Deliver Data to Decision Makers: Two Important Strategies for Success

Deliver Data to Decision Makers:
Two Important Strategies for Success

© 2021 Health Catalyst
Proprietary. Feel free to share but we would appreciate a Health Catalyst citation.
This article is based on a 2020 Healthcare Analytics Summit (HAS 20
Virtual) presentation by Sy Johnson, Chief of Staff, Renown Health, titled,
“Success in the New Normal: Integrated Data to the Masses.”.
Deliver Data to Decision Makers
Sy Johnson, MBA
Chief of Staff,
Renown Health

If easy access to comprehensive data wasn’t a
priority for health systems before the pandemic,
it is now.
With the onset of the novel coronavirus,
healthcare leaders everywhere turned to
data to understand the impacts of COVID-19
(e.g., capacity planning and COVID-19 patient
and staff tracking) and inform decision making
such as directing patient flow and identifying
vulnerable patients.
A key part of the answer to these new
challenges was—and still is—accurate,
up-to-date data.

Data has always been critical for improving
healthcare delivery, even before the pandemic.
From operations to the clinical frontlines, health
systems have relied on data to measure the care
they deliver, identify care variation, and tailor
care delivery to each patient’s needs.
Without data, health systems resort to anecdotal
evidence and then make their best guess when
it comes to improvement efforts, often wasting
precious resources along the way.

While data is the bedrock to meaningful
change in any healthcare setting, it can only
drive systemwide improvement if it is available
across the health system and to decision
makers at every level of the organization.
A health system typically has access to data
but doesn’t always aggregate it from all
source systems and then make it available
to its end users, the point at which data
can drive real change.

By enhancing healthcare data integration that
increases access and availability to end users,
health systems can support data-driven
decisions and better frontline care.

Failure to Deliver Data to Decision
Makers Can Lead to Worse Care
Although data can be a powerful force for
positive change and better health, poor
data quality can lead to uniformed
decisions and worse outcomes.
When health systems lack efficient
healthcare data integration—the process
of compiling data from different sources
and increasing access to decision
makers—they are left to use whatever
data sets they can find, including
fragmented or incomplete data.

For example, if a nurse manager can’t
access data from a central source, she
might look in the EHR and pull a patient’s
data from the past six months.
However, because the EHR doesn’t
include data from all of the hospital’s
source systems, she would make care
decisions for the patient based on
piecemeal datasets.

Although the nurse manager made the best
decision with the data available to her, this
example highlights the need for decision
makers to have easy access to one,
comprehensive source of data, ensuring
that every person uses the same
information to make decisions.

Two Strategies for Effective, Mass
Healthcare Data Integration
Many end users think of cumbersome processes,
custom requests, and long turnaround times
when it comes to requesting data reports.
However, two strategies can help health
systems simplify the healthcare data integration
process and rapidly deliver the most relevant
data to end users:
Select Infrastructure That
Fits Most People’s Needs
Strategy #1
Ask the Right Questions
Strategy #2

Strategy #1: Select Infrastructure That Fits Most People’s Needs
Health systems should invest in data
infrastructure and capabilities that fit the
needs of most of their decision makers rather
than building a data solution for one person
or one group of people.
Data infrastructure that fits the decision
makers’ broader needs allows more people
to leverage data as soon as the infrastructure
is in place, avoiding delays often associated
with building customized options.

Strategy #1: Select Infrastructure That Fits Most People’s Needs
Data teams can rapidly scale a commercial
solution (e.g., the Health Catalyst Data
Operating System (DOS™)) that still permits
customization options as needed.
To find the best data infrastructure for the
health system, leaders should identify a
variety of the organization’s use cases and
then explore analytics solutions they can
swiftly apply to those use cases.

Strategy #2: Ask the Right Questions
Delivering data to decision makers starts when
data and analytic leaders ask the right questions
to identify which data will be most useful.
For example, data and analytic leaders should
assess which data sets end users can currently
access, then ask which additional data sets
they are requesting from data support teams
(e.g., what custom reports is IT generating).
Asking questions about additional data
requests will reveal which data sets team
members need but can’t access in their
decision-making process.

Once data teams have a deeper under-
standing of the organization’s data needs,
they can create a data report “menu” with
different data report options anyone in the
organization can order.
Leaders can think of a data menu as a
fast-food menu.

For example, a restaurant provides a menu
with different types of cheeseburgers that
customers can order.
Similarly, leaders can create a menu based
on the decision makers’ most common
requests/needs and use common language
that end users and technical team members
understand.

Creating a simplified data report menu
decreases custom report requests and
reduces delays in reports due to
misunderstandings from technical jargon.
Ordering data reports from a menu creates
a smoother transaction between end users
and technical team members.

