Using Hadoop for Vital Signs and EMR data

in Healthcare Research and Patient Care

Mohamed Elmallah, melmallah@chla.usc.edu @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!