Closed-Loop Analytics (EHR Integration): Turning Insights into Actions

Transcription

1 Session #6 Closed-Loop Analytics (EHR Integration): Turning Insights into s Jeffrey D. Wu, MPH Director, Product Development Health Catalyst

2 2 Poll Question #1 What is the primary purpose of analytics in healthcare (select one)? a) To provide more advanced reporting b) Retrospective analysis to evaluate performance c) Regulatory compliance and reporting d) Education and/or information to targeted end-users e) Monitoring for quality or improvement initiatives f) Something else entirely g) Unsure or not applicable

3 Learning Objectives Define closed-loop analytics. Evaluate the challenges to creating closed loops in healthcare, including data latency, data availability, and integration capabilities in workflow systems, such as the EHR. Describe current opportunities for closed-loop analytics, the evolution toward true interoperability, and the technologies that will make it possible.

4 Analytics embedded within workflows enable end users (clinicians, financial leaders, and others) to deliver better patient care, improve patient experience, and reduce costs.

5 15x

6 Closed-Loop Analytics is a conceptual cycle consisting of four linked steps where: (1) users (2) generate data (3) that is used to produce metrics, analytics or visualizations (4) that are fed back to users to act on immediately through one or more interventions. Doug Clow The learning analytics cycle: closing the loop effectively. In Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (LAK '12), Simon Buckingham Shum, Dragan Gasevic, and Rebecca Ferguson (Eds.). ACM, New York, NY, USA, DOI=

7 What Is Closed-Loop Analytics? In more recent years, this principle has been applied to other industries to describe a modern approach of directly applying insights from analytics directly into the system or process that initiated the data. This is especially true for marketing analytics.

8 What Is a Closed Loop in Healthcare? Data

9 Analytics Progression Model Analytics Human Input Data Descriptive What happened? Decision or Insight Adapted from Gartner Report July 2015

10 Analytics Progression Model Analytics Human Input Data Descriptive What happened? Diagnostic Why did it happen? Decision or Insight Adapted from Gartner Report July 2015

11 Analytics Progression Model Analytics Human input Descriptive What happened? Data Diagnostic Why did it happen? Predictive Based on what we know, what will happen? Decision support Decision or insight Prescriptive Now that I know, what do I do? Decision automation Adapted from Gartner Report July 2015

12 Many Organizations Are Stuck Here Analytics Human input Descriptive What happened? Data Diagnostic Why did it happen? Predictive Based on what we know, What will happen? Decision support Decision or insight Prescriptive Now that I know, what do I do? Decision automation

13 They Stop Analytics Descriptive What happened? Human input here Data Diagnostic Why did it happen? Predictive Based on what we know, What will happen? Decision support Decision or insight Prescriptive Now that I know, what do I do? Decision automation

14 And Struggle to Account for Time here Analytics Human input and here Descriptive What happened? Data Diagnostic Why did it happen? Predictive Based on what we know, What will happen? Decision support Decision or insight Prescriptive Now that I know, what do I do? Decision automation

15 Workflow Data

16 Closed-loop analytics provides a better, or otherwise unknown, option in a workflow, leading to improved decision making and action.

17 Outcomes of Closed-Loop Analytics 1) Knowledge/Information

18 Outcomes of Closed-Loop Analytics 1) Knowledge/Information 2) Reactionary! *

19 Outcomes of Closed-Loop Analytics 1) Knowledge/Information 2) Reactionary 3) Prescriptive!

20 Outcomes of Closed-Loop Analytics 1) Knowledge/Information 2) Reactionary 3) Prescriptive 4) Proactive

21 Poll Question #2 Please indicate the level of closed-loop analytics your organization has achieved (select one). a) Informational or educational: analytics are used purely as insights for end users b) Reactive: analytics are used to highlight missed opportunities that should be acted on c) Prescriptive: analytics are delivered within a workflow to target best practice opportunities d) Proactive: analytics are deployed within a workflow to recommend actions not native to the current workflow s context e) Unsure or not applicable

22 Workflow tool Analytics Engine Data Warehouse Workflow tool ΣY = ⅖X² / Ω Reports Algorithms and Logic Workflow tool Dashboards

23 Problem 1: Latency Workflow tool Analytics Engine Data Warehouse Workflow tool ΣY = ⅖X² / Ω Reports Algorithms and Logic Workflow tool Dashboards

24 Problem 2: Lack of Integration Back to Workflow Workflow tool Analytics Engine Data Warehouse Workflow tool ΣY = ⅖X² / Ω Reports Algorithms and Logic Workflow tool X Dashboards

25 Historically, closed-loop analytics were driven by the availability of the data, not the needs of the organization to achieve its mission.