Healthcare Data Integration: Two Use Cases
By applying the above two strategies, health
systems can understand gaps in data and
leverage that information to increase data
accessibility to team members in a crisis
(such as COVID-19) or in everyday
population health management.
The following two use cases show these data
integration strategies at work:
1. Respond to COVID-19
2. Improve Population Health Management

Use Case #1: Respond to COVID-19
COVID-19 underscored the need for
systemwide access to data in a crisis.
When the pandemic’s initial impacts (e.g.,
halted elective procedures) took effect in early
2020, health systems needed a high-level
view of the goings on throughout the hospital
to understand the virus’s ripple effects.

Without access to information from every
data source, leaders couldn’t proactively
manage the pandemic.
They had to react to different areas based
on disjointed data that failed to show how a
change in one area (e.g., ICU capacity)
would affect another area (e.g., emergency
department capacity).

To provide more comprehensive data for
the end users—especially during a
pandemic—a health system can ask team
members what information they need to
make decisions during the pandemic,
invest in data solutions that support these
needs, and then combine information from
all the appropriate sources.

For example, data teams could aggregate the
data from the EHR, the supply chain source
system, and any other source systems, based
on the datasets team members deem critical.
Then, the leadership team could use these
data sources to feed a central data dashboard
living in the incident command center.
This data display would serve as the main
source of truth to drive pandemic-response
decisions throughout the healthcare system.

Providing widespread access to the
command center central display is a way to
deliver data to the organization’s decision
makers at every level.
Not only do the decision makers have the
information they need to make educated
decisions about patient care, but they also
see the value that leadership places on
making data-informed decisions.

The health system can also add information
to the incident command center data display
that they consider vital for all team members
to know, such as such as COVID-19 volumes
and trends.
Leaders might consider adding other
COVID-19-related information, including
amounts of personal protective equipment,
staffing, lab supplies, and other information
health systems cannot access from only
one source system.

Use Case #2: Improve Population Health Management
Another example that conveys the value of
healthcare data integration is in population
health management.
To manage the health of patient groups,
population health depends on widespread
access to data to inform a unified approach
to better health.

When elective care went on hold in March
2020, health systems needed to ask the right
questions to identify the patients who were at
the highest risk for worse health due to the
unexpected changes in care.

For example, when health leaders sought to
understand how different departments were
impacted, they would learn that patients
receiving pulmonary rehabilitation couldn’t
continue their regular rehabilitation visits.
Health systems had to pivot in response to
the sudden change and learned to modify
services or find new ways to reach patients
with telehealth.

In this all-too-common scenario, many health
systems have turned to predictive models to
identify patients at higher risk for worse
outcomes or readmission based on the
disruption in routine care.
Ensuring the results from these predictive
models are available to decision makers
throughout the entire health system—with
the right data infrastructure—allows every
service line to identify their at-risk patients
and quickly implement interventions, such as
additional monitoring.

Effective Healthcare Data Integration
Results in Rapid Improvement
As data and data-based technologies (e.g.,
data displays) become more widely used
in healthcare, health systems must make
the data and supporting tools available to
their team members.
Data can’t reach its full potential—to inform
decisions that improve and restore patient
health—if end users can’t easily access it
at the point of decision making.

Effective Healthcare Data Integration
Results in Rapid Improvement
By asking questions and exploring team
members’ needs, leaders can invest in data
infrastructure that benefits the majority of end
users’ needs and create a simple menu that
team members can use to request data reports.
When leaders deliver data to the decision
makers when needed, they maximize data
in workflows, processes, and everyday
care delivery.

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.
The Right Way to Build Predictive Models for the Most Vulnerable Patient Populations
Why Data-Driven Healthcare Is the Best Defense Against COVID-19
Health Catalyst Editors
Healthcare Data Quality: Five Lessons Learned from COVID-19
Taylor Larsen, DOS Marts Data Quality, Director
Three Analytics Strategies to Drive Patient-Centered Care
To Safely Restart Elective Procedures, Look to the Data
Six Proven Methods to Combat COVID-19 with Real-World Analytics

Sy came to Reno from PeaceHealth in Vancouver, Wash. where he served as Chief
Executive Officer for the Columbia Network. In his role at Renown Health, Sy
oversees Renown’s hospital, employed physician and other healthcare services
operations as well as Renown’s owned health plan and other key administrative
functions. A national award-winning senior executive with over 20 years of healthcare
experience, Sy has a solid background in strategic, operational and financial business
planning; physician relationships and clinical integration; as well as a keen focus on
quality and patient service enhancement.
Other Clinical Quality Improvement Resources
Click to read additional information at www.healthcatalyst.com
Sy Johnson, MBA

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.”

Deliver Data to Decision Makers: Two Important Strategies for Success

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