1. Reducing Unwanted Variation in
Healthcare Clears the Way for
Outcomes Improvement

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Reducing Unwanted Variation in Healthcare
Variation—in clinical workflow efficiencies,
processes, and more—is one of the biggest
challenges healthcare organizations face in
outcomes improvement work.
Healthcare isn’t alone—variation is considered
a common foe across many industries.
Consider the words of an early quality pioneer:
Uncontrolled variation is the
enemy of quality.”
W. Edwards Deming
Basic Statistical Tools for Improving Quality

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Reducing Unwanted Variation in Healthcare
Today, healthcare is increasingly recognizing
the relationship between reducing variation
and improving outcomes.
Interventions to reduce variation for a targeted
process can improve care by establishing
consistency based on best practices.
The industry’s evolving data capabilities,
such as Late-Binding™ technology, are
expanding health systems’ ability to reduce
variation in delivery.

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Reducing Unwanted Variation in Healthcare
Creating new protocols, however, such as
bundles of care and care processes based
on best practices, is only one step toward
reduced variation.
Organizations also need to develop strong
analytic solutions to evaluate effectiveness
of these outcomes improvement initiatives.
Perhaps just as importantly, they must also
create methods to track the decision-making
process and rationale in instances when
these initiatives are not followed.

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Healthcare Variation Is an Improvement Opportunity
The ability to identify the type of variation, as
well as when it occurs and why, is fundamental
for healthcare improvement.
Patients frequently present to clinics or hospitals
with varying degrees of complexity and other
unique circumstances.
Consider the following example:

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Healthcare Variation Is an Improvement Opportunity
Two patients go to the emergency department (ED) with pneumonia.
PATIENT ONE
History of renal failure
and severe chronic
obstructive pulmonary
disease (COPD)
PATIENT TWO
No significant
comorbidities
The ED physician will likely
treat each patient differently.
This can include the use of
distinct antibiotics, based on
types of bacteria associated
with severe COPD.
Each patient may receive
antibiotic treatment at different
dosages and frequencies.

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Healthcare Variation Is an Improvement Opportunity
The type of variation described—in which
care is altered to serve the needs of a
specific patient—is considered appropriate,
or intended, variation.
Conversely, if the patient with renal failure
and CPOD were treated in the same way as
the patient without these comorbidities (with
the same antibiotics at the same dose and
frequency), then they might be at risk of
another form of variation: unintended, or
unwanted, variation.

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Healthcare Variation Is an Improvement Opportunity
This form of variation occurs because the
patient was not treated per their specific needs.
As such, unwanted variation is responsible for
suboptimal outcomes, including increased
morbidity and mortality.
The opportunity to reduce variation in outcomes
improvement work lies in unwanted variation:
by working towards data-driven best practices
that reduce variation, health systems further
quality improvement by taking actions that
support better care and reduced cost.

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Healthcare Variation Is an Improvement Opportunity
The Institute for Healthcare Improvement (IHI)
describes variation as a common culprit behind
burdens in the healthcare system:
Many quality and cost problems in a
process or product are due to variation…
“The process that produces 95 percent on-
time delivery or good product is the same
process that produces the other 5 percent
late deliveries or bad product.”

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Healthcare Variation Is an Improvement Opportunity
To improve quality and lower cost, health
systems need to identify the causes of
unwarranted variation in outcomes, and
develop ways to manage them.
A failure to combine analytics with best
practices and adoption principles can
result in suboptimal outcomes and higher
costs—which directly oppose the goals of
healthcare improvement.

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Reducing Variation in Healthcare Demands More
than Standardization
A natural answer to overcoming variation
is standardization. Systems, however,
need to be cautious about how they
employ standardization.
A blanket standardized approach can be
too much of a “cookbook”—a collection
of instructions and precise measure-
ments that don’t account for differences
in patients, facilities, and resources.
Clinicians will encounter cases that
initially appear similar, but—after a
closer look—have more variables that
call for a modification in care.

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Reducing Variation in Healthcare Demands More
than Standardization
Interventions are often initially based
on the Pareto principle (also known
as the “80/20” rule), which identifies a
limited number of input factors that
will have the greatest impact on output.
The Pareto principle maintains that
80 percent of the output from a
situation or system is determined
by 20 percent of the input.

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Reducing Variation Also Demands Analytics
Healthcare analytics plays a critical role in
reducing variation in healthcare by
revealing actionable information.
This includes indicators, such as if
facilities are adhering to best practices, if
interventions are effective, and specific
details about individual patients.
As leaders assess variation in their
organization, they may use a control chart
to provide a robust ability to determine
how closely a process is being followed as
it was designed.

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Reducing Variation Also Demands Analytics
Control charts monitor the extent to
which variation is occurring.
They also determine if the variation is
caused by sources common (stable
and predictable) to the process, or if
it’s the result of special causes
(unpredicted events or processes that
are significantly different from usual
practices).

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Reducing Variation Also Demands Analytics
For example, a certain hospital is in a region
participating in the CMS Comprehensive
Care for Joint Replacement payment model.
The hospital’s Outcomes Improvement
Team is working to improve the quality of
care for patients having a total hip or total
knee replacement surgery.
They are currently focusing on a process
to ensure that patients with diabetes
have a preoperative hemoglobin A1C
result to confirm that their diabetes is
being controlled.

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Reducing Variation Also Demands Analytics
Recently, a patient who underwent a total
hip replacement was slow to recover
following hospitalization.
The patient was discharged to a skilled
nursing facility (SNF), where they had a
prolonged stay due to post-operative
surgical site infection.
Thanks to a strong outcomes improve-
ment structure, the team was able review
information in addition to content present
within their own EMR.