26 ! Reduce the latency of data. Deliver analytics that can be immediately acted on.

27 External Data Workflow tool Analytics Engine Workflow tool Workflow tool Data Warehouse ΣY = ⅖X² / Ω Advanced Modeling Algorithms and Logic NLP & Machine Learning Systems Integration Reports Dashboards API (FHIR, HL7 v2) Mobile, Web, Apps & Widgets Systems Integration

28 Poll Question #3 What is your biggest challenge to doing more advanced closed-loop analytics (select all that apply)? a) Not an organizational priority b) Don t know if closed-loop opportunities exist in our current systems c) Don t have real-time analytics data d) Existing tools lack functionality e) Other f) Unsure or not applicable

29 Setup three apps to be hosted directly within Hyperspace: Revenue Cycle Explorer Hospital Billing Revenue Cycle Explorer Professional Billing Provider Performance Dashboard (PPD) All apps have the added bonus of triggering actions directly within Epic. Revenue Cycle Explorer (HB) launches the Epic activity Hospital Account Maintenance, Revenue Cycle Explorer (PB) launches to the Epic Guarantor Account Summary, and the Provider Performance Dashboard launches the Epic activity Chart Review.

30 In Two Closed-Loop Projects Live Since Jan Improved Utilization: Max Monthly Distinct Users: 282 -> % Max Monthly Sessions: 1,301 -> 2, % Improved Revenue Helped support workflows that redeemed almost 15 million in write-offs and denials

31 Integrated Analytics within Workflow Workflow Engine Tool (EHR)

32 1. Worklist Generation. Analytics that drive a workflow action or guide to a workflow that exists.

33 1. Worklist Generation. Analytics that drive a workflow action or guide to a workflow that exists. 2. Workflow Context Analytics delivered in a workflow context that guide a better or missed intervention.

34 1. Worklist Generation. Analytics that drive a workflow action or guide to a workflow that exists. 2. Workflow Context Analytics delivered in a workflow context that guide a better or missed intervention. 3. Analytics-Driven Workflows Analytics driven workflows that are currently unsupported by existing systems or provide superior functionality. Workflow tool

35 Fully Optimized Closed-Loop Architecture Workflow engine context passed to analytics engine via application programming interfaces (API) to customize analytics to workflow. Data science algorithms leveraging machine learning and real-time data pushes data back to the workflow engine for integrated display. Customizable widgets present end users with most important analytics relevant to this patient at this time. Check list surveillance. Display of relevant information not part of the workflow engine can be accommodated. Allows immediate action. Closer to real-time data acquisition and context passing allows analytics to be hosted directly in workflow and allow immediate action. Data acquisition closer to real-time leveraging APIs (Smart on FHIR). Natural language processing (NLP) and closer to real-time data acquisition allows precise customization of cohort by context.

36 A A A A APIs and Web Calls APIs and web calls that allow integration with a specific system. Interface Engine Standardized interface engines that allow communication with multiple systems through one interface language. Standardized Interface Languages Standardized interface languages such as HL7 v2 and FHIR* that allow common standard integration of data and system actions. *Fast Healthcare Interoperability Resources

37 Key Takeaways and Lessons Learned Don t wait! Some things, like easier accessibility and simple integration, are already available in most systems. Pay attention to workflow. Ensure the integration is part of the work your end users are already doing, or better yet, make it easier for them to do their work. Iterate. Users can tolerate change if the change is incremental and adapted to their workflows. People will accept changes for the sake of an easier workflow or a superior outcome.

38 Evolution from a Data Warehouse to a Data Operating System Data Warehouse Data Operating System 1 Collects data from EHR and claims. Collects data from many sources. 2 Enables creating reports. Enables creating reports and web/mobile apps. 3 Enables SQL queries. Enables SQL, machine learning (R/Python) queries. 4 Data is updated nightly. Data is updated in real-time. 5 Not available in the EHR workflow. Insights are easily available in the EHR workflow. 6 Requires replacing your existing EDW. Works with your existing EDW (or use our EDW). 7 Proprietary schemas. Industry standard schemas (e.g., FHIR). 8 Text analytics is a separate process. Text analytics is built-in. 9 Works with rows and columns. Works with rows, columns and reusable healthcare logic like registries, measures, risk, insights. 10 Provides centralized security at app and data levels. 11 Makes machine learning as easy to use as SQL. 12 Content Marketplace to share executable content with other health systems.

39 Thank You