Four Steps to Effective Opportunity Analysis

Four Steps to Effective
Opportunity Analysis

© 2018 Health Catalyst
Proprietary. Feel free to share but we would appreciate a Health Catalyst citation.
Transforming Healthcare Business Strategy
This report is based on a 2018 Healthcare Analytics Summit presentation
given by Matthew Brown, Finance Manager, Allina Health, and Sarah
Jenson, Director, Analytics, Health Catalyst at Allina Health, entitled,
“Reducing Unwarranted Clinical Variation Saves Tens of Millions of Dollars.”
Matthew Brown
Finance Manager
Alina Health
Sarah Jenson
Director, Analytics,
Health Catalyst at Allina Health

It’s well known within the healthcare
industry that variation in clinical care
indicates waste, and waste has negative
impacts upon care quality and cost.
According to the Advisory Board’s 2017
report, Standardizing Practice for a Tighter
Grip on Cost and Quality, unwarranted
clinical variation accounts for 42 percent
of wasted spending in U.S. healthcare.
Four Steps to Effective Opportunity Analysis

As healthcare reimbursement moves to a
value-based model, health systems are
under greater pressure to reduce clinical
variation and related costs while improving
patient outcomes.
That’s not an easy task, but, fortunately,
savings opportunities exist within every
healthcare organization.
Several studies show that for every $1
billion of revenue a typical health system
has, there are approximately $30 million
of actionable savings opportunities.

Slim margins and lack of resources in health
systems require prioritizing improvement work,
so some healthcare organizations are using
data to identify opportunities and optimize
improvement initiatives.

It’s one thing to know that variation is a problem; it’s
another to know where the greatest unwarranted
variation exists and what to do about it.
Relying on traditional means to gather data, such
as manual inspection of charts or billing records,
doesn’t always lead to effective change initiatives
because these methods are inefficient and fraught
with human error.
Data Informs Opportunity Analysis

Opportunity analysis is a systemwide process that
uses data to identify opportunities for improvement
and quantifies the value of proposed improvement
initiatives in terms of optimized care, increased
revenue, and decreased costs.
It gives health systems a look at performance
on a patient, clinician, and system level.
Using data analytics tools, health systems can
get a high-level look at opportunities for change
and an in-depth look at how to improve outcomes
and financials in a prioritized approach.
Data Informs Opportunity Analysis

Identifying clinical variation is a
challenging process.
It takes time and effort to look at data
and assess where the opportunities to
drive improvement lie.
Standardizing the opportunity analysis
process makes it more repeatable
than an ad hoc analysis and prioritizes
actionable opportunities for cost
savings and care improvements.
How Data Analysis Helps Identify
Opportunities and Find Variation

Analysts recommend engaging in opportunity
analysis every quarter.
While organizations can customize their approach,
an opportunity analysis process should involve
four basic steps:
Kicking off the analysis
Engaging with clinicians to identify opportunities
Digging deeper into those opportunities
Present findings using graphical interpretations
Opportunity Analysis Steps
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Step 1: Kicking Off the Opportunity Analysis
The first part of opportunity
analysis involves getting all
analysts together to select
and assign areas of focus,
which might include service
lines, facilities, types of
services or events, literature
reviews, or a specific area
of interest.
The second part of this step
is to filter down those focus
areas to improvement ideas
and do some preliminary
analysis before engaging
with clinicians to validate the
ideas uncovered in the initial
analysis. Improvement ideas
can come from anywhere—
nurses, clinicians, research
articles, experience, etc.
Once ideas are laid out, preliminary data analysis begins.

Step 1: Kicking Off the Opportunity Analysis
Preliminary analysis requires analysts to get
together, dig into the data, look at variation, and
talk about methodologies to reduce variation.
Doing this well requires trained analysts and
the right data analysis tools.
Preliminary analysis uncovers insights for
possible improvements, which are invaluable
when engaging with clinicians, the next step.

Step 2: Engaging with Clinicians
Clinician and executive backing are
imperative for change initiatives.
Providing actionable data to clinicians
engages them in the quest for improvement.
A compelling story that provides support for
improvement initiatives shows them the
value of a data analysis investment.

Step 2: Engaging with Clinicians
Engaging with clinicians also helps analysts
understand which clinical processes
identified might warrant variation.
Working early on with clinicians to validate
opportunities for improvement makes the
data more actionable later in the process
because the team won’t spend valuable time
and resources working on, for example,
reducing variation that is warranted.

