Service oriented architecture (SOA) deserves service oriented data

Centralized, monolithic databases primarily built using relational approaches have ruled for decades; they’ve given us tremendous advances such as vertically scaled business-critical transactional systems and web applications. The next generation of microapps, microservices, and web widgets demand a scale that vertical scale application-centric relational databases are having difficulty with so we need to move to a more service-oriented database approach in which even small services like those that service patients in a patient portal or specific modules of EHRs can and should have their own databases.

This talk encourages the idea of service-focused databases and how they differ from application-centric databases; using this new approach allows faster delivery of applications, less coupling, and better scalability. Healthcare and biomedical databases are notoriously complex and no single database technology can serve its needs so we need a more service-oriented approach to database design.

You’ll learn how to choose the right database technology for each service, how to model service-oriented databases differently than application-oriented ones, and how to keep service databases running smoothly.

Transcript

1. Service Oriented Architecture Deserves Service Oriented Data Monolithic databases are just as bad as monolithic applications - how can data make a difference? By Shahid N. Shah, CEO
2. NETSPECTIVE www.netspective.com 3 Who is Shahid? • 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) • 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. www.netspective.com 4 When does data matter? Only when we use it.
4. www.netspective.com 5 When will we use the data? When we can trust it. When we can access it.
5. www.netspective.com 6 When will we trust the data? When it doesn’t “suck”. 
6. www.netspective.com 7 How do we know data doesn’t “suck”? When it’s “actionable” – or probably when we can use it to make decisions based on it (e.g. for jobs to be done, workflow, etc.).
7. www.netspective.com 8 Can’t I just wait to use data until it doesn’t suck? Nope.
8. www.netspective.com 9 What are we supposed to do? Treat data like code. Fix broken windows.
9. www.netspective.com 10 Unused data never gets better. Iterate your way to better data by forcing its use.
10. NETSPECTIVE www.netspective.com 11 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
11. NETSPECTIVE www.netspective.com 12 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
12. NETSPECTIVE www.netspective.com 13 Real world requirement: Reduce heart failure readmissions Allocating scarce resources in real-time to reduce heart failure readmissions: a prospective, controlled study http://qualitysafety.bmj.com/content/early/2013/07/31/bmjqs-2013-001901.full “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.”
13. NETSPECTIVE www.netspective.com 14 The business needs • Quality and performance metrics • Patient stratification • Care coordination • Population management • Surveys and other direct- from-patient data collection • Evidence-based surveillance The technology strategy • Aggregated patient registries • Data warehouse / repository • Rules engines • Complex event processing (CEP) • Expert systems • Reporting tools • Dashboarding engines • Remote monitoring • Social engagement portal for patient/family Tech required for move from FFS to ACOs Integrated and aggregated data is the only way to get to ACOs and PCMHs
14. NETSPECTIVE www.netspective.com 15 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 including minimal meta data.
15. NETSPECTIVE www.netspective.com 16 Common approach, low data interop Application A Data Functionality Presentation Feature Y Feature X Application B Data Functionality Presentation Feature Y Feature X Feature Z Copy features and enhance (everything is separate) Application A Data Functionality Presentation Feature Z Feature X Application B Data Functionality Presentation Feature Y Feature X Feature Z Connect to directly to existing data, but copy features and enhance
16. NETSPECTIVE www.netspective.com 17 Services Sophisticated, better data interop Application A Data Functionality Presentation Feature Y Feature X Application B Data Functionality Presentation Feature Y Feature X Feature Z Create API between applications, integrate data, create new data Application A Data Functionality Presentation Feature Z Feature X Application B Data Functionality Presentation Feature Y Feature X Feature Z Create common services and have all applications use them REST SOAP, RMI SOA APIs WOA
17. NETSPECTIVE www.netspective.com 18 What’s being offered to users What users really want What users want vs. what they’re offered Data visualization requires integration and aggregation and then homogenization
18. NETSPECTIVE www.netspective.com 19 The myth of mobility in healthcare Sexy but wrong: Device-centric closed systems Dull but right: Workflow-centric open solutions
19. NETSPECTIVE www.netspective.com 20 The myth of med device data interop Device Serial Converter USB Converter Concentrator Local Network Gateway to EHR Cloud EHR DDS MQTT REST SOAP AMQP XMPP WCTP SNMP SMTP MLLP
20. Treat data as code Fix broken windows by using service oriented data
21. NETSPECTIVE www.netspective.com 22 Architecture transitions Mainframes Client/Server Web 1.0 Service-oriented Architecture (SOA) Web 2.0 & APIs Web-oriented Architecture (WOA) Event-driven Architecture (EDA) Data-driven Architecture (DDA) Prevalent healthcare industry architectures EDI HL7 X.12 MLLP DDS MQTT SOAP AMQP XMPP WCTP SNMP REST SMTP MLLP
