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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
  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”
  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
  4. NETSPECTIVE www.netspective.com 4 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
  5. NETSPECTIVE www.netspective.com 5 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
  6. NETSPECTIVE www.netspective.com 6 Data changes the questions we ask Simple

    visual facts Complex visual facts Complex computable facts
  7. NETSPECTIVE www.netspective.com 7 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
  8. NETSPECTIVE www.netspective.com 9 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
  9. NETSPECTIVE www.netspective.com 10 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
  10. 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
  11. NETSPECTIVE www.netspective.com 12 Predictions for Device Hardware Thick Devices Thin

    Devices Virtual Devices Sensors Only with Built-in Wireless Consumerization of Devices Sensors on mobile phones, platforms
  12. NETSPECTIVE www.netspective.com 13 Predictions for Device Software Software for algorithms

    Software for functionality Software for connectivity Software only Consumerization of Apps
  13. NETSPECTIVE www.netspective.com 14 Predictions for Device Connectivity Stand-alone and monolithic

    Connectivity within own organization Multi-vendor connectivity System of Systems (SoS) Consumerization of IT
  14. NETSPECTIVE www.netspective.com 15 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
  15. NETSPECTIVE www.netspective.com 16 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
  16. NETSPECTIVE www.netspective.com 17 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
  17. NETSPECTIVE www.netspective.com 18 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
  18. NETSPECTIVE www.netspective.com 20 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.
  19. NETSPECTIVE www.netspective.com 21 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
  20. NETSPECTIVE www.netspective.com 22 OSS revolution in manageability Security • Is

    the device authorized? Inventory • Where is the device? Presence • Is a device connected? Teaming • Device grouping
  21. NETSPECTIVE www.netspective.com 23 Key OSS questions Will the FDA accept

    open source in safety-critical systems? Is open source safe enough for medical devices?
  22. NETSPECTIVE www.netspective.com 24 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
  23. NETSPECTIVE www.netspective.com 25 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.
  24. NETSPECTIVE www.netspective.com 26 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
  25. NETSPECTIVE www.netspective.com 27 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