Moving to the Cloud: Modernizing Data Architecture in Healthcare
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The document discusses moving healthcare data architecture to the cloud. It describes a large health system that implemented an enterprise data warehouse (EDW) on the cloud to provide cost savings and flexibility. This consolidated multiple clinical repositories and reduced infrastructure costs. It also describes an academic health center that integrated patient records across its organizations using a cloud-based EDW. This improved analytics and reduced operating costs by 50% while improving patient care. Both organizations benefited from the scalability, cost savings and innovation the cloud enabled for their clinical analytics and research.
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Moving to the Cloud: Modernizing Data Architecture in Healthcare
- 1. MOVING TO THE CLOUD MODERNIZING DATA ARCHITECTURE IN HEALTHCARE
- 2. About Perficient Perficient is the leading digital transformation consulting firm serving Global 2000 and enterprise customers throughout North America. With unparalleled information technology, management consulting, and creative capabilities, Perficient and its Perficient Digital agency deliver vision, execution, and value with outstanding digital experience, business optimization, and industry solutions.
- 3. Perficient Profile Founded in 1997 Public, NASDAQ: PRFT 2016 revenue $487 million Major market locations: Allentown, Atlanta, Ann Arbor, Boston, Charlotte, Chicago, Cincinnati, Columbus, Dallas, Denver, Detroit, Fairfax, Houston, Indianapolis, Lafayette, Milwaukee, Minneapolis, New York City, Northern California, Oxford (UK), Southern California, St. Louis, Toronto Global delivery centers in China and India 3,000+ colleagues Dedicated solution practices ~95% repeat business rate Alliance partnerships with major technology vendors Multiple vendor/industry technology and growth awards
- 4. Speaker Introductions James Gaston, FHIMSS MBA Sr. Director, Maturity Models, HIMSS Analytics Tom Lennon Director, Healthcare Analytics, Perficient Jim Kouba Director, Healthcare Solutions, Perficient
- 6. Welcome James E. Gaston, MBA FHIMSS • Senior Director, Maturity Models, HIMSS Analytics • Decade of experience in acute care hospital, research and admin • Decade of experience of data warehousing and C&BI at Blue Cross Blue Shield Plan • 25 years in healthcare IT, and analytics [email protected] @JamesEGaston https://www.linkedin.com/in/jamesegaston/
- 7. Healthcare Information and Management Systems Society (HIMSS) HIMSS is a global, cause-based, not-for-profit organization focused on better health through information technology (IT). HIMSS leads efforts to optimize health engagements and care outcomes using information technology. HIMSS Annual Conference, Corp Membership, Thought Leadership, etc. Marketing Arm, Healthcare IT News, Local Forums, Content Creation & Syndication, etc. LOGIC™, CapSite, Maturity Models, Insight & Research, Essentials Briefs, etc.
- 8. Healthcare’s Most Comprehensive Market Intelligence Resources & Advisory Solutions Health IT Market Intelligence Health IT Insight & Research Healthcare Organization Benchmarking
- 9. Uniquely Positioned to Deliver Actionable Intelligence Healthcare Delivery Organizations Health IT Solutions
- 10. http://www.himssanalytics.org/research/essentials-brief-2017-cloud-study
- 12. High level of cloud usage, but mainly limited to specific functions Yes 65% No 32% Unsure 3% Does your organization currently utilize the cloud or cloud services? For the purposes of this study, the cloud was defined as a model of networked online storage where data is stored in virtualized pools hosted by third parties and accessed through a web service application programming interface (API), a cloud storage gateway or via a web-based user interface. Use cases of the cloud in healthcare include hosting of applications, disaster recovery/back up and hosting of primary data storage. Roughly 65% of study respondents currently utilize the cloud or cloud services within their organization. Much of the usage leans toward clinical application and data hosting, data recovery and backup, and the hosting of operational applications. n=64
