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Building safety-critical medical device platforms and Meaningful Use EHR gateways

Building safety-critical medical device platforms and Meaningful Use EHR gateways

This is an in depth technical presentation delivered at OSCon 2012 on how to define, design, and build modern safety-critical medical device platforms and Meaningful Use compliant EHR gateways. The talk starts with a quick background on comparative effective research (CER) and patient-centered outcomes research (PCOR) and the kinds of data the government is looking to leverage in the future to help reduce healthcare costs and improve health outcomes. After defining why data is important, the workshop will cover the different techniques for collecting medical data – such as directly from a patient, through healthcare professionals, through labs, and finally through medical devices; the presentation will cover which kinds of data are easy to collect and what are more difficult and how technical challenges to collection can be overcome.

After covering the data collection area the workshop will dive deep into a modern medical device platform architecture which the speaker calls “The Ultimate Medical Device Connectivity Architecture” – providing an in-depth overview and answering questions around architecture, specifications, and design or modern (connected) medical devices.

Presentations of open source software and other inexpensive design techniques for implementing connected architectures will be covered. Finally, the talk will cover details about medical device gateways, what new Meaningful Use rules might require when connecting EHRs to gateways, and how to design and architect gateways that can stand the test of time and be interoperable over the long haul.

Shahid N. Shah

July 18, 2012
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  1. Building open source safety-critical
    medical device platforms and
    Meaningful Use EHR gateways
    Inherent connectivity creates significant
    opportunities in medical science

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  2. NETSPECTIVE
    www.netspective.com 2
    Who is Shahid?
    • 20+ years of software engineering and
    multi-site healthcare system deployment
    experience
    • 12+ years of healthcare IT and medical
    devices experience (blog at
    http://healthcareguy.com)
    • 15+ years of technology management
    experience (government, non-profit,
    commercial)
    • 10+ years as architect, engineer, and
    implementation manager on various EMR
    and EHR initiatives (commercial and non-
    profit)
    Author of Chapter 13, “You’re
    the CIO of your Own Office”

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  3. NETSPECTIVE
    www.netspective.com 3
    What’s this talk about?
    Health IT / MedTech Landscape
    • Data has potential to solve
    some hard healthcare
    problems and change how
    medical science is done.
    • The government is paying for
    the collection of clinical data
    (Meaningful Use or “MU”).
    • All the existing MU incentives
    promote the wrong kinds of
    data collection: unreliable,
    slow, and error prone.
    Key Takeaways
    • Medical devices are the best
    sources of quantifiable,
    analyzable, and reportable
    clinical data.
    • New devices must be
    designed and deployed to
    support inherent connectivity.
    • OSS is ideal for next
    generation and innovative
    medical devices and
    gateways

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  4. NETSPECTIVE
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    What if we had access to all this data?
    Source: Jan Whittenber, Philips Medical Systems
    • Cardiac output
    monitors
    • Defibrillators
    • Fetal monitors
    • Electrocardiographs
    • Infant incubators
    • Infusion pumps
    • Intelligent medical
    device hubs
    • Interactive infusion
    pumps
    • MRI machines
    • X-Ray machines
    • Physiologic monitors
    • Ventilators
    • Vital signs monitors

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  5. NETSPECTIVE
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    What problems can data help solve?
    Cost per patient per
    procedure / treatment
    going up but without
    ability to explain why
    Cost for same
    procedure / treatment
    plan highly variable
    across localities
    Unable to compare
    drug efficacy across
    patient populations
    Unable to compare
    health treatment
    effectiveness across
    patients
    Variability in fees and
    treatments promotes
    fraud
    Lack of visibility of
    entire patient record
    causes medical errors

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  6. NETSPECTIVE
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    Data changes the questions we ask
    Simple visual facts Complex visual facts Complex computable
    facts

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  7. NETSPECTIVE
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    Data can change medical science
    The old way
    Identify problem
    Ask questions
    Collect data
    Answer questions
    The new way
    Identify data
    Generate questions
    Mine data
    Answer questions

