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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: http://HealthcareAnalytics.info
Twitter: @tstrome
Developing an Analytics Strategy that Drives Healthcare Transformation
Signs an Analytics Strategy is Required
2
“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?”
Developing an Analytics Strategy that Drives Healthcare Transformation
Typical Decision Support Model
3
How to make this happen?
Performance
Objectives
Quality Goals
Improvement
Approach
Data
Business
Processes
Analytics
Tools and
Methods
What DID
Happen
What IS
Happening
What Will
Happen
Decisions &
Actions
Outcomes Evaluation
Developing an Analytics Strategy that Drives Healthcare Transformation 4
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 other relevant strategies
including:
– Business Intelligence (BI) strategy
– Information Technology (IT) strategy
– Quality Improvement (QI) strategy
Developing an Analytics Strategy that Drives Healthcare Transformation
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 risks
– 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
5
Analytics Strategy Framework
Developing an Analytics Strategy that Drives Healthcare Transformation
Analytics
Strategy
Business &
Quality
Context
Stakeholders
& Users
Processes &
Data
Tools &
Techniques
Team &
Training
Technology
&
Infrastructure
Components of Analytics Strategy
7
Developing an Analytics Strategy that Drives Healthcare Transformation
Adding SWOT to Strategy
• Traditional “SWOT” analysis can be layered onto the components
(and sub-components) of analytics strategy.
8
Strengths Weaknesses Opportunities Threats
Business &
Quality Context
Stakeholders &
Users
Data &
Processes
Tools &
Techniques
Team &
Training
Technology &
Infrastructure
Business & Quality Context
Analytics
Strategy
Business &
Quality
Context
Stakeholders
& Users
Processes &
Data
Tools &
Techniques
Team &
Training
Technology &
Infrastructure
Developing an Analytics Strategy that Drives Healthcare Transformation 10
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.
Developing an Analytics Strategy that Drives Healthcare Transformation
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.
11
Developing an Analytics Strategy that Drives Healthcare Transformation 12
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, always ask “are we
taking appropriate and necessary steps towards achieving the
organization’s quality and performance goals?”
Stakeholders & Users
Analytics
Strategy
Business &
Quality
Context
Stakeholders
& Users
Processes &
Data
Tools &
Techniques
Team &
Training
Technology &
Infrastructure
Developing an Analytics Strategy that Drives Healthcare Transformation
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.
14
Developing an Analytics Strategy that Drives Healthcare Transformation
HCO Stakeholder Types
15
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.
Developing an Analytics Strategy that Drives Healthcare Transformation
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.
16
Developing an Analytics Strategy that Drives Healthcare Transformation
Example Analytics Use Cases
17
Customer / user Sample use case(s)
Physician Uses real-time analytics for improving diagnostic
accuracy.
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.
Processes & Data
Analytics
Strategy
Business &
Quality
Context
Stakeholders
& Users
Processes &
Data
Tools &
Techniques
Team &
Training
Technology &
Infrastructure
Developing an Analytics Strategy that Drives Healthcare Transformation
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.
19
Developing an Analytics Strategy that Drives Healthcare Transformation
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
20
Developing an Analytics Strategy that Drives Healthcare Transformation
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!
21
Developing an Analytics Strategy that Drives Healthcare Transformation
• 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
22
Developing an Analytics Strategy that Drives Healthcare Transformation
Example Strategic and Tactical Indicator Alignment
23
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
Analytics Tools and Techniques
Analytics
Strategy
Business &
Quality
Context
Stakeholders
& Users
Processes &
Data
Tools &
Techniques
Team &
Training
Technology &
Infrastructure
Developing an Analytics Strategy that Drives Healthcare Transformation
Analyzing The “Right Things” the “Right Way”
What Happened?
(Reports)
What’s Happening
Now?
(Alerts)
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.
25
Developing an Analytics Strategy that Drives Healthcare Transformation
Common Analytical Applications
26
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.
