Proper Data Integration can change Medical Science


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This talk was presented at the 2013 Meaningful Use of Complex Medical Data

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Proper Data Integration can change Medical Science

  1. 1. The Myth of Health Data Integration Complexity There’s nothing special about health IT data that justifies complex, expensive, or special technology Presented at MUCMD 2013 By Shahid N. Shah, CEO
  2. 2. This and many of my other presentations are available at @ShahidNShah 2
  3. 3. NETSPECTIVE Who is Shahid? • • • • 20+ years of software engineering and multidiscipline complex IT implementations (Gov., defense, health, finance, insurance) 12+ years of healthcare IT and medical devices experience (blog at 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 nonprofit) Author of Chapter 13, “You’re the CIO of your Own Office” 3
  4. 4. NETSPECTIVE 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, 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 • • • • • EHRs are not the center of the healthcare data ecosystem. 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
  5. 5. NETSPECTIVE Is your tech infrastructure agile? Improve speed of response to new patient/HCP needs Reduce permissionoriented culture Reduce number of Shadow IT systems React faster to regulatory and market changes Reduce compliance-focus in favor of customer focus 5
  6. 6. NETSPECTIVE NEJM believes doctors are trapped It is a widely accepted myth that medicine requires complex, highly specialized information-technology (IT) systems. This myth continues to justify soaring IT costs, burdensome physician workloads, and stagnation in innovation — while doctors become increasingly bound to documentation and communication products that are functionally decades behind those they use in their “civilian” life. New England Journal of Medicine “Escaping the EHR Trap - The Future of Health IT”, June 2012 6
  7. 7. NETSPECTIVE Real world requirement: Reduce heart failure readmissions Allocating scarce resources in real-time to reduce heart failure readmissions: a prospective, controlled study “This study provides preliminary evidence that technology platforms that allow for automated EMR data extraction, case identification and risk stratification may help potentiate the effect of known readmission reduction strategies, in particular those that emphasize intensive and early post-discharge outpatient contact.” 7
  8. 8. NETSPECTIVE Data changes the questions we ask Simple visual facts Complex visual facts Complex computable facts 8
  9. 9. NETSPECTIVE Implications for scientific discovery Assuming permissions-oriented culture that prevents tinkering and “hacking” is obviated  The old way Identify problem Ask questions Collect data Answer questions What Dr. Jim Fackler was asking for: Don’t try to prove what I think I already know, tell me something I don’t know. What Dr. Curtis Kennedy was remarking: Medicine has patterns, there are only three kinds: Don't know the pattern; know the pattern, don't see it, know the pattern and see it Drs. Kennedy & Fackler agreed with past research: Don’t just give me more data, put it into the hands of the patients / parents / caregivers The new way Identify data Generate questions Mine data Answer questions 9
  10. 10. NETSPECTIVE Application focus is biggest mistake Application-focused IT instead of Data-focused IT is causing business problems. Silos of information exist across groups (duplication, little sharing) Clinical Apps Billing Apps Lab Apps Other Apps Healthcare Provider Systems Patient Apps Partner Systems Poor data integration across application bases 10
  11. 11. NETSPECTIVE The Strategy: Modernize Integration Need to get existing applications to share data through modern integration techniques Clinical Apps NCI App Billing Apps Lab Other Apps Apps NEI App Healthcare Provider Systems Patient Apps NHLBI App Partner Systems Master Data Management, Entity Resolution, and Data Integration Improved integration by services that can communicate between applications 11
  12. 12. NETSPECTIVE Confronting Data Integration Myths My EHR will handle everything I need and push data where required Without semantic mapping the aggregated data is not useful I can’t possibly store everything I don’t have to worry about storing certain types of data I only need to store data for a period of time If I don’t understand how to synthesize data now, I’d rather not store it 12
  13. 13. NETSPECTIVE Why health IT systems integrate poorly • • • • • Permissions-oriented culture prevents tinkering and “hacking” We don't support shared identities, single sign on (SSO), and industryneutral authentication and authorization We’re looking for "structured data integration" instead of "practical app integration" in our early project phases We create large monolithic data warehouses instead of small service oriented databases We “push" data everywhere instead of "pulling" it when necessary • • • • • We assume EHRs the center of the universe We accept and reward vendors that don’t care about integration We have “Inside out” architecture, not “Outside in” We're too focused on heavyweight industry-specific formats instead of lightweight or micro formats Data emitted is not tagged using semantic markup, so it's not securable or searchable by default 13