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Reducing Variation Also Demands Analytics
They identified that there had not been a
preoperative hemoglobin A1c.
In addition, the patient’s primary care
provider’s EMR showed a history of
poorly controlled diabetes.
Thanks to the team’s ability to identify
where in the delivery of care the
variation occurred, the team could
improve their messaging and process to
ensure that all patients with diabetes
have a hemoglobin A1c prior to surgery.

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Reducing Variation Also Demands Analytics
The outcome improvement process might
start with a group representing a portion of a
population, and improvement teams could
alter that over time as they add data from
more of the population.
Using risk stratification tools, they can stratify
patients to make the best use of scarce
resources by targeting high-risk, high-cost
patients who need more aggressive care.

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To Effectively Reduce Variation, Teams Must
Come Together from the Ground Up
Health systems can dramatically impact
outcomes by shifting the focus of the
entire organization to make improvement
a common goal.
As teams from across systems and
facilities begin to work together, success
is often more efficient and robust.
Cohesiveness is built when sites and
departments share information—
particularly successes—around a
common improvement goal.

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To Effectively Reduce Variation, Teams Must
Come Together from the Ground Up
In addition, frontline clinicians must feel
supported when they diverge from a
certain process.
One of the most important things
improvement teams can do in inter-
vention design is consider how to
capture and identify clinician rationale
around intended variation.
By incorporating frontline judgement,
improvement teams can continue to
improve and refine their interventions
over time.

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To Effectively Reduce Variation, Teams Must
Come Together from the Ground Up
Throughout systems with multiple
facilities, there can be a dramatic
difference in how care is delivered.
These systems must remove
unintended types of variations so that
all facilities can achieve a similar
degree of success.
The fundamental goal is to work
across facilities to enable patients to
receive exceptional care anywhere in
the system.

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To Effectively Reduce Variation, Teams Must
Come Together from the Ground Up
Open communication and productive
relationships among staff and team
members across facilities is a critical
step in this process.
As these individuals come together
and form cohesive team structures,
they can achieve goals that once might
have previously seemed impossible.
This is the power and principle of
reducing variation to achieve
sustained outcomes improvement.

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Three Steps to Improving Care by Reducing
Unwanted Variation
Once health systems have identified and
formed outcome improvement teams, they
can improve outcomes by taking three
steps to reduce unwanted variation:
1) Remove obstacles
2) Maintain communication
3) Decrease variation

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Three Steps to Improving Care by Reducing
Unwanted Variation
Step 1: Remove Obstacles to Success on a Communitywide Level
This principle is particularly important for
health systems that have multiple facilities,
within which the way care is delivered can vary.
There may be some intended variation
between facilities in the same system (e.g.,
location, staffing, and resources), but by
reducing variation, they can all adopt the same
fundamental strategy.
The goal is to work across facilities to enable
high-quality care for all patients, no matter
where they are treated.

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Three Steps to Improving Care by Reducing
Unwanted Variation
Step 1: Remove Obstacles to Success on a Communitywide Level
This objective requires open, system-wide
communication and productive relationships
among frontline staff and members of the
outcomes improvement team.
It can help teams from different sites and
departments to understand that other groups
have faced similar struggles.
It’s a sense of inclusion that reminds disparate
groups that reducing variation in healthcare is
not a competition between entities, but rather a
unified effort towards improvement.

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Three Steps to Improving Care by Reducing
Unwanted Variation
Step 2: Maintain Open Lines of Communication/Share Lessons Learned
As health systems look to reduce variation in
care, one of the most important things they can
do is share success stories.
Disclose strides towards improvement—large
and small—among staff at the department and
facility level, and among the greater healthcare
community (between health systems).
Make routine announcements—in the form e-
mails, newsletters, or meetings—a standard
step in the initiative to reduce variation.

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Three Steps to Improving Care by Reducing
Unwanted Variation
Step 3: Decrease the Magnitude of Variation
Health systems deliver care to patients with
intended variation—as determined by
comorbidities, personal factors, etc.
They might start with an intervention focused
on a population or portion of a population and
alter the intervention over time to reduce
variation, they gain experience and expertise.
By decreasing the extent of variation in care
delivery, coupled with continued tracking of
processes and interventions, teams can
quickly identify and address issues.

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Reducing Variation: A Critical Starting Point for
Outcomes Improvement
Healthcare systems face many trials as they
work towards outcomes improvement—from
creating a strong governance and team
structure, incorporating best practices, and
building a strong analytic system, while
ensuring organizational and financial alignment.
Each of these challenges makes up the journey
of outcomes improvement. Reducing variation
persists along the entire journey, as it shows
health systems where their opportunity for
improvement lies.

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

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More about this topic
Link to original article for a more in-depth discussion.
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Josh Ferguson joined Health Catalyst in May 2015 as a Clinical Advanced Application Content
and Deployment Director. Prior to coming to Health Catalyst, Josh worked at Intermountain
Healthcare for over 17 years in a variety of capacities including: Medical Knowledge Engineer,
Clinical Implementation Coordinator, Respiratory ICU Nurse Practitioner, and a nurse in the
ICU, acute rehab and transitional care units. Josh earned his Master’s degree in Nursing from
the University of Washington.
While attending the UW, he completed the course work for 3 different tracks including: Adult Acute Care
Nurse Practitioner, Clinical Nurse Specialist, and Nursing Educator. His baccalaureate degree is in Nursing
and Human Performance Management from Weber State University.
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