Developing an Analytics Strategy that Drives Healthcare Transformation
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
Team and Training
Analytics
Strategy
Business &
Quality
Context
Stakeholders
& Users
Processes &
Data
Tools &
Techniques
Team &
Training
Technology &
Infrastructure
Developing an Analytics Strategy that Drives Healthcare Transformation
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
29
Developing an Analytics Strategy that Drives Healthcare Transformation
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)
30
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
Technology and Infrastructure
Analytics
Strategy
Business &
Quality
Context
Stakeholders
& Users
Processes &
Data
Tools &
Techniques
Team &
Training
Technology &
Infrastructure
Developing an Analytics Strategy that Drives Healthcare Transformation
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.
Developing an Analytics Strategy that Drives Healthcare Transformation
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
Developing an Analytics Strategy that Drives Healthcare Transformation
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.
34
Strategy Execution
Developing an Analytics Strategy that Drives Healthcare Transformation 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”
Developing an Analytics Strategy that Drives Healthcare Transformation
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.
37
http://www.mindtools.com/pages/article/gap-analysis.htm
Category Current State Target State Corrective
Action
Priority Owner Due Date
Business & Quality
Context
Stakeholders &
Users
Data & Processes
Tools &
Techniques
Team & Training
Technology &
Infrastructure
Developing an Analytics Strategy that Drives Healthcare Transformation
Prioritizing Gap Corrective Actions
• Use the Impact / Effort matrix to help quantitatively determine priority
for addressing analytics gaps.
38
Q1
Impact(increasing)
Effort/Resources Required (increasing)
Q4
Q2 Q3
Low impact, Low effort
“Consider”
High impact, Low effort
“Immediate”
High impact, High effort
“Evaluate”
Low impact, High effort
“Avoid”
Developing an Analytics Strategy that Drives Healthcare Transformation
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
Developing an Analytics Strategy that Drives Healthcare Transformation 40
Contact Information for Trevor Strome
– Email: tstrome@wrha.mb.ca or
trevor@HealthcareAnalytics.info
– 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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Data Analytics Strategy

  • 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: http://HealthcareAnalytics.info Twitter: @tstrome
  • 2. Developing an Analytics Strategy that Drives Healthcare Transformation Signs an Analytics Strategy is Required 2 “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. Developing an Analytics Strategy that Drives Healthcare Transformation Typical Decision Support Model 3 How to make this happen? Performance Objectives Quality Goals Improvement Approach Data Business Processes Analytics Tools and Methods What DID Happen What IS Happening What Will Happen Decisions & Actions Outcomes Evaluation
  • 4. Developing an Analytics Strategy that Drives Healthcare Transformation 4 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 other relevant strategies including: – Business Intelligence (BI) strategy – Information Technology (IT) strategy – Quality Improvement (QI) strategy
  • 5. Developing an Analytics Strategy that Drives Healthcare Transformation 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 risks – 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 5
  • 7. Developing an Analytics Strategy that Drives Healthcare Transformation Analytics Strategy Business & Quality Context Stakeholders & Users Processes & Data Tools & Techniques Team & Training Technology & Infrastructure Components of Analytics Strategy 7
  • 8. Developing an Analytics Strategy that Drives Healthcare Transformation Adding SWOT to Strategy • Traditional “SWOT” analysis can be layered onto the components (and sub-components) of analytics strategy. 8 Strengths Weaknesses Opportunities Threats Business & Quality Context Stakeholders & Users Data & Processes Tools & Techniques Team & Training Technology & Infrastructure
  • 9. Business & Quality Context Analytics Strategy Business & Quality Context Stakeholders & Users Processes & Data Tools & Techniques Team & Training Technology & Infrastructure
  • 10. Developing an Analytics Strategy that Drives Healthcare Transformation 10 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. Developing an Analytics Strategy that Drives Healthcare Transformation 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. 11
  • 12. Developing an Analytics Strategy that Drives Healthcare Transformation 12 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, always ask “are we taking appropriate and necessary steps towards achieving the organization’s quality and performance goals?”
