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How Leading Healthcare Companies use MongoDB Marcelo Rocha DaSilva MongoDB Solutions Architect [email protected]

Webinar: How Leading Healthcare Companies use MongoDB

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Healthcare providers continue to feel increased margin pressure, due to both macro-economic factors as well as significant regulatory change. In response to these pressures, leading healthcare organizations are leveraging new technologies to increase quality of care and simultaneously reduce costs. In this session, hear how MongoDB has enabled successful real world projects, such as: * Electronic Medical Records - A leading health care provider provides patient data to doctors and other professionals via a web-enabled Bring Your Own Device application * Reference Data Management - One of the country's largest clinical laboratory networks provides a scalable solution for the management of laboratory test results The use cases are specific to Healthcare but the patterns of usage - agility, scale, global distribution - will be applicable across many industries.

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Page 1: Webinar: How Leading Healthcare Companies use MongoDB

How Leading Healthcare Companies use MongoDB

Marcelo Rocha DaSilvaMongoDB Solutions [email protected]

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• Webinar will begin at 1pm ET

• There is a Q&A following the webinar. You can enter questions in the Q&A box to the Host and Presenter.

• A recording of the webinar will be available and emailed 24 hours after the event is complete.

• Audio should start immediately when you log into the event via Audio Broadcast. You will need a Voip headset and reliable internet connection for Audio Broadcast. If you are having issues connecting, please dial 1-877-668-4493; Access code: 668 308 088 Or ask a question in the Chat box.

• For any other issues please email [email protected].

MongoDB Healthcare webinarMongoDB Healthcare webinar

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• Need for greater efficiency driven by the market and the Patient Affordable Care Act

• Today’s health data lives in silos• Cultural barriers prevent faster adoption

of emerging technologies• Data lives in silos, not easily shared

Health Care ChallengesHealth Care Challenges

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• Federal Incentives for Electronic Medical Records and Electronic Health Records

• Sensors, devices, network bandwith, and storage costs have fallen dramatically.

• Opportunity to make medical decisions based on the data is available today

Health Care OpportunitiesHealth Care Opportunities

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Digital HumansDigital Humans

Source:http://health.usnews.com/health-news/hospital-of-tomorrow/articles/2013/07/12/how-technology-is-transforming-health-care_print.html

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Health Care Data Challenges

Many New Apps Data Sources Better Care

Do More With LessFaster Time to Patient

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With the right tools the government, health care providers, and insurers can

•Build new applications not possible before

•Enhance service to patients significantly

•Remove data redundancy

•Better assess and effect health indicators

•Reduce cost

Big Data Is An OpportunityBig Data Is An Opportunity

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MongoDB

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MongoDB

The leading NoSQL database

Document Database

Open-Source

General Purpose

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Electronic

Medical

Records

Large Data

Volumes

Evolving

Data

Model

MongoDB Health Care Use Cases

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Agility

How?

Scalability

$Value

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To provide the best database for how we build and run apps today

MongoDB Vision

Build–New, complex, varying data–Flexibility–New languages–Faster development

Run–Big Data scalability–Real-time–Commodity hardware–Cloud

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MongoDB Features

• JSON Document Model with Dynamic Schemas

• Auto-Sharding for Horizontal Scalability

• Text Search

• Aggregation Framework and MapReduce

• Full, Flexible Index Support and Rich Queries

• Built-In Replication for High Availability

• Advanced Security

• Large Media Storage with GridFS

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RDBMS

Agility – Document Oriented Model

MongoDB

{ _id : ObjectId("4c4ba5e5e8aabf3"), employee_name: "Dunham, Justin", department : "Marketing", title : "Product Manager, Web", report_up: "Neray, Graham", pay_band: “C", benefits : [ { type :  "Health", plan : "PPO Plus" }, { type :   "Dental", plan : "Standard" }

] }

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• MongoDB does not need any pre-defined data schema.

• Every document could have different data

Agility – Dynamic Schema Agility – Dynamic Schema

{name: “jeff”, eyes: “blue”, height: 72, boss: “ben”}

{name: “brendan”, aliases: [“el diablo”]}

{name: “ben”, hat: ”yes”}

{name: “matt”, pizza: “DiGiorno”, height: 74, boss: 555.555.1212}

{name: “will”, eyes: “blue”, birthplace: “NY”, aliases: [“bill”, “la ciacco”], gender: ”???”, boss: ”ben”}

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Agility – Rich Query and Aggregation

{

object: ‘M1 Abrahms 3123’,

type: ‘Armored Vehicle’,

owner: ‘5th Armored’,

location: [45.123,47.232],

current_range: 245

armament: [

{ model: ‘105mm M68A1’,

type: ‘Rifled Cannon’,

range: 100000, … },

{ model: ‘120mm M256’,

type: ‘Smooth Bore Cannon’}],

crew: [ {name: ‘Paul’, …

weight: 126000,

equipment: […

desc: “This unit is highly …

}

Rich Queries• Find all armored vehicle under 64 tons

with a smooth bore cannon and a crew member with IED removal training

Geospatial• Find all units within a 220 mile radius of

a position with transport capacity of 20 sorted by proximity

Text Search • Find all units having Arabic mentioned

Aggregation• Calculate the average range of units

within the Afghanistan Theater of Operation

Map Reduce• Find correlations between co-located

units and mission casualties

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• Electronic Medical Records

• Paper based chart is now completely digital

• System has a large number of interfaces

• Bring your own device allows faster adoption and new possibilities.

• ACID transaction – Fully consistent data store

• Flexible data model

• Modern development languages

• High Availability

Use Case: Hospital

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• Large Data Volumes

• Scalability

• Enterprise ready – Security, Backups

• Rich query language

• ACID transaction – Fully consistent data store

• Flexible data model

• Modern development languages

Use Case: Clinical Tests

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Agility – Native Language Drivers

ShellCommand-line shell for interacting directly with database

DriversDrivers for most popular programming languages and frameworks

> db.collection.insert({company:“10gen”, product:“MongoDB”})> > db.collection.findOne(){

“_id”: ObjectId(“5106c1c2fc629bfe52792e86”),“company”: “10gen”“product”: “MongoDB”

}

Java

Python

Perl

Ruby

Haskell

JavaScript

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Better Data Locality

Scale - Performance

In-Memory Caching

In-Place Updates

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Scale – Auto-Sharding

Auto-Sharding

• Increase capacity as you go

• Commodity and cloud architectures

• Improved operational simplicity and cost visibility

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Scale – HA & Replication

• Automated replication and failover

• Multi-data center support

• Improved operational simplicity (e.g., HW swaps)

• Data durability

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High Availability

• Highly Available

• Geographically distributed

• Fully Consistent

• Data durability

DC1

DC2

DC3

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High Availability & Scale

DC1

DC2

DC3

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Developer/Ops Savings•Ease of Use•Agile development•Less maintenance

Hardware Savings•Commodity servers•Internal storage (no SAN)•Scale out, not up

Software/Support Savings•No upfront license•Cost visibility for usage growth

Value - Lower TCO

DB Alternative

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MongoDB Products and Services

TrainingOnline and In-Person for Developers and Administrators

MongoDB Management Service (MMS)Cloud-Based Suite of Services for Managing MongoDB Deployments

SubscriptionsMongoDB Enterprise, MMS (On-Prem), Professional Support, Commercial License

ConsultingExpert Resources for All Phases of MongoDB Implementations

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