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.

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. 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. 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. 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. Analytics Strategy Framework

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

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

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

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

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

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

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.
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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. 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.
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34. Executing Strategy

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. 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
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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)