  14. 14. How do we modernize integration?
  15. 15. NETSPECTIVE Don’t assume your EHR will manage your data The EHR can not be the center of the healthcare data ecosystem • Most non-open-source EHR solutions are designed to put data in but not get data out • Never build your data integration strategy with the EHR in the center, create it using the EHR as a first-class citizen Why EHRs are not (yet) disruptive 15
  16. 16. NETSPECTIVE Encourage clinical “tinkering” and “hacking” It’s ok to not know the answer in advance • Clinicians usually go into medicine because they’re problem solvers • Today’s permissionsoriented culture now prevents “playing” with data and discovering solutions 16
  17. 17. NETSPECTIVE Promote “Outside-in” architecture Think about clinical and hospital operations and processes as a collection of business capabilities or services that can be delivered across organizations. 17
  18. 18. NETSPECTIVE Integration improves focus on the real customer Dr. Warren Sandberg suggested he needs help here Inside-out focus IT Personnel Internal business users and HCPs HCP and Staff Evaluators Outside-in focus External HCPs Patients Sophisticated and more agile focus Unsophisticated and less agile focus HCPs = healthcare providers 18
  19. 19. NETSPECTIVE Implement industry-neutral ICAM Implement shared identities, single sign on (SSO), neutral authentication and authorization 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 industryneutral 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 . 19
  20. 20. NETSPECTIVE App-focused integration is better than nothing Structured data dogma gets in the way of faster decision support real solutions Dogma is preventing integration App-centric sharing is possible Many think that we shouldn’t integrate until structured data at detailed machinecomputable 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. 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. • Consider Direct for app-centric connectivity. 20
  21. 21. NETSPECTIVE Pushing data is more expensive than pulling it We focus more on "pushing" versus "pulling" data than is warranted early in projects Old way to architect: “What data can you send me?” (push) Better way to architect: “What data can I publish safely?” (pull) 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. • Implement FHIR or 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. • Consider Direct for connectivity if you can’t get away from ‘push’. 21
  22. 22. NETSPECTIVE Move to service-oriented (de-identifiable) data Don’t assume all your data has to go into a giant data warehouse Old way to architect: Monolithic RDBMS-based data warehouse Better way to architect: Service-oriented databases on RDBMS/NoSQL The centralized clinical data warehouse (CDW) model, where a massive multi-year project creates a monolithic relational database that all analytics will run off was fine when retrospective reporting is what defined analytics. This old architecture won’t work in modern predictive analytics and mobile-centric requirements. • Drive transactional ACID-based data requirements to RDBMS and consider columnstores, document-stores, and network-stores for other kinds of data • Break relationships between data and store lookup, transactional, predictive, scoring, risk strat, trial associated, retrospective, identity, mortality ratios, and other types of data based on their usage criteria not developer convenience • Use translucent encryption and auto-deidentification of data to make it more useful without further processing • Design for decentralized sync’ing of data (e.g. mobile, etc.) not centralized ETL 22
  23. 23. NETSPECTIVE An example of structuring data for analysis Preparing data is important Hard to secure data structures Easier to secure data structures 23
  24. 24. NETSPECTIVE Industry-specific formats aren’t always necessary Reliance on heavyweight industry-specific formats instead of lightweight micro formats is bad HL7 and X.12 aren’t the only formats Consider industry-neutral protocols 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. • • • • 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 Consider semantic data formats like RDF, RDFa, and related family. 24
  25. 25. NETSPECTIVE Tag all app data using semantic markup When data is not tagged using semantic markup, it's not securable or shareable by default Legacy systems trap valuable data Semantic markup and tagging is easy 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. • 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 • Google's recent implementation of its Knowledge Graph is a great example of the utility of this semantic mapping approach. 25
  26. 26. NETSPECTIVE Produce data in search-friendly manner Produce HTML, JavaScript and other data in a security- and integration-friendly approach Proprietary data formats limit findability Search engines are great integrators • 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. • 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. 26
  27. 27. NETSPECTIVE Rely first on open source, then proprietary “Free” is not as important as open source, you should pay for software but require openness Healthcare fears open source Open source can save health IT • 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. • 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. 27
  28. 28. Visit E-mail Follow @ShahidNShah Call 202-713-5409 Thank You