Using Improvement Science in Healthcare to Create True Change

Using Improvement Science in
Healthcare to Create True Change

© 2020 Health Catalyst
Proprietary. Feel free to share but we would appreciate a Health Catalyst citation.
Improvement Science in Healthcare
Today’s healthcare landscape is witnessing
exponential growth in healthcare data.
In the past, health systems were faced
with collecting, collating, and classifying
overwhelming amounts of data.
Now, health systems face a new
challenge—how to use that data to
drive improvement.

Although some healthcare leaders are
embracing new technological advances,
historically, healthcare has been slow to
adopt new technologies for a myriad of
reasons, including budget constraints
and regulatory burdens.

Another reason for the slow rate of
technology adoption is a health system’s
inability, or personnel lack of experience, to
effectively implement changes in practice,
including using the correct methods to
understand the impact of technology and
practice changes on outcomes.

Improvement Science in Healthcare Is the Answer
Improvement Science is one of the
answers to these common data and
technology challenges.
It allows for the scientific study about
which improvement strategy works
best in the complex system of healthcare.

Improvement Science in Healthcare Is the Answer
Healthcare teams can use improvement
science and analytics to understand how
to use theory to guide their practice as
they try something new.
To help determine which methods will
increase the likelihood of success, and
how an improvement team can know if
the changes they made lead to the
desired impact.

Leveraging Data to Identify Unwarranted
Clinical Variation
Unwarranted clinical variation is all too
common for healthcare systems; it occurs
when notable differences in medical
practice utilization can’t be explained by a
predisposition to illness, medical need, etc.
Although unwarranted clinical variation has
improved in the overall healthcare industry
overtime, it is still one of the biggest areas
in which health systems can improve.

Clinical Variation
In fact, it is estimated that unwarranted
clinical variation represents between $20
and $30 million dollars for every $1 billion
dollars in revenue, a huge financial
opportunity for providers.

Clinical Variation
To apply improvement science, understand
clinical variation, and take the right
measures to overcome this unwarranted
variation, healthcare leaders must
understand the two types of variation.
Common cause variation
Special cause variation
>
>

Clinical Variation
Common cause variation is a variation that is
inherent in a system (process or product) over
time; it affects everyone working in the system
and affects all outcomes of the system.
Special cause variation is not always a part of
the system and doesn’t affect everyone.
Special cause variation is attributable to a
specific cause and is nonrandom.

Clinical Variation
Real improvement effort requires that
leaders can recognize if the results are
inherent to the process (common cause
variation) or if they are due to some
identifiable cause (special cause variation).

Clinical Variation
If leaders aren’t able to identify the type of variation,
they can make one of two large mistakes:
1) Acting like something is a unique event
when it’s normal for the process, and
2) Ignoring issues that are special variation,
assuming the variation is normal.
Without the ability to display data/performance
over time, it is impossible to know if process
changes are producing the desired results.

Applying Improvement Science Model:
An 8-Step Improvement Model
The 8-step Improvement Science Model
(Figure 1) provides one approach for
applying improvement science in healthcare.
The key to improvement science is using
and applying a consistent model to drive
improvement and using meaningful data
in every step.

Figure 1. 8-Step Improvement Science Model.
?
Guiding Question
Do we understand
the problem?
1
Analyze the
Opportunity
and Define
the Problem
?
Guiding Question
Do we know where
we want to be?
2
Scope the
Opportunity
and Set
SMART Goals
?
Guiding Question
Do we know
the cause?
3
Explore Root
Causes and
Set SMART
Process Aims
?
Guiding Question
Do we know what
to change?
4
Design
Interventions
and Plan Initial
Implementation
?
Guiding Question
Have we applied
and measured
the change?
5
Implement
Interventions
and Measure
Results
?
Guiding Question
Did the changes result
in improvement?
6
Monitor, Adjust,
and Continually
Learn
?
Guiding Question
Are we sustaining
the gains?
7
Diffuse and
Sustain
?
Guiding Question
Have we
communicated
the results?
8
Communicate
Quantitative
and Qualitive
Results
Do we need to
reevaluate root
cause?
Do we need to
adjust our
interventions?
Is it an adoption
problem?
Is our data valid?

Step 1. Analyze the opportunity for improvement and define the problem.
The first step in tackling unwarranted clinical
variation is using data and analytic insights to
identify areas for opportunity.
Robust analytic capabilities are key to
identifying improvement opportunities.

A strong analytics platform with the ability to
aggregate data from a variety of sources,
including disparate EHRs, human resource
information systems, supply chain systems, and
revenue cycle systems, provides a complete
picture of a health system’s performance.