- 13. Organizations beginning to see the value of IT scalability and flexibility Meet organizational need for a scalable, always-on solution 34% Address disaster recovery needs 27% Lower current IT maintenance costs 12% Lack of internal IT staff or IT expertise on site 10% Enhance our information/data security 7% Other 10% Which of the following best describes the primary reason your organization adopted cloud services? When asked for the primary reason for the adoption of cloud services, respondents indicated their need for scalability for an ‘always-on’ solution. With the increased focus on hosting clinical applications addressing the organizational need for essential, ‘always-on’ clinical solutions through the cloud seems to be resonating across the market. While scalability and disaster recovery are top of mind for many organizations, it is somewhat surprising to see only 12 percent of those that utilize the cloud did so to lower IT costs. The past 10 years of IT adoption has required healthcare organizations to build up massive IT infrastructures that are expensive to maintain. It will be interesting to see if market sentiment around the cloud and IT maintenance changes significantly in the next few years, especially if organizations shift from a capital spending to operational spending model for some of their IT infrastructure.n=42
- 14. Understanding the benefits and risks of the cloud still hampering market sentiment Not currently in our budget 36% Privacy and security concerns 29% Feel the risks currently outweigh the benefits 21% IT operations are solely internal to organization 14% Which of the following describes the primary reason your organization does not currently use or have plans to invest in cloud services? While roughly 36% of respondents that do not use the cloud and currently have no plans to do so indicated budgetary reasons, there still seems to be a clear lack of understanding around the benefits and risks of the cloud as well as how the cloud addresses privacy and security. Security is top of mind across the healthcare industry and it will take a combination of solutions and diligence to constantly ward off threats to healthcare data. n=14
- 15. We drive the health IT market in the direction it needs to go Improved Patient Care and Health IT Insights Analytics Maturity Adoption Model Continuity of Care Maturity Model Digital Imaging Adoption Model Outpatient EMR Adoption Model EMR Adoption Model
- 16. Cloud Journey: Large Health System
- 17. About the Client • One of the largest non-profit health care integrated delivery organizations in the United States • Committed to improving the health and well being of the people and communities it serves through leadership, education, innovation, and excellence in medicine • Serves the healthcare needs of urban, suburban and rural communities and includes 15 hospitals and multiple community health locations
- 18. • Just completed a strategic roadmap for a clinical analytics architecture • First step was to establish a solid technical and data foundation for a unified, world-class enterprise analytics system • Further position cutting-edge clinical research and state-of-the-art clinical and business management analytics Business Drivers Key Goals • Consolidate & rationalize multiple clinical repositories • Provide an integrated technology platform that is extensible • Use standardized enterprise class, contemporary technology that is secure • Reduce infrastructure costs • Retire existing technology
- 19. Key Challenges • Current environment fractionated – Multiple technologies in place – Decentralized governance – Gaps in data availability – Inconsistencies in data representation • Development in parallel with enterprise rollout of new EHR – EHR data critical to success – SMEs first priority is to rollout – New data structures and content not well understood • Need to develop skills and knowledge for self-sufficiency – New staff = steep learning curve – New technology = extensive training & ramp-up • Security
- 20. Solution Implemented an EDW on the cloud to provide cost savings and architecture flexibility. Developed a streamlined migration and integration of data from the on-premises repositories to the cloud platform using design patterns that are built specifically for efficient data movement in a cloud environment. Solution Components – Healthcare industry data model – Cloud database - Infrastructure as a Service (IaaS) – Perficient Cloud Analytics Gateway – Secure, high-speed cloud data migration service – ETL tool for localized job execution control – Data governance and lineage tool – Infrastructure optimization tool
- 21. Standardized data for BI reporting Reduced data integration 50% Extensible using industry standard technologies Populates key functional areas Repeatable and Consistent Reduces risk through utilizing tested and proven methodology, patterns and framework based on best practices, across multiple implementations High Quality Proven expertise and domain knowledge of implementation team, utilizing IBM’s UDMH and technologies Timely Less time to value, while iteratively driving to further value, through reduced data integration times Meaningful Meets industry standard high-value use cases to aggregate data into data marts for purpose-built analytics Attainable Easy to use framework through collaborative, incremental build (not a big bang approach) and user engagement and enablement Scalable Established framework allows for incremental value to be added, with reduced effort Health Analytics Gateway Features and Principles On-Premises or Cloud-Based
