iHT² Health IT Summit Atlanta - Case Study “Analytics Strategies to Improve Quality & Outcomes”

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Case Study “Analytics Strategies to Improve Quality & Outcomes”

Trevor Strome, MSc, PMP
Analytics Lead
WRHA Emergency Program
Assistant Professor, Department of Emergency Medicine
University of Manitoba

iHT2 case studies and presentations illustrate challenges, successes and various factors in the outcomes of numerous types of health IT implementations. They are interactive and dynamic sessions providing opportunity for dialogue, debate and exchanging ideas and best practices. This session will be presented by a thought leader in the provider, payer or government space.

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iHT² Health IT Summit Atlanta - Case Study “Analytics Strategies to Improve Quality & Outcomes”

  1. 1. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Trevor Strome, MSc, PMP Analytics Lead, Winnipeg Regional Health Authority – Emergency Program Assistant Professor, Dept. of Emergency Medicine, University of Manitoba Blog: http://HealthcareAnalytics.info Twitter: @tstrome
  2. 2. Developing an Analytics Strategy Framework that Improves Quality and Outcomes “Every system is perfectly designed to get the results it gets.” - Dr. Paul Batalden
  3. 3. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Healthcare Analytics and the Information Value Chain 3 Performance Objectives Quality Goals Improvement Approach Data Business Processes Analytics What DID Happen What IS Happening What Will Happen Decisions & Actions Outcomes Evaluation Healthcare analytics is the system of tools, techniques, and people required to consistently and reliably generate accurate, validated, and trustworthy business and clinical insight.
  4. 4. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Signs an Analytics Strategy is Required 4 “We have all these dashboards, but why aren’t we seeing any improvement?” “Why can’t I get the data that we need for our quality improvement project?” “Those quality improvement experts ask for all this data and reporting but never seem to know what they need?”
  5. 5. Analytics Strategy Framework
  6. 6. Developing an Analytics Strategy Framework that Improves Quality and Outcomes 6 Analytics Strategy Overview • A strategy that ensures analytics development and capabilities are in alignment with enterprise quality and performance goals – avoids the “all dashboard, no improvement” syndrome • Helps to achieve optimal use of analytics – can mean the difference between a “collection of reports” versus a high-value information resource • Analytics Strategy helps align other relevant organizational strategies
  7. 7. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Analytics Strategy Business & Quality Context Stakeholders & Users Processes & Data Tools & Techniques Team & Training Technology & Infrastructure Analytics Strategy Framework 7
  8. 8. Business & Quality Context Analytics Strategy Business & Quality Context Stakeholders & Users Processes & Data Tools & Techniques Team & Training Technology & Infrastructure
  9. 9. Developing an Analytics Strategy Framework that Improves Quality and Outcomes 9 Business Context: Enterprise Goals, Objectives, and Strategy • Goals: – Are what the organization is aiming to achieve. – Define the performance and quality targets of the organization – Answer “why” the organization is (or should be) engaging in certain improvement activities • Strategy – Outlines how the organization expects to achieve its goals • Analytics must provide insight into past, current, and anticipated future progress towards meeting the enterprise goals.
  10. 10. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Aligning Strategic and Tactical Quality Objectives • Analytics is the “glue” which ties strategic objectives and tactical activities together. • Objectives of unit- or department-based improvement initiatives should, where possible, align with the quality objectives of the organization as a whole. – Prevents misdirected/wasted activity – Enables the HCO to monitor progress and evaluate outcomes Strategic Level Strategic Objectives Analytics Metrics Indicators Targets Tactical Level Tactical Objectives A reminder that the customer (“the patient”) is the ultimate reason for the work we’re doing. 10 Voice of the customer
  11. 11. Developing an Analytics Strategy Framework that Improves Quality and Outcomes 11 Quality Strategy / Improvement Approach • Quality Strategy outlines the steps and approach the organization is going to be taking to achieve quality goals/objectives. • Which QI approaches are utilized (i.e., Lean, Six Sigma) will impact what data is required, how it is analyzed, and how it is communicated. • Analytics development teams and quality improvement teams must work closely together – to ensure that information requirements of users and the delivery via analytics are in sync.
  12. 12. Stakeholders & Users Analytics Strategy Business & Quality Context Stakeholders & Users Processes & Data Tools & Techniques Team & Training Technology & Infrastructure
  13. 13. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Stakeholder Analysis • A stakeholder is a person (or group of persons) that are: – impacted by, users of, or otherwise have a concern (or interest in) the development and deployment of analytical solutions throughout the healthcare organization. • When developing an analytics strategy, it is important to understand what each of the likely analytics stakeholders will require, and develop approaches to ensure they are getting what they need. 13
