data analytics strategy

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?”


Typical Decision Support Model

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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


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

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Analytics Strategy Framework


Analytics Strategy

Business & Quality Context

Stakeholders & Users

Processes & Data

Tools & Techniques

Team & Training

Technology &

Infrastructure

Components of Analytics Strategy

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Adding SWOT to Strategy

• Traditional “SWOT” analysis can be layered onto the components

(and sub-components) of analytics strategy.

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Strengths Weaknesses Opportunities Threats

Business &

Quality Context

Stakeholders &

Users

Data &

Processes

Tools &

Techniques

Team &

Training

Technology &

Infrastructure


Analytics Strategy



Processes & Data

Tools & Techniques

Team & Training

Technology & Infrastructure


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.


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.

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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?”


Analytics Strategy



Processes & Data

Tools & Techniques

Team & Training



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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HCO Stakeholder Types

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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.


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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Example Analytics Use Cases

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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



Processes & Data

Tools & Techniques

Team & Training



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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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

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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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• 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

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Example Strategic and Tactical Indicator Alignment

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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



Processes & Data

Tools & Techniques

Team & Training



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.

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Common Analytical Applications

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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.


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.

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Team and Training

Analytics Strategy



Processes & Data

Tools & Techniques

Team & Training



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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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


Emergency Program


Technology and Infrastructure

Analytics Strategy



Processes & Data

Tools & Techniques

Team & Training



Healthcare BI and Analytics Technology and Infrastructure

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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.


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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• 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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Strategy Execution


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”


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.

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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





Prioritizing Gap Corrective Actions

• Use the Impact / Effort matrix to help quantitatively determine priority

for addressing analytics gaps.

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Q1

Imp

ac

t (i

ncre

as

ing

)

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”


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

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Contact Information for Trevor Strome

– Email: [email protected] or

[email protected]

– 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)

mailto:[email protected]

mailto:[email protected]

http://twitter.com/tstrome

http://twitter.com/tstrome

http://healthcareanalytics.info/

http://healthcareanalyticsbook.com/



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