OSEHRA is a Great Business Opportunity, OSEHRA Summit 2014, Shahid Sha

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Presented at the OSEHRA Summit 2014, this talk focused on: * OSEHRA is major business opportunity for ISVs and systems integrators * Open source software and associated business models can satisfy most needs. * There’s nothing special about health IT data that justifies complex, expensive, or special technology.

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OSEHRA is a great business opportunity for health IT vendors and system integrators:

OSEHRA is a great business opportunity for health IT vendors and s ystem integrators 3 rd Annual OSEHRA Summit Shahid N. Shah Chairman of OSEHRA Advisory Board

Who is Shahid?:

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”

What’s this talk about?:

What’s this talk about? Background Is disruptive innovation in healthcare possible ? What does innovation in healthcare mean and how do you help customers make it happen? EHRs are not the center of the healthcare data ecosystem . Key takeaways OSEHRA is major business opportunity for ISVs and systems integrators OSS can satisfy most needs. There’s nothing special about health IT data that justifies complex, expensive, or special technology .

VA, VHA, VistA, and OSEHRA:

VA, VHA, VistA , and OSEHRA Top-notch pedigree and a well funded buyer of innovation VHA OSEHRA Community VistA EHR Code Data 1 Facility 1 Facility 2 … Data 2 … OSEHRA Core IV&V (Test, Docs) Certify OSEHRA Add-ons Contributed Add-ons Contributed Core OSEHRA Deployment Contributed Tests/Docs Convergence, Refactoring 2011 2013 Free or Commercial 2013 Commercial Deployments VA FY2012 IT Spend: $3.1 B Innovation Coordination Delivery

How OSEHRA makes the market bigger:

How OSEHRA makes the market bigger Market generation and economic benefits

How OSEHRA makes the market bigger:

How OSEHRA makes the market bigger Market generation and economic benefits

What does “disrupting healthcare” mean?:

What does “disrupting healthcare” mean? This is $1 Trillion and the Healthcare Market is about $3 Trillion This is $1 Billion

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No, your innovation will not disrupt healthcare. I promise. The good news is that doesn’t have to.

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No, your big data or mobile ideas will not disrupt healthcare. But if you can use them to add or extract value from the existing system, you’ll do just fine.

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No, your EHR/PHR or app will not be used by enough doctors or patients to disrupt healthcare. But if you can get even a fraction of them to use your software, you’ll do just fine.

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No, your innovation will not be accepted by permissions-oriented institutions. Find customers with a problem-solving culture willing to accept risks and reward failures.

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No, your innovation will not be easily integrated into regulated device-focused clinical workflows. Incumbent vendors will not entertain the potential of new legal liabilities without someone to share it with or new competition without direct compensation.

What I mean by “actionable innovation”:

You have made the job of identifying, diagnosing, treating, or curing diseases faster, better, or cheaper for clinicians through the use of information technology (IT ) or business models. You have made the job of self-diagnosing, self-treating, or preventing diseases and improving overall wellness of patients through the use of new incentives, business models, or IT. What I mean by “actionable innovation” You can help your customers achieve practical, relevant, actionable solutions

The macro environment:

The macro environment

Shift from Fees for Service (FFS) to Value (FFV):

Shift from Fees for Service (FFS) to Value (FFV) The Shift The clinical model is shifting away from treatment of chronic conditions and focusing more on prevention, wellness, obesity intervention, behavior and lifestyle modification . Implications Clinical operations are shifting to hospital and physician ‘centered’ services that will rely heavily on health information technologies to monitor, coordinate, and manage care . Successful Transition in Care resulting in Reduced Hospital Readmission Rates Proactive population management Patient engagement and collaboration Disease prevention through wellness and obesity management Chronic disease management Care coordination and collaboration Metrics and analytics

The realities of patient populations:

The realities of patient populations Obesity Management Wellness Management Assessment – HRA Stratification Dietary Physical Activity Physician Coordination Social Network Behavior Modification Education Health Promotions Healthy Lifestyle Choices Health Risk Assessment Diabetes COPD CHF Stratification & Enrollment Disease Management Care Coordination MD Pay-for-Performance Patient Coaching Physicians Office Hospital Other sites Pharmacology Catastrophic Case Management Utilization Management Care Coordination Co-morbidities Well Patient At Risk Chronic Care Acute Treatment Prevention Management 26 % of Population 4 % of Medical Costs 35 % of Population 22 % of Medical Costs 35 % of Population 37 % of Medical Costs 4% of Population 36 % of Medical Costs Source: Amir Jafri, PrescribeWell

How Digital Health helps in shift:

How Digital Health helps in shift

How to best identify your customers:

How to best identify your customers Help them stay away from market segmentation, focus on identifying PBU particpants Identifying your customers will depend on helping your customers identify theirs

Patient Collaboration Maturity Model:

Patient Collaboration Maturity Model Choosing a single EHR vendor as your platform for connected care won’t work beyond integrated care scenarios. EHRs are Useful Here EHRs are insufficient by themselves

How will your customers get paid for innovation?:

How will your customers get paid for innovation ? If you haven’t figured it out for them, customers will not figure it out for themselves

We’re digitizing biology:

We’re digitizing biology Last and past decades This and future decades Gigabytes and petabytes Petabytes and exabytes

Data is getting more sophisticated:

Data is getting more sophisticated Try to use existing data to create new diagnostics or therapeutic solutions Biosensors Social Interactions

Healthcare industry / market trends:

Healthcare industry / market t rends Major market and regulatory trends that are causing customers and competitors to shift You must learn and be able to talk to customers about all these terms

Implications of healthcare trends:

Implications of healthcare trends DATA Evidence Based Medicine Comparative Effectiveness Software Regulated IT and Systems Integration Services

The new world order:

The new world order

We’re in the integration age:

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.

What’s the problem?:

What’s the problem? What are we doing wrong when it comes to health IT applications?

Why you can’t just “buy integration”:

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

Application focus is biggest mistake:

Application focus is biggest mistake Application-focused IT instead of Data-focused IT is causing business problems.

The Strategy: Modernize Integration:

The Strategy: Modernize Integration Need to get existing applications to share data through modern integration techniques

Important needs of non-Gov clinical customers:

Important needs of non- Gov clinical customers OSEHRA needs to get non-government clinical customers but there are important gaps

Value-adds to clinical users:

Value-adds to clinical users The conceptual ROI for OSEHRA activities

Important needs of engineering customers:

Important needs of engineering customers OSEHRA needs to get non-government clinical customers but there are important gaps

Needed: Reimagined User Interactions:

What’s being offered to users What users really want Needed: Reimagined User Interactions Data visualization requires integration and aggregation

Needed: Self-service applications:

Needed: Self-service applications

Needed: diagnostic quality mHealth:

Needed: diagnostic quality mHealth

Needed: predictive analytics:

Needed: predictive analytics

Needed: care team involvement:

Needed: care team involvement HEALTHCARE PROVIDER PATIENT/ CONSUMER HOSPITAL FAMILY CAREGIVER ALTERNATE SITE OF CARE Care Team CALL CENTERS AND REMOTE SUPPORT

Needed: automated diagnostics:

Needed: automated diagnostics

Modern Microapps and Services Approach (Sample):

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

How do we modernize integration?:

How do we modernize integration?

Why health IT systems integrate poorly:

Why health IT systems integrate poorly Permissions-oriented culture prevents tinkering and “hacking” We don't support shared identities, single sign on (SSO), and industry-neutral 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

Don’t assume your EHR will manage your data:

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/ HITECH and MU have created false demand and unwarranted importance to EHRs

Encourage clinical “tinkering” and “hacking”:

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 Dr. Wetzel said medicine is inherently experimental

Promote “Outside-in” architecture:

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.

Integration improves focus on the real customer:

Integration improves focus on the real customer Unsophisticated and less agile focus Sophisticated and more agile focus Inside-out focus Outside-in focus HCPs = healthcare providers

Implement industry-neutral ICAM:

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

App-focused integration is better than nothing:

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 . Consider Direct for app-centric connectivity. App-focused integration is better than nothing Structured data dogma gets in the way of faster decision support real solutions

Pushing data is more expensive than pulling it:

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

Move to service-oriented (de-identifiable) data:

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

An example of structuring data for analysis:

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/

Industry-specific formats aren’t always necessary:

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

Tag all app data using semantic markup:

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

Produce data in search-friendly manner:

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

Rely first on open source, then proprietary:

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

Modern Microapps and Services Approach (Sample):

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

Primary challenges:

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?

Additional Information:

Additional Information OSEHRA website: www.osehra.org HardHats.org: http://www.hardhats.org MUMPS http://en.wikipedia.org/wiki/MUMPS http://www.mcenter.com/mtrc/mfaqhtm1.html World Vista: www.worldvista.org Webnairs : https://www.vxvista.org/display/vx4Learn/Recorded+Webinars

Thank You:

Thank You Visit http://www.netspective.com http :// www.healthcareguy.com E-mail shahid.shah@netspective.com Follow @ ShahidNShah Call 202-713-5409

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