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  8. NETSPECTIVE
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    Evidence-based medicine is our goal
    Eminence
    • Trust me
    Evidence
    • Prove it

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  9. NETSPECTIVE
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    Types of medical data we care about
    Proteome is our set
    of proteins
    expressed by our
    genome and
    changes regularly
    over time
    Proteomics is the
    study of the
    proteome
    Proteome
    Genotype is the
    entirety of our
    hereditary
    information (DNA,
    RNA, etc.)
    Genetics is the
    study of the
    genome
    Genome
    Phenotype is a
    composite of our
    observable
    characteristics or
    traits
    This is what we’ve
    been studying for
    centuries
    Phenome

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  10. NETSPECTIVE
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    Unstructured patient data sources
    Patient Health
    Professional
    Labs &
    Diagnostics
    Medical Devices Biomarkers /
    Genetics
    Source Self reported by
    patient
    Observations by
    HCP
    Computed from
    specimens
    Computed real-
    time from patient
    Computed from
    specimens
    Errors High Medium Low
    Time Slow Slow Medium
    Reliability Low Medium High
    Data size Megabytes Megabytes Megabytes
    Data type PDFs, images PDFs, images PDFs, images
    Availability Common Common Common Uncommon Uncommon

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  11. NETSPECTIVE
    www.netspective.com 11
    Structured patient data sources
    Patient Health
    Professional
    Labs &
    Diagnostics
    Medical Devices Biomarkers /
    Genetics
    Source Self reported by
    patient
    Observations by
    HCP
    Specimens Real-time from
    patient
    Specimens
    Errors High Medium Low Low Low
    Time Slow Slow Medium Fast Slow
    Reliability Low Medium High High High
    Discrete size Kilobytes Kilobytes Kilobytes Megabytes Gigabytes
    Streaming size Gigabytes Gigabytes
    Availability Uncommon Common Somewhat
    Common
    Uncommon Uncommon

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  12. NETSPECTIVE
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    Predictions for Device Hardware
    Thick Devices Thin Devices
    Virtual
    Devices
    Sensors Only
    with Built-in
    Wireless
    Consumerization of Devices
    Sensors on
    mobile
    phones,
    platforms

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  13. NETSPECTIVE
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    Predictions for Device Software
    Software for
    algorithms
    Software for
    functionality
    Software for
    connectivity
    Software
    only
    Consumerization of Apps

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  14. NETSPECTIVE
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    Predictions for Device Connectivity
    Stand-alone
    and
    monolithic
    Connectivity
    within own
    organization
    Multi-vendor
    connectivity
    System of
    Systems
    (SoS)
    Consumerization of IT

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  15. NETSPECTIVE
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    Predictions for Gateways
    Single-purpose
    devices
    standalone
    Multi-purpose
    standalone
    Multi-purpose
    with
    documentation
    connectivity
    Multi-purpose
    with cooperating
    connectivity
    Multi-purpose
    with analytical
    connectivity
    Changes in Practice Models

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  16. NETSPECTIVE
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    Predictions for Self-Management
    Physicians
    manage paper
    “charts”
    independently
    Physicians and
    Hospitals
    manage paper
    charts together
    Electronic Health
    Records (EHRs)
    manage data in
    systems
    Health
    Information
    Exchange allow
    coordination
    Patients
    manage their
    own data
    The Patient is in charge

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  17. NETSPECTIVE
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    Implications
    Make sure the
    patient is in the
    middle
    Move from
    hardware to
    software focus
    Move to
    algorithms and
    analytics
    Understand
    system of
    systems (SoS)
    Plan for
    integration and
    coordination
    Start building
    simulators

