elmallah june27 11am_room230_a
DESCRIPTION
Researchers and care providers wanted to have access to all of the patients` vitals signs (temperature, blood pressure, heart rate, and respiratory rate) but most of this data wasn?t recorded, only a few readings a day were posted to the patients Electronic Medical Record (EMR). The EMR isn`t meant to store such volume of data, let alone to perform any data mining on it. This session will describe the architecture of the solution that was implemented to collect these vital signs automatically from Bedside Medical Devices (BDMI), and store them into a temporary storage, then load them into a Hadoop cluster. The session will also cover how the team married this vital signs data in the HDFS (Hadoop File System) with the rest of the EMR data for our Principles Investigators (PI) in our research institute to search for correlations between administered medications, diagnosis, and vital signs readings. The session will describe the reasons behind the design decisions that were made, such as using a Cloud Hadoop cluster versus on-premises while maintaining HIPAA.TRANSCRIPT
Using Hadoop for Vital Signs and EMR data
in Healthcare Research and Patient Care
Mohamed Elmallah, [email protected] @melmallah
Session Plan
• Objectives• CHLA• Speaker• The match• Environment• Why now• Research use case• The challenges• What needs to happen• Takeaways• Q&A
Objectives
• Explain why Healthcare is a perfect domain for Hadoop
• Describe some of the many challenges
• Describe use cases in research and patient care
• Go over lessons learned and next steps
• How Hadoop vendors and Bigdata community can help
This Session will not
• dive into technical details, it will stop at the highlevel architecture
• assume that you are a healthcare expert
• show you a production Hadoop with 40k node
• talk about petabytes of data (just a few TBs)
CHLA - History
• Founded in 1901, oldest children’s hospital in CA
• ~12K inpatient visits / year
• ~320K outpatient visits / year
• ~65K ED visits / year
• ~16K pediatric surgeries / year
CHLA - Clinical
• U.S. News and World Report’s Honor Roll
• Ranked in all 10 pediatric subspecialties
• ~5,000 employees and ~600 medical staff
• 365 active licensed beds, 85% private
• 80+ intensive care beds
CHLA - Clinical
• Affiliated with the Keck School of Medicine, USC
– http://www.chla.org
• The Saban Research Institute, ~100 researchers and physicians (and data scientists :)
– http://www.chla.org/saban
Speaker
• Ex-developer (e.g. Manager) of Enterprise Apps and Architecture team
• 2+ Year with CHLA
• Worked for Cedars Sinai and Kaiser Permanente
• Ex- DBA, Support Engineer, ERP Implementor: Oracle, Qualcomm
Hadoop and Healthcare
• Healthcare is so different
– HealthIT for many years has been lagging – HIPAA: Health Insurance Portability and Accountability Act– PHI: Protected Health Information– Public Cloud: Not there yet– In many technology areas: A few niche players– Some organizations are powered by research and academia
Hadoop and Healthcare
• Healthcare is NOT so different
– Data is growing– HealthIT is trying to save money– There is continued spending in HealthIT– EMR/EDW is not a feasible solution to retain and deliver
information– Care providers are dependent on hosted applications– Care providers are paying more attention to their social
network footprints.– Other great candidate domains for bigdata are lagging too
Environment
• EMR: Cerner Millennium: PowerChart, FirstNet, SurgiNet • Data Mart/Reporting: PowerInsight
• Patient Registration: McKesson Star• DataMart/Dept BI/Reporting: HBI, HPM, SpotFire
• ERP: Peoplesoft Fin/HR/Materials/Contracts
• Bed Management: Teletracking
• Placement/Transfer/Scheduling: Central Logic
Environment
• Integration Engine: eGate (HL7, FTP), P2P
• Content Management: Sharepoint, Kintera/Sphere CMS, maybe Autonomy/OpenText
• Foundation CRM: Blackbaud• Departmental Applications: Radiology, Quality
Improvement, Pathology, Hemonc, etc.
• Enterprise Technologies: AD, SSRS, SSIS, .Net C#, JQuery, ExtJS, HTML5, Oracle DB, SQL Server, IIS, Linux
What is Changing?
