Jump Start Analytics in Your HIE (webinar)
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Link to the recorded webinar - https://youtu.be/RE6j3tF1MHA Topics for this webinar include: • How to integrate existing HIE data in the Health Catalyst analytics platform, DOS™ (Data Operating System) • Gaining insights from HIE data that can drive outcome improvements • Existing applications and tools available that can leverage HIE data
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Jump Start Analytics in Your HIE (webinar)
- 1. Health Catalyst Jump start analytics in your HIE
- 5. Transactional System vs Analytic Platform 5
- 6. © 2018 Health Catalyst 6 Transactional Data (OLTP) Analytic Data (OLAP) Application / Transaction Oriented Subject / Analysis Oriented Used to operate the business Used to analyze the business Current real time History to current Repetitive real time access Ad-Hoc access Performance Sensitive (real time response) Performance Relaxed Few records accessed at a time Large volumes accessed at a time Read + Update Access and indexed Read only (batch update) No data redundancy (3rd Normal Form) Redundancy accepted (de-normalized) Thousands of users accessing in real time Hundreds of users (ad hoc)
- 7. Data Operating System (DOS)
- 8. © 2018 Health Catalyst DOS enables the full potential of data EDW Traditional Delayed by a day or more Conference Room Analytics Retrospective Right Time From event to insight quickly Operational Analytics Real-time data pipeline, FHIR Right Insights Predictive Prescriptive Quality & Performance Metrics SQL Algorithms, Machine Learning models Right Place At point of care In the workflow Unsupervised Outcomes EMR Closed Loop, Excel, Analytics Portal Right Delivery Analytic Accelerators Software Modules Mobile Create-your-own apps Open APIs, App Platform, Fabric Services Traditional EMRs and EDWs have brought us this far Right Data Multiple integrated data sources External data sources Socioeconomic, Personal device data, Big Data DOS DOS DOS DOS DOS
- 9. © 2018 Health Catalyst The Data Operating System Data Ingest Real-time Streaming Source Connectors Catalyst Analytics Platform Fabric Data Services Real-time Processing Health Catalyst Applications Data Quality Data Governance Pattern Recognition Hadoop/ Spark Data Export Population & Registry Builder Leading Wisely Care Management Atlas Client-built Applications NLP Touchstone Benchmarks CORUS Cost Accounting Patient Safety Measures Manager ACO Financials Patient Engagement HL7 Data Pipelines Metadata Data Lake Reusable Content AI Models Third-party Apps Artificial Intelligence Pipelines Marketplace SAMD & SMD Fabric Application Services Terminology & Groupers EMR Integration Security, Identity & Compliance Patient & Provider Matching Value Sets & Measures Standard, Extensible Data Models RegistriesFHIR HL7 Analytic Accelerators
- 10. © 2018 Health Catalyst Flow of Data through DOS 10 Claims Reports DOS Open APIs & Marketplace Extend EMR Apps Notes Cost Care Mgmt Social Biometric Content Acquire 200+ data sources Organize Source Marts Standardize Shared Data Marts Analyze Combine | Enrich | Predict Fabric Data Microservices, Content Microservices, AI Models Deliver EMR Integration Source Connectors Data Ingest Data Pipelines Data Lake Standard Data Models Metadata Data Governance Data Quality HL7 FHIR Real-time Streaming Machine Learning Pipelines NLP Pattern Recognition Security, Identity & Compliance Registries Terminology & Groupers Measures EMR Integration Patient & Provider Matching Closed Loop EMR Data Export Apps AI Models HIE Longitudinal Record
- 11. © 2018 Health Catalyst 7 Attributes of DOS 11 Reusable Clinical and Business Logic Streaming Data Integrates Structured and Unstructured Data Closed-Loop Capability Microservices Architecture Machine Learning Agnostic Data Lake
- 12. © 2018 Health Catalyst What do we know about our patients? 12 Historical and Analytical Insights Data in the Moment • Chief Complaint • Observations • Labs • Diagnosis • Procedures • Medications • Clinical History • “Patients like me” • Risk Prediction Models • Cost Estimates • Gaps in Care • Patient Registries
- 13. © 2018 Health Catalyst A different kind of data integration 13 Analytical InsightsAt the Point of Care • Diagnosis • Medications • Labs • Procedures • Observations • Chief Complaint • Gaps in Care • “Patients like me” • Risk Prediction Models • Cost Estimates
- 14. Demonstration
- 15. Turning Data into Outcomes
- 16. © 2018 Health Catalyst Health Catalyst Mission Unleash data as a catalyst for massive, sustained improvement in healthcare outcomes 1616 2 3 1Provide insight-producing analytics and decision support technology Deliver proven analytics services and improvement expertise Create the best place to work
- 17. © 2018 Health Catalyst Capabilities to Scale Outcomes Improvement Leadership, Culture and Governance Financial Alignment Where do we focus? How are we compensated? What should we be doing? How are we doing? How do we transform? Clinical Outcomes Cost Outcomes Experience Outcomes 17
- 18. Health Catalyst Overview Domain Experts Analysts, Data Scientists, Data Architects Outsourced Services Patient Safety Cloud-based Recommendation Engines Machine Learning NLP Big Data Closed-Loop Mobile Vertical, Use-Case Driven Applications Care Management Pop Health / ACO Suite Cross-Cutting Analytic Applications CORUS (Costing) Health Catalyst Applications Portfolio Health Catalyst Data Operating System (DOS) Real-time Streaming Services Analytic Accelerators AtlasLeading Wisely TouchStone (Benchmarks) Populations Builder Applications built with cutting-edge technology: Measures Manager
- 19. Questions?
Editor's Notes
- This slide shows how EDW stop at getting the right data while DOS goes beyond to enable you to get the full value of analytics
- Right Data: DOS provides the Catalyst Analytics Platform to acquire, organize and standardize data At the right time: DOS provides real-time streaming and low latency processing to have analytics ready soon after the business event has been recorded With the right insights: DOS provides AI pipelines and AI models so you can create the right insights To the right place: EMR integration shows the insights in the clinician workflow, Analytics portal enables anyone in the organization to interact with data and Excel integration enables business folks to analyze data Using the right applications: Open APIs enable you to build your own DOS applications or use third-party applications to customize and enhance your DOS
- Reusable clinical and business logic: Registries, value sets, and other data logic lies on top of the raw data and can be accessed, reused, and updated through open APIs, enabling third-party application development. Streaming data: Near- or real-time data streaming from the source all the way to the expression of that data through DOS that can support transaction-level exchange of data or analytic processing. Integrates structured and unstructured data: Integrates text and structured data in the same environment. Eventually, it will incorporate images too. Closed-loop capability: The methods for expressing the knowledge in DOS, include delivering that knowledge at the point of decision making, for example, back into the workflow of source systems, such as an EHR. Microservices architecture: In addition to abstracted data logic, open microservices APIs exist for DOS operations such as authorization, identity management, data pipeline management, and DevOps telemetry. These microservices also enable third-party applications to be built on DOS. Machine learning: DOS natively runs machine learning models, and enables rapid development and utilization of ML models, embedded in all applications. Agnostic data lake: Some or all of DOS can be deployed over the top of any healthcare data lake. The reusable forms of logic must support different computation engines; e.g., SQL, Spark SQL, SQL on Hadoop, et al.
- David just took you through what is required from a platform perspective to excel at analytics, but at Health Catalyst, we are not just in this business of providing analytics, we are here to use data to drive outcomes. In fact, that is our mission.
- 3 Systems; Key difference;