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  18. NETSPECTIVE
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    OSS revolution in device design
    Device Components 3rd Party Plugins
    App
    #1
    App
    #2
    Security and Management Layer
    Device OS
    (QNX, Linux, Windows)
    Sensors Storage Display Plugins
    Web Server, IM Client
    Connectivity Layer (DDS, HTTP, XMPP)
    • Presence
    • Messaging
    • Registration
    • JDBC, Query
    Plugin Container
    Event Architecture
    Location
    Aware
    1 2
    3
    4
    5
    6
    7

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  19. NETSPECTIVE
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    OSS revolution in device capabilities
    Most obvious benefit Least attention
    Most promising
    capability

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  20. NETSPECTIVE
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    OSS revolution in Gateways
    Corporate Gateway (ESB)
    Service
    DB
    Management
    Services
    Security
    Firewall
    HTTPS, REST, SOAP
    SFTP, SCP, HL7, X.12
    SMTP, XMPP, DDS
    HTTPS, SOAP, REST, HTTP
    SFTP, SCP, HL7, X.12
    SMTP, XMPP, DDS
    Customers & Partners
    Apps MQs Services
    Apps Services
    Corporate Cloud (Data Center)
    Development
    App
    DB
    Central
    DB
    Registry
    Remote
    Facilities
    VPN
    NOTE: Initial design is for a non-federated
    backbone. If performance or security
    demands require it, a federated solution will
    be deployed.

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  21. NETSPECTIVE
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    OSS revolution in integration
    Cloud
    Services
    Management
    Dashboards
    Data Transformation (ESB, HL7)
    Device Gateway
    (DDS, XMPP, ESB)
    Enterprise
    Data
    Inventory
    Cross Device
    App Workflows
    Alarm
    Notifications
    Patient Context
    Monitoring
    Device
    Teaming
    Device
    Management
    Report
    Generation
    HIT
    Integration
    Remote
    Surveillance
    Device
    Data
    SSL VPN
    Patient
    Self-Management
    Platforms

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  22. NETSPECTIVE
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    OSS revolution in manageability
    Security
    • Is the device
    authorized?
    Inventory
    • Where is the device?
    Presence
    • Is a device connected?
    Teaming
    • Device grouping

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  23. NETSPECTIVE
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    Key OSS questions
    Will the FDA accept
    open source in
    safety-critical
    systems?
    Is open source safe
    enough for medical
    devices?

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  24. NETSPECTIVE
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    Simple answers
    Will the FDA accept
    OSS in safety-
    critical systems?
    Is OSS safe enough
    for medical
    devices?
    Yes Yes
    but you must prove it

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  25. NETSPECTIVE
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    It’s not as hard as we think…
    • Modern real-time operating systems (open
    source and commercial) are reliable for safety-
    critical medical-grade requirements.
    • Open standards such as TCP/IP
    , DDS, HTTP
    , and
    XMPP can pull vendors out of the 1980’s and
    into the 1990’s. 
    • Open source and open standards that promote
    enterprise IT connectivity can pull vendors into
    the 2010’s and beyond.

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  26. NETSPECTIVE
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    But it’s not easy either…we need
    Risk
    Assessments
    Hazard Analysis
    Design for
    Testability
    Design for
    Simulations
    Documentation Traceability
    Mathematical
    Proofs
    Determinism
    Instrumentation
    Theoretical
    foundations

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  27. NETSPECTIVE
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    OSS / open standards applicability
    Project / Standard Subject area D G Comments
    Linux or Android Operating system   Various distributions
    OMG DDS (data distribution
    service)
    Publish and subscribe
    messaging
      Open standard with open source
    implementations
    AppWeb, Apache Web/app server  
    OpenTSDB Time series database  Open source project
    Mirth HL7 messaging engine  Built on Mule ESB
    Alembic Aurion HIE, message exchange  Successor to CONNECT
    HTML5, XMPP
    , JSON Various areas   Don’t reinvent the wheel
    SAML, XACML Security and privacy  
    DynObj, OSGi, JPF Plugin frameworks   Build for extensibility

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  28. Conclusion and Questions
    Thank you
    @ShahidNShah
    [email protected]
    www.HealthcareGuy.com

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