22. NETSPECTIVE www.netspective.com 23 Data attributes fix broken windows Provenance / Source Ownership Steward Units of Measure Location Device Confidence / Probability Subject area / Classification Confidentiality Privacy Creation User / Org Transformed? Analyzed? Interpreted? Quality Metrics Curated? Revisions? Combinable / Aggregatable?
23. NETSPECTIVE www.netspective.com 24 Monolithic Apps Approach Blob Tables Browser Modules Themes Workflow Server Pages Drupal CMS Custom App Models Views Monolithic MVC Controllers Application Server (AS) RDBMS Server Workstation Domain Tables Data Tables User Tables • Custom IAM • Data only available to AS • Lots of FK constraints couple tables • All views, controllers, models maintained on the server side • All security and data translation done on the server and sent to the client
24. NETSPECTIVE www.netspective.com 25 Well intentioned SOA Blob Tables Browser Support API Workflow Pages Service 1 Service 2 Support Widgets Service 3 Controllers Application Server (AS) RDBMS Server Workstation Domain Tables Data Tables User Tables
25. www.netspective.com 26 Source: http://www.sun.com/products/soa/benefits.jsp
26. www.netspective.com 27 Modern Microapps and Services Approach Identity Manager LDAP Patient Services RDBMS Domain Services NoSQL Analytics SQL/Cube RDBMS Limited FK Constraints oData JSON oData oData SQLV oAuth SAML oData LDIF Domain Services Widgets Patient Services Dashboard 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 Device Services DDS
27. NETSPECTIVE www.netspective.com 28 Old way to architect: Monolithic RDBMS-based data warehouse 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. Better way to architect: Service-oriented databases on RDBMS/NoSQL • Drive transactional ACID-based data requirements to RDBMS and consider column- stores, 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-de- identification of data to make it more useful without further processing • Design for decentralized sync’ing of data (e.g. mobile, etc.) not centralized ETL Move to service-oriented (de-identifiable) data Don’t assume all your data has to go into a giant data warehouse
28. NETSPECTIVE www.netspective.com 29 Hard to secure data structures Easier to secure data structures An example of structuring data for analysis Preparing data is important http://www.ibm.com/developerworks/data/library/techarticle/dm-ind-ehr/
29. NETSPECTIVE www.netspective.com 30 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. 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 31 • 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 Don’t assume your EHR will manage your data The EHR can not be the center of the healthcare data ecosystem Why EHRs are not (yet) disruptive http://www.christenseninstitute.org/why-ehrs-are-not-yet-disruptive/
31. NETSPECTIVE www.netspective.com 32 • Clinicians usually go into medicine because they’re problem solvers • Today’s permissions- oriented culture now prevents “playing” with data and discovering solutions Encourage clinical “tinkering” and “hacking” It’s ok to not know the answer in advance
32. NETSPECTIVE www.netspective.com 33 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.
33. NETSPECTIVE www.netspective.com 34 Patients External HCPs HCP and Staff Evaluators Internal business users and HCPs IT Personnel Focus on the real customer Unsophisticated and less agile data focus Sophisticated and more agile data focus Inside-out focus Outside-in focus HCPs = healthcare providers
34. NETSPECTIVE www.netspective.com 35 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
35. NETSPECTIVE www.netspective.com 36 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 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’. Pushing data is more expensive than pulling it We focus more on "pushing" versus "pulling" data than is warranted early in projects
36. NETSPECTIVE www.netspective.com 37 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
37. NETSPECTIVE www.netspective.com 38 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
38. NETSPECTIVE www.netspective.com 39 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
39. Thank You Visit http://www.netspective.com http://www.healthcareguy.com E-mail shahid.shah@netspective.com Follow @ShahidNShah Call 202-713-5409
40. NETSPECTIVE www.netspective.com 41 Abstract Centralized, monolithic databases primarily built using relational approaches have ruled for decades; they’ve given us tremendous advances such as vertically scaled business-critical transactional systems and web applications. The next generation of microapps, microservices, and web widgets demand a scale that vertical scale application-centric relational databases are having difficulty with so we need to move to a more service-oriented database approach in which even small services like those that service patients in a patient portal or specific modules of EHRs can and should have their own databases. This talk will discuss the idea of service-focused databases and how they differ from application-centric databases; using this new approach allows faster delivery of applications, less coupling, and better scalability. Healthcare and biomedical databases are notoriously complex and no single database technology can serve its needs so we need a more service-oriented approach to database design. You’ll learn how to choose the right database technology for each service, how to model service-oriented databases differently than application-oriented ones, and how to keep service databases running smoothly. Service Oriented Architecture Requires Service Oriented Data