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OSEHRA Summit 2012 Lunch Keynote: Current health IT systems integrate poorly and that's a big opportunity for the OSEHRA community

OSEHRA Summit 2012 Lunch Keynote: Current health IT systems integrate poorly and that's a big opportunity for the OSEHRA community

OSEHRA Summit 2012 Lunch Keynote - The Myth of Health Data Integration Complexity. This is an opinionated look at why current health IT systems integrate poorly and how it’s a big opportunity for the OSEHRA Community.

Background:
* A deluge of healthcare data is being created as we digitize biology, chemistry, and physics.
* Data changes the questions we ask and it can actually democratize and improve the science of medicine, if we let it.
* While cures are the only real miracles of medicine, big data can help solve intractable problems and lead to more cures.
* Healthcare-focused software engineering is going to do more harm than good (industry-neutral is better).

Key takeaways:
* Major opportunity for systems integrators
* Applications come and go, data lives forever. He who owns, integrates, and uses data wins in the end.
* Never leave your data in the hands of an application/system vendor.
* There’s nothing special about health IT data that justifies complex, expensive, or special technology.
* Spend freely on multiple systems and integration-friendly solutions.

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Shahid N. Shah

October 18, 2012
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Transcript

  1. The Myth of Health Data Integration Complexity An opinionated look

    at why current health IT systems integrate poorly and how it’s a big opportunity for the OSEHRA Community By Shahid N. Shah, CEO
  2. NETSPECTIVE www.netspective.com 2 Who is Shahid? • Chairman, OSEHRA Board

    of Advisors • 20+ years of software engineering and multi-discipline complex IT implementations (Gov., defense, health, finance, insurance) • 12+ years of healthcare IT and medical devices experience (blog at http://healthcareguy.com) • 15+ years of technology management experience (government, non-profit, commercial) Author of Chapter 13, “You’re the CIO of your Own Office”
  3. NETSPECTIVE www.netspective.com 3 What’s this talk about? Background • A

    deluge of healthcare data is being created as we digitize biology, chemistry, and physics. • Data changes the questions we ask and it can actually democratize and improve the science of medicine, if we let it. • While cures are the only real miracles of medicine, big data can help solve intractable problems and lead to more cures. • Healthcare-focused software engineering is going to do more harm than good (industry-neutral is better). Key takeaways • Major opportunity for systems integrators • Applications come and go, data lives forever. He who owns, integrates, and uses data wins in the end. • Never leave your data in the hands of an application/system vendor. • There’s nothing special about health IT data that justifies complex, expensive, or special technology. • Spend freely on multiple systems and integration-friendly solutions.
  4. NETSPECTIVE www.netspective.com 4 How OSEHRA makes the market bigger New

    businesses can be created which service OSEHRA code, technologies, etc. and make revenue from said services New system integration business or existing ones can augment their products / services to include OSEHRA capabilities New or existing hosting / datacenter businesses can offer fully hosted OSEHRA capabilities directly to clinicians or even at some point VA/DoD/IHS New revenue centers in existing or new businesses can take common certification criteria and build tools around it for automated testing, documentation preparation, etc. Market generation and economic benefits
  5. The macro environment What’s creating “data deluge”?

  6. NETSPECTIVE www.netspective.com 6 Digitize biology Digitize chemistry Digitize physics Predict

    fundamental behaviors Digitize mathematics Digitize literature Digitize social behavior Predict human behavior We’re digitizing biology Last and past decades This and future decades Gigabytes and petabytes Petabytes and exabytes
  7. NETSPECTIVE www.netspective.com 7 How can data help? Proteomics Emerging •Must

    be continuously collected •Difficult today, easier tomorrow •Super-personalized •Prospective •Predictive Genomics Since 2000s, started at $100k per patient, <$1k soon •Can be collected infrequently •Personalized •Prospective •Potentially predictive •Digital •Family history is easy Phenotypics Since 1980s, pennies per patient •Must be continuously collected •Mostly Retrospective •Useful for population health •Part digital, mostly analog •Family History is hard Economics Since 1970, pennies per patient •Business focused data •Retrospective •Built on fee for service models •Inward looking and not focused on clinical benefits Biosensors Social Interactions
  8. NETSPECTIVE www.netspective.com 8 Data changes the questions we ask Simple

    visual facts Complex visual facts Complex computable facts
  9. NETSPECTIVE www.netspective.com 9 Implications for scientific discovery The old way