When leaders have access to comprehensive
data and analytic insight, they can accurately
identify problem areas, then focus on
improvement efforts to decrease unwarranted
clinical variation, improve quality, reduce
costs, and improve financial performance.

Step 2. Scope the opportunity and set SMART goals.
Analytics help health systems scope the size of
the improvement opportunity.
With the ability to dive deeper into the data,
health systems can drill down and understand
the depth and breadth of a problem.

Step 3. Explore root causes and set SMART process aims.
Access to specific, granular data allows leaders
to understand what is at the root cause of a
problem. Larger, high-level data sets are
helpful, but they don’t allow leaders to
understand the why behind specific problems.

For example, a health system experiencing
high catheter-associated urinary tract
infection (CAUTI) rates, needed more
nuanced data to understand what was
causing the increased rates.
With aggregated data from eight different
hospitals, leadership didn’t know if the
high CAUTI rates were occurring at all
hospitals or only a few.

When the health system obtained specific
data, it learned that the high rates were due
to several reasons, such as inconsistent
CAUTI insertion techniques, failures to
adhere to CAUTI maintenance bundle
compliance, and lack of proper routine
hygiene.

The root causes at the individual facilities
within the larger system varied, requiring
different improvement plans and
interventions at each location.
With this specific information, the health
system understood which problems it
needed to solve and put the appropriate
measures into place, subsequently reducing
the incidence of CAUTI systemwide.

Step 4. Design interventions and plan initial implementation.
Change concepts help prompt new ideas for
improvement by providing a basic framework
for improvement team members to consult
before making any drastic changes.
The change concepts list (Figure 2) is
based on common challenges that all
healthcare organizations face.
Therefore, if an improvement team is
struggling to identify one specific improve
ment opportunity, they can review the six
change concepts and the list can help
generate an improvement intervention.

Figure 2. Change Concepts to Improve Interventions.

Successful interventions also require the right
people to comprise the improvement team.
It is valuable to include system leadership,
day-to-day leadership, and the right technical
and clinical expertise.
But without engaging front-line staff—to
ensure that implementation steps are
realistic and fit within the workflow—
improvement teams and their
interventions will fail.

Before moving to implementation, teams
need to prepare the implementation plan.
Teams must ensure they understand the
current state, resources required for change,
and organizational readiness for change.
Improvement teams need to develop a
communication plan, provide training,
including onsite support, if needed.

Teams also need to determine how they will
measure impact of that intervention on the
outcome measures of interest, and track
performance over time.
When considering which intervention is best,
improvement teams increase the likelihood
of improving outcomes if they integrate a
model of evidence-based practice into the
analytics-driven improvement efforts.

Step 5. Implement interventions and measure results.
Many health systems use scorecards to
evaluate the effectiveness of their
improvement efforts.
While scorecards are important and promote
internal accountability, they are not the right
tool for measuring results.

When measuring improvement work, the
right measurement tool should be able to
answer the question, “Are we getting
better?”
To answer that question, we need to
understand common and special cause
variation, and need to visualize performance
over time—something run charts do well.

Run charts are simple to use, making it one
of the best tools to measure improvement.
A run chart provides a variety of benefits for
teams trying to measure improvement
success.
For example, a run chart (Figure 3) shows
improvement teams how well or how poorly
a process is performing at the start of the
improvement work.

Figure 3. Average length of stay run chart

Teams can apply the run chart rules to
determine when changes in the data are
actual improvements versus common
cause changes over time, and it offers
direction as team members work on
additional improvement projects.

Step 6. Monitor, adjust, and continually learn.
After an improvement team has implemented
the right intervention and selected the best way
to measure results, the team must stay focused
on that improvement effort.
Consistent monitoring and adjusting will allow
team members to make changes that allow
improvement efforts to reach their potential.

Step 6. Monitor, adjust, and continually learn.
Teams can continue to use a run chart to monitor
the effectiveness of improvement efforts.
If the run chart shows that improvements aren’t
happening, teams can immediately adjust
interventions quickly, reduce unnecessary waste,
and apply better-suited interventions.

Step 7. Diffuse and sustain.
Improvement science, combined with measure-
ment tools, empowers health systems to diffuse
and sustain gains.
One of the biggest challenges associated with
improvement work is sustainability, which is
often just as hard, if not harder, than making
the initial improvements.

With an improvement model that delivers the
desired outcomes and an experienced
improvement team, a health system can
spread its improvements to other areas of the
health system and avoid starting from scratch
when defining future improvement projects.

Because scalability is a common challenge
with improvement projects, it is important that
improvement teams—from the start of every
project—consider how the improvement
efforts can be replicated or tweaked slightly to
work for another part of the organization.

