Developing an Analytics Strategy that Drives Healthcare Transformation

Transcription

1 Developing an Analytics Strategy that Drives Healthcare Transformation Trevor Strome, MSc, PMP Analytics Lead, Winnipeg Regional Health Authority Emergency Program Assistant Professor, Dept. of Emergency Medicine, University of Manitoba Blog:

2 Where is Winnipeg, Manitoba? 2

3 Signs an Analytics Strategy is Required 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? Why do those quality improvement folks ask for all this data and reporting but never seem to know what they need? 3

4 Typical Decision Support Model Performance Objectives Business Processes What DID Happen Data Analytics Tools and Methods What IS Happening Decisions & Actions Outcomes Evaluation Improvement Approach What Will Happen Quality Goals How to make this happen? 4

5 What is an Analytics Strategy? 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 should align with: Business Intelligence (BI) or Information Technology (IT) strategy Quality Improvement (QI) strategy 5

6 Building and Executing a Successful Strategy Understand requirements Review strategy components with stakeholders Identify how analytics are currently used Determine what capabilities will be needed (short & long term) Identify gaps and mitigate risk List known/potential gaps and their mitigation approaches Prioritize gap mitigation based on impact, effort, & cost Execute plan Assign task owners and target implementation deadlines Monitor progress and apply mid-course corrections 6

7 Analytics Strategy Framework

8 Components of Analytics Strategy Business & Quality Context Technology & Infrastructure Stakeholders & Users Analytics Strategy Team & Training Processes & Data Tools & Techniques 8

9 Adding SWOT to Strategy Traditional SWOT analysis can be layered onto the components (and sub-components) of analytics strategy. Business & Quality Context Strengths Weaknesses Opportunities Threats Stakeholders & Users Data & Processes Tools & Techniques Team & Training Technology & Infrastructure 9

10 Business & Quality Context Business & Quality Context Technology & Infrastructure Stakeholders & Users Analytics Strategy Team & Training Processes & Data Tools & Techniques

11 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 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. 11

12 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 Voice of the Customer A reminder that the customer ( the patient ) is the ultimate reason for the work we re doing. 12

13 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 by via analytics are in sync. When executing the analytics strategy, ask are we taking appropriate and necessary steps to achieve the organization s quality goals? 13

14 Stakeholders & Users Business & Quality Context Technology & Infrastructure Stakeholders & Users Analytics Strategy Team & Training Processes & Data Tools & Techniques

15 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. 15

16 HCO Stakeholder Types Stakeholder Patient Sponsor Influencer Customer / User Description The person whose health an healthcare experience we re trying to improve with the use of analytics The person who supports and provides financial resources for the development and implementation of the analytics infrastructure 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. A person in the HCO who accesses analytical tools, or uses the output of analytical tools, to support decision making and to drive action. 16

17 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. 17

18 Example Analytics Use Cases Customer / user Physician Unit manager QI team leader Healthcare executive Sample use case(s) Uses real-time analytics for improving diagnostic accuracy. Uses personalized performance report to adjust care practices. Determine which patients are likely to exceed length of stay targets. Identify bottlenecks in patient flow. Evaluate outcomes of QI initiatives. Evaluate and monitor overall performance of the organization. 18

19 Processes & Data Business & Quality Context Technology & Infrastructure Stakeholders & Users Analytics Strategy Team & Training Processes & Data Tools & Techniques

20 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. 20

21 Data Considerations for Analytics Strategy 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? 21

22 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! 22

23 Using Appropriate Indicators 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. Strategic Level Indicator Tactical Level Sub- Indicator 1 Sub- Indicator 2 Sub- Indicator 3 Tactical Indicator 1 23

24 Analytics Tools and Techniques Business & Quality Context Technology & Infrastructure Stakeholders & Users Analytics Strategy Team & Training Processes & Data Tools & Techniques

25 Analyzing The Right Things the Right Way Past Present Future Information What Happened? (Reports) What s Happening Now? (Alerts) What Will Happen? (Extrapolation) Insight How and Why Did It Happen? (Modeling) What s the next best action? (Recommendation) What s the best/worst that can happen? (Prediction, Simulation) Notes: Adapted from: Davenport TH, Harris JG, & Morison R. Analytics at Work. Boston: Harvard Business School Publishing Corporation,

26 Common Analytical Applications 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. Online Analytical Processing Allows analysts to interactively explore data by drilling-down, rolling up, or slicing and dicing data. 26

27 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. 27

28 Team and Training Business & Quality Context Technology & Infrastructure Stakeholders & Users Analytics Strategy Team & Training Processes & Data Tools & Techniques

29 Human Resources PEOPLE are a critical consideration when developing or expanding an analytics capability within a healthcare organization Although having the best toys 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 How to attract the best analytical talent How to retain the analytic talent within your HCO 29

30 Organizational Considerations Different resource management models exist for analytics: centralized analytics office distributed analytics resources virtual center of excellence / competency center Senior Management Decision Support Services (Analytics) Surgery Program Medicine Program Emergency Program Central ( Core ) Analytics Analysts Program Analytics Resource Program Analytics Resource Program Analytics Resource Virtual Business Intelligence / Analytics Competency Centre 30

31 Technology and Infrastructure Business & Quality Context Technology & Infrastructure Stakeholders & Users Analytics Strategy Team & Training Processes & Data Tools & Techniques

32 Healthcare BI and Analytics Technology and Infrastructure Reporting and analytics are the tip of the iceberg regarding the business intelligence technology stack. Source: Evelson, B. It's Time to Reinvent your BI Strategy. Forrester Research, Inc. 32

33 Focus on Business An abstracted BI stack helps maintain focus on key components of analytics required to address business goals. Analytics Stack Presentation Visualization Dashboards Reports Alerts Mobile Geospatial Quality & Performance Management Processes Indicators Targets Improvement strategy Analytics Evaluation strategy Tools Techniques Team Stakeholders Deployment Data Requirements Management Quality Management Integration Infrastructure Business Context Storage Objectives Goals Voice of patient 33

34 Technology & Infrastructure Analytics and reporting are the tip of the iceberg in the business intelligence. 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. 34

35 Strategy Execution

36 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

37 Gap Analysis Identify important gaps between current and future state, what the corrective action(s) will be, who owns the actions, and what the due date for corrective actions is. Category Current State Target State Corrective Action Priority Owner Due Date Business & Quality Context Stakeholders & Users Data & Processes Tools & Techniques Team & Training Technology & Infrastructure 37

38 Impact (increasing) Prioritizing Gap Corrective Actions Use the Impact / Effort matrix to help quantitatively determine priority for addressing analytics gaps. High impact, Low effort Immediate High impact, High effort Evaluate Q2 Q3 Q1 Q4 Low impact, Low effort Consider Low impact, High effort Avoid Effort/Resources Required (increasing) 38

39 Outcomes of Implementing an Analytics Strategy 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 Development of the analytics portal into a strategic information resource Development efforts more focused / integrated Dramatically increased use of self-serve of data Applying analytics strategic framework in preparation for new Enterprise Data Warehouse roll-out 39

40 Contact Information for Trevor Strome or Phone: Blog: Book: Healthcare Analytics for Quality and Performance Improvement (Published by John Wiley & Sons, Inc, and available on Amazon.com) 40