    Identify problem Ask questions Collect data Answer questions The new way Identify data Generate questions Mine data Answer questions
  10. NETSPECTIVE www.netspective.com 10 We’re in the integration age Source: Geoffrey

    Raines, MITRE We’re not in an app-driven future but an integration- driven future. He who integrates the best, wins.
  11. Recognizable Data Sources Where is all the data coming from?

  12. NETSPECTIVE www.netspective.com 12 Data is hidden everywhere Clinical trials data

    (failed or successful) Secure Social Patient Relationship Management (PRM) Patient Communications, SMS, IM, E-mail, Voice, and Telehealth Patient Education, Calculators, Widgets, Content Management Blue Button, HL7, X.12, HIEs, EHR, and HealthVault Integration E-commerce, Ads, Subscriptions, and Activity-based Billing Accountable Care, Patient Care Continuity and Coordination Patient Family and Community Engagement Patient Consent, Permissions, and Disclosure Management
  13. NETSPECTIVE www.netspective.com 13 More hidden sources of data Clinical systems

    Consumer and patient health systems Core transaction systems Decision support systems (DSS and CPOE) Electronic medical record (EMR) Managed care systems Medical management systems Materials management systems Clinical data repository Patient relationship management Imaging Integrated medical devices Clinical trials systems Telemedicine systems Workflow technologies Work force enabling technologies
  14. NETSPECTIVE www.netspective.com 14 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
  15. NETSPECTIVE www.netspective.com 15 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
  16. What’s the problem? What are we doing wrong?

  17. NETSPECTIVE www.netspective.com 17 Why you can’t just “buy integration” Myth

    • I only have a few systems to integrate • I know all my data formats • I know where all my data is and most of it is valid • My vendor already knows how all this works and will solve my problems Truth • There are actually hundreds of systems • There are dozens of formats you’re not aware of • Lots of data is missing and data quality is poor • Tons of undocumented databases and sources • Vendors aren’t incentivized to integrate data
  18. NETSPECTIVE www.netspective.com 18 Application focus is biggest mistake Application-focused IT

    instead of Data-focused IT is causing business problems. Healthcare Provider Systems Clinical Apps Patient Apps Billing Apps Lab Apps Other Apps Partner Systems Silos of information exist across groups (duplication, little sharing) Poor data integration across application bases
  19. NETSPECTIVE www.netspective.com 19 NCI App NEI App NHLBI App Healthcare

    Provider Systems Clinical Apps Patient Apps Billing Apps Lab Apps Other Apps Master Data Management, Entity Resolution, and Data Integration Partner Systems Improved integration by services that can communicate between applications The Strategy: Modernize Integration Need to get existing applications to share data through modern integration techniques
  20. NETSPECTIVE www.netspective.com 20 Important needs of non-Gov clinical customers Easy

    to install packages that make it possible to experiment with OSEHRA code RCM integration Patient portal integration Interoperable with existing systems (labs, pharma, etc.) OSEHRA needs to get non-government clinical customers but there are important gaps
  21. NETSPECTIVE www.netspective.com 21 Value-adds to clinical users More functionality Faster

    delivery Better integration Interoperability Free EHR The conceptual ROI for OSEHRA activities
  22. NETSPECTIVE www.netspective.com 22 Important needs of engineering customers Easy to

    install packages that make it possible to experiment with OSEHRA code Common data model Common identity management Platform to build on (APIs, etc.) Ability to build mHealth apps on top of OSEHRA OSEHRA needs to get non-government clinical customers but there are important gaps
  23. How do we modernize integration?

