors •  Guaranteed interoperability

The Solution : Apache Camel •  Patterns to implement routing and mediation rules

in Java via Spring based XML •  Uses URIs to work directly with any kind of

Transport or messaging model ( FTP, File, JMS etc.)

•  Provides Business Activity Monitoring (BAM) •  Convenient storage of ETL data to Mongo •  Parallel processing and ordering of messages for

throughput and load balancing

Ac5ve MQ


SMTP

OpenGeo Elas5cSearch

EHR Requirement: Spatial Data and Search

The Need: •  Data Integration and spatial visualization •  View epidemiological region •  Demographic analysis •  Allow users to search health records efficiently

The Solution: •  OpenGeo Suite

•  MongoDB – WMS and WFS data •  “Object Embedding” in OpenLayers •  HTML5, JQuery and OpenLayers for desired map

view •  Google’s geocoder for locating addresses

•  Elastic Search •  Modeled with document oriented DBs •  Distributed based search support •  Elastic search engine on top of Apache Lucene

HTML 5

JQuery

HTTP

MongoDB

Spring Security


EHR Requirement: Rules Engine

The need: •  Automate workflows of administrative processes •  Increase business agility •  Automate activities •  Lower modification expenses on business logic

The solution: •  ActivitiBPM/Drools and Spring-data-mongo

•  Capable of processing large volumes of data •  Mongo for rule repository and storing user

documents (e.g. prescriptions) •  Rule 1: rule based services (e.g. calculating

premiums and refunds) •  Rule 2 : complex decision activities and content

based routing decision (automated or manual or both)

•  Rule 3: Work item allocation for manual processing steps (e.g. fraud detection)

HTML 5 JQuery

ActivitiBPM/ Drools

Spring Data

HTTP

MongoDB

Spring Security

ü  New Diseases ü  New or modified laws on the

health insurance market ü  New insurance products ü  New business model

Ac5ve MQ


Physical Architecture •  Expect high volumes of users and patient

information •  Sharding, an efficient and inexpensive

option •  Store metadata in Config Servers


Load Balancer

Nginx Nginx

JeYy JeYy

MongoS

Mongod Mongod

Mongod

NewWave Road Map


Multi-Cloud Environment


Public

Hybrid

Private

SaaS

PaaS

IaaS

Mongo for Social Media

“Sixty Percent of surveyed physicians and 65 percent of surveyed nurses are interested in using social networks for professional purposes” - Manhattan research Taking the Pulse, v9.0.

Use Case: •  EHR application relies on social media for

trend detection and intelligence gathering – natural disaster detection or flu outbreak tracking

Why Mongo?? • Integration with Spring Social • Mongo 2.2’s powerful aggregation framework • Built-in Map/Reduce framework • Sharding and replication capability

Twitter caught the 2010 cholera outbreak

in Haiti


QUESTIONS??

@NewWave_Tech Linkedin.com/company/newwave_technologies