Step 3: Digging Deeper into the Data
Once the team has decided upon the areas to
investigate, it’s time for the analysts to do
what they do best.
They look at how to take what they’ve
learned and identify which specific
opportunities should be pursued.

Opportunities for improvement within health
systems abound, making it difficult for analysts
to identify the best options to present to
decision makers, but following these guidelines
for approaching the data helps:
Getting granular with the data
Focusing on areas with both high cost
and high variation
Looking for cost drivers
Examining variation
Analyzing the impact
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Getting granular with the data
By drilling down to homogeneous patient
populations by segmenting on severity,
diagnosis, procedures, and more, populations
become small enough for clinicians to
confidently say that everyone in the population
should reasonably be treated in the same way.

Focusing on areas with both high cost and high variation
The starting focal point can be vertical, such as
clinical service lines, or horizontal, such as
services that cut across the organization, such
as labs, drugs, readmissions, or network leakage.
Analysts should keep in mind that sometimes
high costs are okay if outcomes are outstanding,
so it’s important to marry cost and variation.

Looking for cost drivers
Searching for specific areas driving costs up
is a good start. The areas may include room,
supplies, OR, drugs, lab, radiology,
respiratory, and other.
From there, analysts can dig into deeper
levels of detail.

Examining variation
Examining specific facilities or providers for
variation gives insights into who or what is
driving variation.
The Advisory Board article mentioned above
stated that most variation comes from a minority
of physicians and facilities (16 percent).

Analyzing the impact
Considering factors, such as length of stay,
potentially preventable complications, or
potentially preventable readmissions, helps
analysts see the impact of variation.

Step 4: Present Findings Using Graphical Interpretations
The last step of opportunity analysis is to present
the findings to the stakeholders and clinicians.
Before analysts make presentations to teams
throughout the organization, it’s important they
are on the same page so there is continuity in
the messages.
Presentations should be both consistent and
digestible, which helps analysts explain what
they found in the data and helps others
understand those insights.

When presenting the results of an opportunity
analysis, analysts should use standard graphical
interpretations to tell the data’s story.
When talking about clinical variation, several
visualization types present data well:
Control Charts
Bubble graphs
Box Plots
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CONTROL CHARTS
A control chart illustrates variation in overall care
and the variation over time, highlighting areas
out of control. For example, data points going
above the upper control limit, as seen in Figure
1, indicate that care delivery is inconsistent and
warrants closer examination. If something is out
of control, it provides a starting point for
analysis, and the chart is a good visualization to
show leaders the variation and thus the
opportunity for improvement.
Figure 1: Control Chart

BUBBLE GRAPHS
Bubble graphs highlight volume, cost, and
variation within each location or providers. They
should be used in conjunction with control
charts. On the bubble graph, the x axis
represents cost and the y axis represents the
coefficient of variation. The size of the bubble
represents volume (the larger the bubble, the
greater the volume). The Bubble graph is a
simple visual reference to compare high cost-
high variation and lower cost-low variation
providers. These may be the best practice
providers who have good insights to share.
Figure 2: Bubble Graph

BOX PLOTS
Box plots highlight the range of variation within a
location or provider, and the overall percentiles
to make for easy comparison across categories.
For example, providers above the overall 75th
percentile indicate an opportunity for
improvement.
Figure 3: Box Plots

Move from Opportunities to Action
After analysts present the opportunity
analysis and the group agrees on improve-
ment initiatives to further explore, the finance
team should investigate these opportunities
to understand the population and financial
impact of any proposed action.
Together, the finance team, the analysts,
and care teams agree upon assumptions
based on a series of questions:

How is the care model changing?
To successfully reduce variation and improve
outcomes, it’s important for clinicians understand
any necessary changes to care models.

What are the steps needed to drive results?
The first part of any improvement initiative is to
identify what needs to be changed.
The second part is creating a concrete plan
with specific steps to the desired results.

How can the steps be tracked?
Tracking actions and progress is key to understanding
how and why a change initiative works (or doesn’t).
Throughout the process, organizations
should use a tracking system that records
steps taken and the results of those steps.

How will changes to patient care affect finances (positively or negatively)?
When weighing the costs versus the
benefits, it’s important for organizations
to consider that sometimes care
improvements hurt the bottom line,
but those improvement initiatives
should still be considered if the
benefits outweigh the costs.