  24. NETSPECTIVE www.netspective.com 24 Why health IT systems integrate poorly Technology

    “Culture” • Permissions-oriented culture prevents tinkering and “hacking” • We don’t let patients drive data decisions. • No scripting or customizing EHRs, lab systems, etc. • Interoperability isn’t required for transactions to be completed (e- commerce) • We have “Inside out” architecture, not “Outside in” Actual Technology • We don't support shared identities, single sign on (SSO), and industry- neutral authentication and authorization • We're too focused on "structured data integration" instead of "practical app integration“ • We focus more on "pushing" versus "pulling" data than is warranted early in projects • We're too focused on heavyweight industry-specific formats instead of lightweight or micro formats
  25. NETSPECTIVE www.netspective.com 25 Process and people consolidation won’t work in

    the future “For decades, businesses typically have been rewarded for consolidation around standard processes and stockpiling assets through people, technology and goods. Companies are discovering they need a new kind of leverage – capability leverage – to mobilize third parties that can add value.” Defining and coordinating interactions across a multitude of organizations is the new way • Outside-in architecture asks you to think about your operations and processes as a collection of business capabilities or services. • Each individual service must be analyzed and packaged to see who can deliver them best. According to Deloitte, “this architectural transition requires new skills from the CIO and the IT organization. CIOs who anticipate and understand the opportunity are likely to become much more effective business partners with other executive leaders.” Promote “Outside-in” architecture The IT department inside your organization cannot possibly do everything you’d like Source: Deloitte “Outside-in Architecture”
  26. NETSPECTIVE www.netspective.com 26 Proprietary identity is hurting us • Most

    health IT systems create their own custom identity, credentialing, and access management (ICAM) in an opaque part of a proprietary database. • We’re waiting for solutions from health IT vendors but free or commercial industry- neutral solutions are much better and future proof. Identity exchange is possible • Follow National Strategy for Trusted Identities in Cyberspace (NSTIC) • Use open identity exchange protocols such as SAML, OpenID, and Oauth • Use open roles and permissions-management protocols, such as XACML • Consider open source tools such as OpenAM, Apache Directory, OpenLDAP , Shibboleth, or commercial vendors. • Externalize attribute-based access control (ABAC) and role-based access control (RBAC) from clinical systems into enterprise systems like Active Directory or LDAP . Implement industry-neutral ICAM Implement shared identities, single sign on (SSO), neutral authentication and authorization
  27. NETSPECTIVE www.netspective.com 27 Dogma is preventing integration Many think that

    we shouldn’t integrate until structured data at detailed machine- computable levels is available. The thinking is that because mistakes can be made with semi-structured or hard to map data, we should rely on paper, make users live with missing data, or just make educated guesses instead. App-centric sharing is possible Instead of waiting for HL7 or other structured data about patients, we can use simple techniques like HTML widgets to share "snippets" of our apps. • Allow applications immediate access to portions of data they don't already manage. • Widgets are portions of apps that can be embedded or "mashed up" in other apps without tight coupling. • Blue Button has demonstrated the power of app integration versus structured data integration. It provides immediate benefit to users while the data geeks figure out what they need for analytics, computations, etc. App-focused integration is better than nothing Structured data dogma gets in the way of faster decision support real solutions
  28. NETSPECTIVE www.netspective.com 28 Old way to architect: “What data can

    you send me?” (push) The "push" model, where the system that contains the data is responsible for sending the data to all those that are interested (or to some central provider, such as a health information exchange or HL7 router) shouldn’t be the only model used for data integration. Better way to architect: “What data can I publish safely?” (pull) • Implement syndicated Atom-like feeds (which could contain HL7 or other formats). • Data holders should allow secure authenticated subscriptions to their data and not worry about direct coupling with other apps. • Consider the Open Data Protocol (oData). • Enable auditing of protected health information by logging data transfers through use of syslog and other reliable methods. • Enable proper access control rules expressed in standards like XACML. Pushing data is more expensive than pulling it We focus more on "pushing" versus "pulling" data than is warranted early in projects
  29. NETSPECTIVE www.netspective.com 29 HL7 and X.12 aren’t the only formats

