webinar: how leading healthcare companies use mongodb
DESCRIPTION
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.TRANSCRIPT
How Leading Healthcare Companies use MongoDB
Marcelo Rocha DaSilvaMongoDB Solutions [email protected]
2
• 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
3
• 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
4
• 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
5
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
6
Health Care Data Challenges
Many New Apps Data Sources Better Care
Do More With LessFaster Time to Patient
7
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
MongoDB
9
MongoDB
The leading NoSQL database
Document Database
Open-Source
General Purpose
10
Electronic
Medical
Records
Large Data
Volumes
Evolving
Data
Model
MongoDB Health Care Use Cases
11
Agility
How?
Scalability
$Value
12
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
13
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
14
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" }
] }
15
• 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”}
16
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
17
• 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
18
• 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
19
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
20
Better Data Locality
Scale - Performance
In-Memory Caching
In-Place Updates
21
Scale – Auto-Sharding
Auto-Sharding
• Increase capacity as you go
• Commodity and cloud architectures
• Improved operational simplicity and cost visibility
22
Scale – HA & Replication
• Automated replication and failover
• Multi-data center support
• Improved operational simplicity (e.g., HW swaps)
• Data durability
23
High Availability
• Highly Available
• Geographically distributed
• Fully Consistent
• Data durability
DC1
DC2
DC3
24
High Availability & Scale
DC1
DC2
DC3
25
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
26
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