After a successful improvement project ends,
it is also important for the improvement team
to ensure sustainability over time.
This may take regular check-ins or continued
conversations with leaders, but it is a must-do
to keep improvement work going.

Step 8. Communicate Quantitative and Qualitative Results.
A valuable step that is often overlooked or
forgotten by improvement teams is communic-
ating results, whether good or bad.
Reporting results internally holds team
members accountable and acknowledges
the value of each team member’s work.
Acknowledgment can also motivate team
members to stay committed to (often)
challenging improvement work.

Step 8. Communicate Quantitative and Qualitative Results.
Sharing results is also a way to garner
executive support for current improvement
work and gain momentum for improvement
work in the future.
Improvement leaders also have a responsibility
to communicate what works so that other
departments can apply the same (or similar)
principles, accelerate improvement, and
benefit the patient populations they serve.

Improvement Science in Healthcare Yields
Return on Investment
Improvement science provides a valuable
framework for improvement efforts in the
complex world of healthcare, and analytics
is a key part of that framework.
Without the ability to deeply understand
performance through data, health
systems cannot improve

It’s also imperative for health systems to
select the right members to comprise the
improvement team and equally imperative
for the improvement team to understand
how to identify and validate improvement
through the right tools, such as a run chart.

Lastly, improvement team leaders must
communicate results to other team
members throughout the organization and
executive leadership to gain support for
improvement efforts and instill a sense of
accountability.
After all, improvement strategies and
roadmaps are only useful if team members
actually apply these new improvement
principles in their everyday work.

With so many challenges to tackle every
day, identifying areas for improvement and
executing an improvement plan can seem
daunting to healthcare leaders, but the
results are far worth it.
Effective improvement science in
healthcare can eliminate unwarranted
clinical variation, resulting in improved
outcomes for patients, improved financial
performance, and reduced costs of care.

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.
Using Improvement Science in Healthcare to Create True Change
Healthcare Quality Improvement: A Foundational Business Strategy
Health Catalyst Editors
The Top Six Examples of Quality Improvement in Healthcare
How to Run Your Healthcare Analytics Operation Like a Business
Dan LeSueur, Senior VP of Professional Services
Improving Strategic Engagement for Healthcare CIOs with Five Key Questions
Eric Denna, PhD; Ryan Smith, MBA, Senior VP and Executive Advisor
Four Critical Phases for Effective Healthcare Data Governance

Other Clinical Quality Improvement Resources
Click to read additional information at www.healthcatalyst.com
Heather Schoonover is a Vice President at Health Catalyst and is responsible for ensuring customer
outcomes, including the development of strategies for driving and communicating customer outcomes.
Heather has more than 20 years’ experience in nursing and healthcare. Prior to joining Health Catalyst,
Heather was the director of professional practice at PeaceHealth and was responsible for improving
patient safety and outcomes, organizational outcomes, leader and staff competency, and the nurse
practice environment. Heather has held adjunct nursing faculty positions and pro tem appointments on
the Washington State Nursing Care Quality Assurance Commission, the State regulatory board of nursing.
Heather obtained a Master of Nursing from Washington State University and is board certified by the American Nurses
Credentialing Center as a clinical nurse specialist in public and community health. Heather is a Clinical Nurse Specialist
Institute Fellow, and has been honored to be the recipient of leadership awards from both Sigma Theta Tau, the
International Honor Society for Nursing, and the Northwest Organization of Nurse Executives. Heather has more than
20 years’ experience in nursing and healthcare. Prior to joining Health Catalyst, Heather was the director of professional
practice at PeaceHealth and was responsible for improving patient safety and outcomes, organizational outcomes, leader
and staff competency, and the nurse practice environment. Heather has held adjunct nursing faculty positions and pro
tem appointments on the Washington State Nursing Care Quality Assurance Commission, the State regulatory board of
nursing. Heather obtained a Master of Nursing from Washington State University and is board certified by the American
Nurses Credentialing Center as a clinical nurse specialist in public and community health. Heather is a Clinical Nurse
Specialist Institute Fellow, and has been honored to be the recipient of leadership awards from both Sigma Theta Tau,
the International Honor Society for Nursing, and the Northwest Organization of Nurse Executives.
Heather Schoonover, MN, ARNP-CNS, PHCNS-BC, FCNS, Vice President

Other Clinical Quality Improvement Resources
Click to read additional information at www.healthcatalyst.com
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.”

Using Improvement Science in Healthcare to Create True Change

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to Using Improvement Science in Healthcare to Create True Change

Similar to Using Improvement Science in Healthcare to Create True Change (20)

More from Health Catalyst

More from Health Catalyst (20)

Recently uploaded

Recently uploaded (20)

Using Improvement Science in Healthcare to Create True Change