    The general assumption is that formats like HL7, CCD, and X.12 are the only ways to do data integration in healthcare but of course that’s not quite true. Microsoft Excel & Access, Google Docs, etc. don’t have live access to our data in transactional systems such as EHRs. Consider industry-neutral protocols • Consider identity exchange protocols like SAML for integration of user profile data and even for exchange of patient demographics and related profile information. • Consider iCalendar/ICS publishing and subscribing for schedule data. • Consider microformats like FOAF and similar formats from schema.org. • Consider semantic data formats like RDF, RDFa, and related family. Industry-specific formats aren’t always necessary Reliance on heavyweight industry-specific formats instead of lightweight micro formats is bad
  30. NETSPECTIVE www.netspective.com 30 Legacy systems trap valuable data In many

    existing contracts, the vendors of systems that house the data also ‘own’ the data and it can’t be easily liberated because the vendors of the systems actively prevent it from being shared or are just too busy to liberate the data. Semantic markup and tagging is easy • One easy way to create semantically meaningful and easier to share and secure patient data is to have all HTML tags be generated with companion RDFa or HTML5 Data Attributes using industry-neutral schemas and microformats similar to the ones defined at Schema.org. • Google's recent implementation of its Knowledge Graph is a great example of the utility of this semantic mapping approach. Tag all app data using semantic markup When data is not tagged using semantic markup, it's not securable or shareable by default
  31. NETSPECTIVE www.netspective.com 31 Proprietary data formats limit findability • Legacy

    applications only present through text or windowed interfaces that can be “scraped”. • Web-based applications present HTML, JavaScript, images, and other assets but aren’t search engine friendly. Search engines are great integrators • Most users need access to information trapped in existing applications but sometimes they don’t need must more than access that a search engine could easily provide. • Assume that all pages in an application, especial web applications, will be “ingested” by a securable, protectable, search engine that can act as the first method of integration. Produce data in search-friendly manner Produce HTML, JavaScript and other data in a security- and integration-friendly approach
  32. NETSPECTIVE www.netspective.com 32 Healthcare fears open source • Only the

    government spends more per user on antiquated software than we do in healthcare. • There is a general fear that open source means unsupported software or lower quality solutions or unwanted security breaches. Open source can save health IT • Other industries save billions by using open source. • Commercial vendors give better pricing, service, and support when they know they are competing with open source. • Open source is sometimes more secure, higher quality, and better supported than commercial equivalents. • Don’t dismiss open source, consider it the default choice and select commercial alternatives when they are known to be better. Rely first on open source, then proprietary “Free” is not as important as open source, you should pay for software but require openness
  33. www.netspective.com 33 Modern Microapps and Services Approach (Sample) Identity Manager

    LDAP Entity Services RDBMS Domain Services RDBMS Analytics SQL/Cube RDBMS Limited FK Constraints oData SQLV SQLV oData SQLV oAuth SAML oData LDIF Domain Services Widgets Entity Services CMS oData Micro Apps No Direct Table Access Separate Schemas No FK Constraints Bootstrap AngularJS Bootstrap AngularJS Backplane Reporting Apps Third Party Bootstrap Backplane RDFa HTML5 DA RDFa HTML5 Data Attrs RDFa HTML5 Data Attrs ETL Bootstrap Backplane Rich client only or tiny server frameworks (Mojo, Rack, etc.) XACML oData Search Service ElasticSearch iCal syslog Log/Monitor Service CalDAV Service Rules Service Doc/Blob Service oData Browser Accessible XMPP Service
  34. NETSPECTIVE www.netspective.com 34 Primary challenges • Tooling strategy must be

    comprehensive. What hardware and software tools are available to non-technical personnel to encourage sharing? • Formats matter. Are you using entity resolution, master data and metadata schemas, documenting your data formats, and access protocols? • Incentivize data sharing. What are the rewards for sharing or penalties for not sharing healthcare data? • Distribute costs. How are you going to allow data users to contribute to the storage, archiving, analysis, and management costs? • Determine utilization. What metrics will you use determine what’s working and what’s not?
  35. Thank You Visit http://www.netspective.com http://www.healthcareguy.com E-mail shahid.shah@netspective.com Follow @ShahidNShah Call

    202-713-5409