• ACA, MU– Patient Portals– Diagnosis-Related Group (classification of cases)
• Mobile (more access, more data)
• EMR system is becoming more open– API to access data
EMR Client-Server Architecture
EMREMR
Backend App Servers
Backend App Servers
XenApp ServersXenApp Servers
Expanding the EMR Architecture
EMREMR
Backend App Servers
Backend App Servers
XenApp ServersXenApp Servers
WSMiddle
-tier Servers
WSMiddle
-tier Servers
CustomMiddle
-tier Servers
CustomMiddle
-tier Servers
What is Changing?
• Cloud-based solutions (SaaS)
• More integration demand with other data sources– BMDI– Lab Outreach– Using non-CHLA data (e.g. NIH - National Institutes of
Health data)
• Increased demand for dashboards, trends, sparkline
Sample NICCU Rounding PageBuilt in-house
Sample Custom Components for Summary Pages
Part of Patient Chart. Built in-house
What are we doing?
• Expanding our in-house development team, not only on middle tier and UI, but data and BI.
• Using consultants and professional services in a smarter manner– Insist on open data access– Insist on open architecture (SOA: Web Services, or at
least direct database access)
• Partner with bigdata vendors (small and large)
NICCU/PICU/CTICU Data Acquisition Use Case
• EMR keeps a few on-demand snapshots through proprietary integration with devices
• Researchers wants continuous access to Vital Signs from:– Patient monitors: Philips MP70 conventional modules (HR,
SPO2, BP, TCOM), Philips MP70 Vuelink– Cerebral/Somatic Oximeters: INVOS– Cerebral functional monitor (CFM): Olymbic Brainz– Respiratory monitors: Respironics NM3, BiCore II– Cardiac monitors: Aesculon and ICON– Ventilators: Servo, AVEA, HiFreq Oscillatory, etc.– Infusion pumps: Medfusion– Dialysis machines: Prisma
NICCU/PICU/CTICU Data Acquisition Use Case
• Collect data (numeric and wave form) from BMDI into a SQL Server DB
• Data has some PHI data
• Data is augmented with metadata (dates, notes, etc.)
• Instead of each vendor connecting directly to devices, we will have a centralized, complete, controlled and in-house repository– Each device has a limited number of ports
Data Acquisition Architecture
Short TermSQL ServerShort TermSQL Server
Web ServicesWeb Services
Trend ViewerTrend Viewer
Data AccessLayer
Data AccessLayer
Live XML
Stream
Live XML
Stream
Hubs + XML Serialization
Service
Hubs + XML Serialization
Service
PlaybackPlayback
Access & AuditingAccess & Auditing
PI
Challenges
• We have a development team, but mainly in .Net Web Development, have been preparing them– Data (modeling, ETL, BI, Analytics) training– Considering Java training
• Getting the buy-in from business side
• Many of the niche healthcare vendors are small, not Hadoop-ready
• The small but successful bigdata vendors are busy, and the big ones are usually expensive
Our Next Steps
• Marry the Vital Signs to the Patient Chart and its Events (e.g. administration of medication), and access one from the other, keeping HIPAA in sight.
• Once clinical/research use case is proven, low hanging fruits in social networking, and operations/finances (claims, payroll, etc.) should be next– Not to reinvent the wheel– Use analytics/algorithms already proven– Partner with other care providers
Our Next Steps
• Expose practical Bigdata to end-users and business stakeholders
• Bigdata is not an IT thing
• Hadoop is an echosystem not just one product
What Needs to Happen
• Healthcare focus– Bigdata vendors need to understand the domain – Repeating the word “HIPAA” many times is not enough
• Fill in a gap
– BI– Archiving– Data Governance– Enterprise Search– Social Networking
• Agile implementations
What Needs to Happen
• HIPAA Ready
• Offer quick start packages– Help Hospitals to teach their HealthIT staff Hadoop– Teach Hadoop/MR to Oracle/.Net Developers– Don’t forget the administrators
Objectives
• Explain why Healthcare is a perfect domain for Hadoop
• Describe some of the many challenges
• Describe use cases in research and patient care
• Go over lessons learned and next steps
• How Hadoop vendors and Bigdata community can help
For more info
• MUCMD: Meaningful Use of Complex Medical Data Conference, August 16-17, 2013 Los Angeles– http://mucmd.org
• VPICU: Virtual Pediatric Intensive Care Unit– http://www.picu.net
Questions?
@melmallah@healthcare4me@bigdata4u
Thank You!