  14. 14. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Common HCO Stakeholder Types 14 Stakeholder Description Patient The person whose health an healthcare experience we’re trying to improve with the use of analytics Sponsor The person who supports and provides financial resources for the development and implementation of the analytics infrastructure Influencer A person who may not be directly involved in the development or use of analytics, but who holders considerable influence over support of analytics initiatives. Customer / User A person in the HCO who accesses analytical tools, or uses the output of analytical tools, to support decision making and to drive action.
  15. 15. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Analytics Use Cases • A use case is a brief description of how analytics will be used by a stakeholder. Analytics use cases can help to: – identify any gaps in analytics capabilities, and – reduce the likelihood that critical analytics needs will be missed. • Analytics use cases help identify: – what data elements are most important and what indicators will be necessary to calculate, and – what types of usability and presentation factors (such as dashboards, alerts, and mobile access) need to be considered. • TIP: Develop high-level use cases when outlining the analytics strategy, and drill down in more detail as new analytical applications are designed and built. 15
  16. 16. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Example Analytics Use Cases 16 Customer / user Sample use case(s) Physician Uses personalized performance report to adjust care practices. Unit manager Determine which patients are likely to exceed length of stay targets. QI team leader Identify bottlenecks in patient flow. Evaluate outcomes of QI initiatives. Healthcare executive Evaluate and monitor overall performance of the organization.
  17. 17. Processes & Data Analytics Strategy Business & Quality Context Stakeholders & Users Processes & Data Tools & Techniques Team & Training Technology & Infrastructure
  18. 18. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Data considerations • Data is the “raw material” of analytics. • Modern computerized clinical systems (such as electronic medical records) contain dozens if not hundreds of individual data elements. – The potential exists for thousands of possible data items from which to choose for analytics. • An analytics strategy must consider: – how to determine which data is necessary for quality and performance improvement – how the data is managed and its quality assured – how data links back to business processes for necessary context. 18
  19. 19. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Data Issue Example Data Sources • What are the sources of data? • What data is necessary to address key business issues? Data Quality • How good is the quality of available data? • Is the data “good enough” for analytics? • What gaps in data exist? • Does metadata exist? Data governance • Who is responsible for data management, governance, and stewardship? • What policies and procedures exist? Business Processes • What business processes and procedures align with important quality issues? • What data is available for measuring processes? Are proxy measures available? Data Considerations for Analytics Strategy 19
  20. 20. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Business Processes • Business processes provide essential context to the data. • Most quality improvement methodologies monitor progress and evaluate performance and outcomes using indicators based on process data. – This requires a strong alignment between key business processes and the data that measures those processes. • As part of the analytics strategy, you should consider: – if and how current business processes are documented, and – how data items are mapped to these documented business processes. • TIP: stacks of Visio charts becomes unmanageable very quickly! 20
  21. 21. Developing an Analytics Strategy Framework that Improves Quality and Outcomes • Using appropriate indicators that align between tactical and strategic levels are necessary. – Tactical-level sub-indicators should align with strategic indicators – Some tactical-level-specific indicators might be necessary for initiatives that are important at a program, department, or unit level, but don’t directly align with strategic goals. Indicator Sub- Indicator 1 Sub- Indicator 2 Sub- Indicator 3 Strategic Level Tactical Level Tactical Indicator 1 Using Appropriate Indicators 21
  22. 22. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Example Strategic and Tactical Indicator Alignment 22 95% of patients admitted from ED achieve EDLOS < 8hrs Time to physician assessment Time to consult answered Time to consult decision Strategic Level Tactical Level Time to inpatient bed assigned Time to patient left ED
  23. 23. Analytics Tools and Techniques Analytics Strategy Business & Quality Context Stakeholders & Users Processes & Data Tools & Techniques Team & Training Technology & Infrastructure
  24. 24. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Analyzing The “Right Things” the “Right Way” What Happened? (Reports) What’s Happening Now? (Alerts, Dashboards) What Will Happen? (Extrapolation) How and Why Did It Happen? (Modeling) What’s the next best action? (Recommendation) What’s the best/worst that can happen? (Prediction, Simulation) Past Present Future Information Insight Notes: Adapted from: Davenport TH, Harris JG, & Morison R. Analytics at Work. Boston: Harvard Business School Publishing Corporation, 2010. 24
  25. 25. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Common Analytical Applications 25 Analytical Application Description Statistical • Used for deeper statistical analysis not available in “standard” business intelligence or reporting packages Visualization • Used for developing interactive, dynamic data visualizations that aid with analysis Data Profiling • Helps to understand and improve the quality of an HCO’s data. Data Mining • Analysis of large data sets to uncover unknown or unsuspected relationships. Text Mining • Analysis of unstructured, text-based data to extract high-quality information.