Could this project be eligible for a pay for performance program?
Pay for performance (P4P) programs
can help recoup costs of a costly
care improvement initiative.
Many payers offer financial rewards
for outcome improvements, so
organizations may want to engage
with payers about the potential of
P4P eligibility.

Finance takes these assumptions and creates a
model to predict the impact to the bottom line.
This prediction should consider four factors:
Revenue loss
Increased bonus from payer (P4P)
Net gain
Improved outcomes
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Bringing It All Together
Improving healthcare delivery and
outcomes is a must for all health systems,
and conducting quarterly opportunity
analysis highlights areas that, so to speak,
offer the most bang for the buck.
Using data to perform an opportunity
analysis is an effective way to begin
rooting out and addressing unwarranted
clinical variation, which in turn can save
money while improving outcomes.

When designing an opportunity analysis process,
it’s important for analysts to remember the four
key steps:
Kicking off with preliminary analysis
Meeting with clinicians to gather input
Digging deeper into the data for further analysis
Presenting to decision makers
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Following these four basic steps and letting
the data be a guide helps analysts identify
and prioritize opportunities.
With effective data analysis and engaged
clinicians, organizations can find opportunities
for improvement initiatives that reduce
variation, save money, and improve care.
All these successes will benefit patients.

For more information:
“This book is a fantastic piece of work”
– Robert Lindeman MD, FAAP, Chief Physician Quality Officer

More about this topic
Link to original article for a more in-depth discussion.
Reducing Unwanted Variation in Healthcare Clears the Way for Outcomes Improvement
Josh Ferguson APRN, ACNP, ANP-BC, VP of Clinical Outcomes Improvement
Four Essential Ways Control Charts Guide Healthcare Improvement
Lloyd Provost
Opportunity Analysis Permits Successful Execution of At-Risk Contracts
Health Catalyst Success Story
Introducing The Next-Generation In Opportunity Analysis, Benchmarking And Improvement Prioritization
Aaron Neiderhiser, Product Management, Sr. Director
Professional Services: Opportunity Analysis
Health Catalyst Product

Matthew is a Finance Manager at Allina Health in Minneapolis, MN. He earned his B.S. from
Miami University in Oxford, OH. His department administrates the budget, rolling forecast,
productivity and cost accounting data for the system. Matt and his team leverage the patient
level cost accounting data to model the financial implications of care improvement processes
for the systems clinical service lines. He has worked closely with the Oncology, Surgical and
Value Based Care services to demonstrate financial opportunities across Allina.
Other Clinical Quality Improvement Resources
Click to read additional information at www.healthcatalyst.com
Matthew Brown – Finance Manager, Allina Health

Sarah Jenson is Director of Analytics at Allina Health and also at Health Catalyst. Sarah
aspires daily to help healthcare organizations drive improvement through data. She received
her Master’s in Sociology and has supported Allina Health’s analytics achievements for nearly
a decade, and continued in that role after Allina Health outsourced its analytics department to
Health Catalyst in 2015.
By creating a process to identify unwarranted clinical variation, she and her team have identified
millions of dollars in potential savings for Allina Health thought cost savings, lives saved, and quality
improvements – specifically this has resulted in reductions in Spine cost of care, improvements in
Stroke care delivery, and efficiencies in Sepsis treatment. Prior to her time at Allina Health, Sarah spent
several years working in healthcare market research helping insurance providers and healthcare
systems better understand their brand perception, gauge member onboarding processes, measure
patient experiences and outcomes, identify new market opportunities, as well as aiding in other
research needed to support key decisions at the highest level.
Sarah Jenson – Director, Analytics, Health Catalyst at Allina Health

Health Catalyst is a mission-driven data warehousing, analytics and outcomes-improvement company
that helps healthcare organizations of all sizes improve clinical, financial, and operational outcomes
needed to improve population health and accountable care. Our proven enterprise data warehouse
(EDW) and analytics platform helps improve quality, add efficiency and lower costs in support of more
than 65 million patients for organizations ranging from the largest US health system to forward-thinking
physician practices.
Health Catalyst was recently named as the leader in the enterprise healthcare BI market in
improvement by KLAS, and has received numerous best-place-to work awards including Modern
Healthcare in 2013, 2014, and 2015, as well as other recognitions such as “Best Place to work for
Millenials, and a “Best Perks for Women.”

Four Steps to Effective Opportunity Analysis

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