The Top Four Skills of an Effective Healthcare Data Analyst

The Top Four
Skills of an
Effective
Healthcare
Data Analyst

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The Top Four Skills of an
Effective Healthcare Data Analyst
Data analysts play a critical role in empowering
health systems to make changes that drive
long-lasting improvement.
With big data sets to collate, interpret, and
translate, health systems rely on data analysts
to transform numbers on a spreadsheet into
meaningful insights that lead to change.

In 2020, with the unexpected onset of
COVID-19, the role of a data analyst
has become increasingly fundamental
to a health system’s ability to react
quickly and effectively to the pandemic.
While data analysts play a vital role in
enabling improvement within a health
system, they do not always have the
tools and support they need.

For example, a 2018 survey of data
analysts by data science company Kaggle
shows they spend the majority of their
time cleaning data rather than analyzing it.
As a result of overwhelming data support
needs—exacerbated by the pandemic due
to increased data-sharing and emerging
analytic needs—healthcare data analysts
spend most of their time on tasks that
don’t lead to real care transformation.

Four Skills Set Healthcare Data
Analysts Up for Success
Data analysts have many responsibilities,
including interpreting large data sets,
creating graphs and models, and
understanding interoperability.
However, this often means data analysts are
all-consumed with secondary tasks, making
it difficult to focus on their primary goal—
assisting organizational leaders in achieving
optimal healthcare management.

To unlock data to drive ongoing, meaningful
adjustments and quickly respond to market
changes, data analysts can stay focused on
top-of-license work with robust analytics
tools to offload basic responsibilities.
Sophisticated data and analytics tools can
help cleanse dirty data, optimize data
sharing and access, and centralize data into
one place (e.g., the Health Catalyst Data
Operating System (DOS™)).

The value of analytics tools goes beyond the
applications because it frees up analysts’ time
to focus on improvement and more rapidly
identify trends to drive business strategy.

Acquiring the following four skills, on top of having
data and analytics support tools in place, will help
data analysts perform at the top of their license,
avoid getting bogged down by rudimentary tasks,
and guide their organizations towards data-driven,
meaningful improvement:
1. Master the Foundational Competencies
2. Begin with the End in Mind
3. Focus on Problem Solving
4. Play the Data Detective

#1: Master the Foundational Competencies
Smart healthcare organizations rely on
healthcare analytics to guide care
improvement and delivery decisions
based on data insights.
Throughout the process of transforming
data into information, data analysts
must rely on their foundational compe-
tencies to unleash the data within their
organization’s analytics platform, a big
investment for any health system.

#1: Master the Foundational Competencies
Ensuring data analysts have six specific competencies allows healthcare organizations
to generate a return on investment for their data platform and maximize the data within
the analytics platform to direct the improvement-oriented changes:
Structured query language
(SQL): Communicating and
manipulating databases with
SQL provides a deeper
understanding of the data.
1
Export, transform, and load
(ETL): Aggregating data from
disparate sources into the data
platform allows for effective
data integration.
2
Data modeling: Modeling data
that reflects real-world
scenarios results in sustainable
processes and workflows.
3
Data analysis: Critical analysis
of the data reveals the most
valuable information and
insight.
4
Business intelligence reporting:
Translating complex data sets
into easy-to-read displays
allows all team members to use
data in decision making.
5
Tell the story of the visualiza-
tions: Piecing together data
fragments to tell the bigger
story.
6

#2: Begin with the End in Mind
After data analysts have mastered the
foundational skills, knowledge, and
experience to manage and analyze data,
what takes them to the next level?
Data analysts transition from good to great
when they keep the end goal in mind
throughout an entire project and derive
objective information for decision makers
along the way.

#2: Begin with the End in Mind
Data analysts can adopt two principles to begin with the end in mind:
Think critically: Critical thinking
skills make the difference
between answering a question
on the surface versus digging
deeper to figure out which
analysis provides the most value.
1
Build relationships: Building
and nurturing relationships with
decision makers allows an
analyst to delve more deeply
into the original inquiry and
understand the bigger picture,
possibly discovering more
context to help achieve the
end goal.
2

#3: Focus on Problem Solving
Rising costs, an increasing focus on population
health, alternative payment models, and COVID-
19 are a few reasons why healthcare is anything
but simple.
To manage this complexity, digitization is no
longer an option but an imperative.

At the heart of a digitized health system lies
a need for healthcare data analysts to
understand the system’s pressures, so their
analyses help leaders develop strategies to
improve care delivery and keep facility doors
open and profitable.
Analysts forecast volume, build dashboards,
and more, but their real value lies in their ability
to operate with a problem-solving mindset.

Too often, low-level tasks (e.g., building
dashboards, training other employees
about new technologies, and generating
one-off reports) encumber data analysts,
leaving little time for problem solving.
Although these tasks are part of the job, a
data analyst must be proactive in freeing
herself from focusing only on low-level work
by continually asking herself if she is
providing leaders with valuable information
that drives change.

Data analysts must use data to understand
a health system’s problems from an
operational, clinical, and financial angle.
With a comprehensive understanding of the
problem, the data analyst is prepared to
offer greater insights that lead to the right
course of resolution.

#4: Play the Data Detective
As data becomes more abundant in healthcare,
especially when organizations are emphasizing
interoperability to learn more about COVID-19,
so does the need for data detectives.
A healthcare data analyst assumes the role of
data detective by identifying new opportunities,
determining how to pursue them, and
leveraging data across all initiatives.

The data detective pieces together real-world
concepts within a database to build accurate
representations of a health system’s patient
population with data.
Then, the data detective analyzes and identifies
potential target areas for improvement within the
data construct and couples this analysis with a
subject matter expert’s viewpoint to decide the
best course of action.

Donning the data detective hat includes data
analysis, seeking expertise from team members,
and critically thinking about possible outcomes
or scenarios based on expansive information
from across the system to solve small and
large problems spanning the organization.

Healthcare Data Analysts Are Critical to
Outcomes Improvement
As health systems feel more pressure to
improve outcomes with limited resources,
respond to COVID-19, and generate revenue
on thin margins, data analysts keep health
systems on the right course and inform
leaders when they take a wrong turn.

Healthcare Data Analysts Are Critical to
Outcomes Improvement
If data analysts can avoid becoming all
consumed with secondary tasks—such as
data preparation and management—they can
transform data into meaningful information.
This information guides leaders to make
sound financial and clinical decisions that
allow the health system to reach peak
operational efficiency, even in the dire
times of a pandemic.

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 Top Four Skills of an Effective Healthcare Data Analyst
Three Must-Haves for a Successful Healthcare Data Strategy
David Grauer, MBA, MHSA, Sr. VP Professional Services
Healthcare Data Literacy: A Must-Have for Becoming a Data-Driven Organization
Anna Kleckner, PhD, MPH, Business Consultant
Five Practical Steps Towards Healthcare Data Governance
Stephen Hess
Five Lessons for Building Adaptive Healthcare Data Models that Support Innovation
Mike Dow, Technical Director
A Roadmap for Optimizing Clinical Decision Support
Health Catalyst Editors

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
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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
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The Top Four Skills of an Effective Healthcare Data Analyst

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