  26. 26. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Inventory of Existing Analytical Tools • Analytical tools must meet the requirements of analysts building analytics solutions/applications, and the end-users who will rely on the resultant information and insight. • Conduct an inventory of existing analytics tools to determine if: – Capability is missing that will be required – Existing capability exists that may not be widely known • Identify viable best-of-breed vendor solutions that meet requirements; custom-build from scratch if necessary or if participating in research. 26
  27. 27. Team and Training Analytics Strategy Business & Quality Context Stakeholders & Users Processes & Data Tools & Techniques Team & Training Technology & Infrastructure
  28. 28. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Team Development Considerations • PEOPLE are a critical consideration when developing or expanding an analytics capability within a healthcare organization • Although having the best tools are nice, having the best (and right) people is critical to achieving the goals and objectives of the HCO • An analytics strategy must consider: – What kinds of people (and the skills they bring) are necessary – The optimal size and composition of the team – Roles and degree of specialization – What gaps in skills exist, and what training is required – How to attract the best analytical talent – How to retain the analytic talent within your HCO – Optimal organizational structure 28
  29. 29. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Organizational Considerations • Different resource management models exist for analytics teams: – “centralized” analytics office – “distributed” analytics resources – “virtual” center of excellence / competency center (combines best aspects of centralized and distributed models) 29 Virtual Business Intelligence / Analytics Competency Centre Senior Management Decision Support Services (Analytics) Central (“Core”) Analytics Analysts Surgery Program Program Analytics Resource Medicine Program Program Analytics Resource Emergency Program Program Analytics Resource
  30. 30. Technology and Infrastructure Analytics Strategy Business & Quality Context Stakeholders & Users Processes & Data Tools & Techniques Team & Training Technology & Infrastructure
  31. 31. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Technology & Infrastructure • Analytics and reporting are the tip of the iceberg in the business intelligence stack. • The current, near-term, and long-term analytics needs of the HCO must drive how analytics-related technological capabilities are acquired. The exact complement of tools will depend on the overall needs of the HCO. • The analytics strategy is an important input to IT hardware and infrastructure strategies and planning as hardware and other system upgrades are considered. 31
  32. 32. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Healthcare BI and Analytics Technology and Infrastructure 32 Source: Evelson, B. It's Time to Reinvent your BI Strategy. Forrester Research, Inc. Reporting and analytics are the “tip of the iceberg” regarding the business intelligence technology stack.
  33. 33. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Analytics Stack Presentation Visualization Dashboards Reports Alerts Mobile Geospatial Quality & Performance Management Processes Indicators Targets Improvement strategy Evaluation strategy Analytics Tools Techniques Team Stakeholders Requirements Deployment Management Data Quality Management Integration Infrastructure Storage Business Context Objectives Goals Voice of patient Focus on Business • An abstracted BI stack helps maintain focus on key components of analytics required to address business goals. 33
  34. 34. Executing Strategy
  35. 35. Developing an Analytics Strategy Framework that Improves Quality and Outcomes 35 Strategy Execution Summary • It is important to implement and adhere to the analytics strategy • Plan for and schedule activities to address identified gaps – Establish a selection criteria to determine what projects will get emphasis in light of needs of the business and analytics strategy – Prioritize activities and desired capabilities to balance resources as new (possibly conflicting) work arises • Monitor progress towards achieving goals of the analytics strategy • Ensure that the strategy is a living document that serves as a roadmap for guiding action and doesn’t become “shelfware”
  36. 36. Developing an Analytics Strategy Framework that Improves Quality and Outcomes Successes • Increased coordination between management, QI teams, and analytics/BI developers. – Increased accessibility of analytics insight to QI practitioners – Rapid (in some cases real-time) monitoring and evaluation of improvement initiatives – Senior management gaining more clarity into program / department performance • Have seen a focusing of QI efforts, by integrated multidisciplinary teams, that have achieved significant and sustainable outcomes • Created a strategic information resource – Development efforts more focused / integrated – Dramatically increased use of “self-serve” of data 36
  37. 37. Developing an Analytics Strategy Framework that Improves Quality and Outcomes 37 Contact Information for Trevor Strome – Email: tstrome@wrha.mb.ca or trevor@HealthcareAnalytics.info – Phone: 204-632-3395 – Twitter: @tstrome – Blog: http://HealthcareAnalytics.info – Book: Healthcare Analytics for Quality and Performance Improvement http://HealthcareAnalyticsBook.com (Published by John Wiley & Sons, Inc, and available on Amazon.com)

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