  • 13. Stakeholders & Users Analytics Strategy Business & Quality Context Stakeholders & Users Processes & Data Tools & Techniques Team & Training Technology & Infrastructure
  • 14. Developing an Analytics Strategy that Drives Healthcare Transformation 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. 14
  • 15. Developing an Analytics Strategy that Drives Healthcare Transformation HCO Stakeholder Types 15 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.
  • 16. Developing an Analytics Strategy that Drives Healthcare Transformation 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. 16
  • 17. Developing an Analytics Strategy that Drives Healthcare Transformation Example Analytics Use Cases 17 Customer / user Sample use case(s) Physician Uses real-time analytics for improving diagnostic accuracy. 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.
  • 18. Processes & Data Analytics Strategy Business & Quality Context Stakeholders & Users Processes & Data Tools & Techniques Team & Training Technology & Infrastructure
  • 19. Developing an Analytics Strategy that Drives Healthcare Transformation 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. 19
  • 20. Developing an Analytics Strategy that Drives Healthcare Transformation 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 20
  • 21. Developing an Analytics Strategy that Drives Healthcare Transformation 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! 21
  • 22. Developing an Analytics Strategy that Drives Healthcare Transformation • 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 22
  • 23. Developing an Analytics Strategy that Drives Healthcare Transformation Example Strategic and Tactical Indicator Alignment 23 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
  • 24. Analytics Tools and Techniques Analytics Strategy Business & Quality Context Stakeholders & Users Processes & Data Tools & Techniques Team & Training Technology & Infrastructure
  • 25. Developing an Analytics Strategy that Drives Healthcare Transformation Analyzing The “Right Things” the “Right Way” What Happened? (Reports) What’s Happening Now? (Alerts) 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. 25
  • 26. Developing an Analytics Strategy that Drives Healthcare Transformation Common Analytical Applications 26 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.
  • 27. Developing an Analytics Strategy that Drives Healthcare Transformation 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 Analytics Strategy Business & Quality Context Stakeholders & Users Processes & Data Tools & Techniques Team & Training Technology & Infrastructure
  • 29. Developing an Analytics Strategy that Drives Healthcare Transformation 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 29
  • 30. Developing an Analytics Strategy that Drives Healthcare Transformation 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) 30 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
  • 31. Technology and Infrastructure Analytics Strategy Business & Quality Context Stakeholders & Users Processes & Data Tools & Techniques Team & Training Technology & Infrastructure
  • 32. Developing an Analytics Strategy that Drives Healthcare Transformation 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 that Drives Healthcare Transformation 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. Developing an Analytics Strategy that Drives Healthcare Transformation 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. 34
  • 36. Developing an Analytics Strategy that Drives Healthcare Transformation 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”
  • 37. Developing an Analytics Strategy that Drives Healthcare Transformation 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. 37 http://www.mindtools.com/pages/article/gap-analysis.htm Category Current State Target State Corrective Action Priority Owner Due Date Business & Quality Context Stakeholders & Users Data & Processes Tools & Techniques Team & Training Technology & Infrastructure
  • 38. Developing an Analytics Strategy that Drives Healthcare Transformation Prioritizing Gap Corrective Actions • Use the Impact / Effort matrix to help quantitatively determine priority for addressing analytics gaps. 38 Q1 Impact(increasing) Effort/Resources Required (increasing) Q4 Q2 Q3 Low impact, Low effort “Consider” High impact, Low effort “Immediate” High impact, High effort “Evaluate” Low impact, High effort “Avoid”
  • 39. Developing an Analytics Strategy that Drives Healthcare Transformation 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. Developing an Analytics Strategy that Drives Healthcare Transformation 40 Contact Information for Trevor Strome – Email: tstrome@wrha.mb.ca or trevor@HealthcareAnalytics.info – 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)