- 22. Key Benefits • Provided access to historical and operational data from the consolidated EDW for optimal reporting and comprehensive clinical research – Clinical practice and research teams now have a more holistic view of the patient’s experience over the course of treatment and clinical interactions – Removed burden of legacy environments and disparate repositories through migration to a consolidated, modern cloud-based data platform • Improved ability to onboard new systems and integrate new data sources • Cloud environment has reduced hardware and server costs, increased scalability and flexibility, and speeds time to deployment
- 23. Lessons Learned • Establishing an enterprise-wide steering committee drove more rapid decision making and enabled buy-in from multiple, organizational constituents • Consolidation of vendors and tools enabled more focus in solution design and issue resolution – Vendor and client partnership approach established open dialog and enhanced the solution – Early collaboration from engineers from all technologies identified key solution risks and mitigation plans • Build in time to train resources and fully adopt and internalize the new technologies – Expect unanticipated challenges and plan for them upfront
- 24. Cloud Journey: Academic Health Center
- 25. About the Client • One of the largest academic health centers in the United States • Combines interdisciplinary teaching, research and clinical facilities allowing unique opportunity to: – Prepare the region’s future health care professionals – Provide the best available health care to its patients – Maintain its position as a leader in life sciences research
- 26. Provide the data and analytics platform and program to power the organization’s journey to translational and personalized medicine in support of leading edge value-based care delivery models. Begin to leverage the wealth of information the collective organization has across the full population of pediatric and adult patients to improve care in the short term and provide game changing innovation over the long term. Guiding Principles – Foster Innovation – Enable Agility – Favor Intuitive Visualizations – Learn Fast Vision
- 27. Key Challenges • Complex organization – Involved multiple autonomous organizations – Decentralized funding and governance – Disparate execution paradigms • Complex architecture, infrastructure, and operations – Disparate technology standards and skills – IT staffs were already stretched thin – Traditional data consumers now becoming data providers • Must scale to handle large amounts of data – Genomics data – Clinical data – Claims data – Environmental data • Security concerns all around
- 28. Key Benefits • Integrated 6 million adult and pediatric patient records • Reduced operating cost by 50% > Re-allocate into other areas • Able to deliver a broader and richer set of tools and technologies to data scientists and clinical decision makers; decreasing prep time by 50% so improving patient care can be the primary focus. • Rapid, iterative development of visually oriented analytics - Disease surveillance - Diagnosis prevalence
- 29. Initially implemented – Structured EDW – Enterprise ETL and RDBMS architecture – Traditional BI reporting platform Solution Eventual solution – Cloud based, fully managed EDW – Leverages super-fast SQL query engine – Local front-end visualization tool
- 30. Results
- 31. Results
- 32. Results
- 33. Lessons Learned • In-house infrastructure provisioning took too long and stifled innovation • The pivot to the cloud enabled significant reduction in IT capital investment • Using a common external provider eases organizational anxiety • Shifts security risks away from an already stretched internal IT staff • Analytic insight can be delivered in weeks as opposed to quarters • Improved alignment with guiding principles: innovation, agility, intuitive visualization, and learning fast
- 34. Questions Type questions in the chat box located in the lower left hand corner of your screen
- 35. Follow Us Online • Twitter.com/Perficient_HC • Blogs.perficient.com/Healthcare • Perficient.com/SocialMedia • Facebook.com/Perficient
Editor's Notes
- #21: UDMH: This model is a healthcare-specific blueprint for data warehousing and analytics that incorporates a robust set of data models coupled with industry specific terms, ultimately decreasing time to implementation. Traditionally, data warehousing uses an Extract, Transform, and Load (ETL) approach, which requires data clean-up and transformation prior to moving the data into a repository. With BJC’s data migration effort and design patterns, Perficient used an Extract, Load, and Transform (ELT) approach, which is a more modern data architecture that excels in a cloud-based environment.