Healthcare organizations are turning to the enterprise data warehouse (EDW) as the foundation of their analytics strategy. But simply implementing an EDW doesn’t guarantee an organization’s success. One obstacle organizations come up against is that their analytics team members don’t have the right skills to maximize the effectiveness of the EDW. The following six skills are essential for analytics team members: structured query language (SQL); the ability to perform export, transform, and load (ETL) processes; data modeling; data analysis; business intelligence (BI) reporting; and the ability to tell a story with data.

1. 6 Essential Data Analyst
Skills for Your Healthcare
Organization
― John Wadsworth

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Data Analyst Skillsets Drive Success
Smart healthcare groups are
turning to the enterprise data
warehouse (EDW) as the
foundation of their analytics
strategy to improve their
care delivery and cost.
But you need more than a
solid software foundation.
To fully leverage the EDW investment, you need to have
the right people with the right skills—strong healthcare data
analyst skills.

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Producers and Consumers of Data
and Information
Most healthcare workers will
never directly interact with an
EDW. They’ll never look for
trends by querying a database,
write reports or analyze data.
Someone else will actually pull
data from the EDW, analyze it,
and then produce a report.
These people are producers.
And the people that receive
these reports can be classified
as consumers.

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Producers and Consumers of Data
and Information
It’s common for health system
to invest millions of dollars and
multiple years into a data
warehouse and still have
dissatisfied consumers.
If the team lacks the skills to
manage and leverage an EDW,
it can create real problems for a
health system’s enterprise-wide
analytics strategy.

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6 Skills Healthcare Data Analysts Need
To support sustained outcomes
improvement, there are six skills
needed among staff members
(either analysts or architects)
tasked with analytics.
1. Structured query language
2. Export, transform, and load (ETL)
3. Data modeling
4. Data analysis
5. Business intelligence (BI) reporting
6. Telling the story of the visualizations

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6 Skills Healthcare Data Analysts Need
1: Structured query language
An analytics team member needs
to be able to talk directly to and
manipulate databases through
structured query language (SQL).
Highly experienced data analysts
should also bring skills with these
kinds of toolsets:
Microsoft Access GUI
Crystal Reports
A business intelligence (BI) tool

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6 Skills Healthcare Data Analysts Need
2: Export, transform, and load (ETL)
The data expert needs to be able to
perform export, transform, and load
(ETL) processes. Simply put, you
need to take data from one system
and put it into another.
In an EDW, a user pulls data from
disparate systems (e.g., EHRS,
finance, human resources) that
don’t talk to one another.
This movement of data is done
through the ETL process.

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6 Skills Healthcare Data Analysts Need
3: Data modeling
Data modeling is a fancy way to
say that you write code that
models real-world processes and
workflows.
Consider the needs for a hospital
admission process:
• Patient demographic data
• Insurance information
• Patient clinical history
• Admitting diagnosis
• Attending physician
• Other as-needed data

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6 Skills Healthcare Data Analysts Need
4: Data analysis
An analytics team member needs
to be able to make sense of the
data once it is in the EDW.
A good analyst using complex
thinking around set theory and
analysis through SQL, can extract
pertinent insights and drive cost
and quality improvements.

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6 Skills Healthcare Data Analysts Need
5: Business intelligence (BI) reporting
An analytics team member
needs to be able to present
data in a way that is intuitive
to nontechnical users.
The visual representation
must be simple to interpret
by a lay audience. This skill
separates an average
analyst from a stellar one.

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6 Skills Healthcare Data Analysts Need
6: Telling the story of the visualizations
The analytics team member
must be able to effectively
interpret and transmit the
stories embedded in the data.
BI reporting gives contextual
meaning in bits and pieces, or
a micro view. Telling the story
means providing a logical flow
that pulls together a coherent
story―a big picture view.

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Staffing Models for Skills Management
Staffing in healthcare is
primarily based on two models:
• Generalist model
• Specialist model
Specialists tend to focus on
their particular skillset where
data architect and analysts
within the generalist staffing
model may support a wider
range of functionality on
process improvement teams.

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Staffing Models for Skills Management
The important thing is expertise
across all of these skills within
the team.
Both generalist and specialist
staffing models can work as
long as:
1. The skill is covered with a high
degree of expertise
2. Coordination and handoffs
between technical team members
are seamless.

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Unlocking the Value of a Healthcare EDW
Ensuring coverage of all six
skills skills will help any
organization get the most
value out of their EDW.
Turning data into actionable
information is what good
analytics is all about: unlocking
data to drive meaningful,
sustainable change.

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More about this topic
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3 Frequent Mistakes in Healthcare Data Analytics
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Finding $5.7 Million with a Healthcare Data Warehouse
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Link to original article for a more in-depth discussion.
6 Essential DataAnalyst Skills for Your Healthcare Organization

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Other Clinical Quality Improvement Resources
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John Wadsworth joined Health Catalyst in September 2011 as a senior data architect.
Prior to Catalyst, he worked for Intermountain Healthcare and for ARUP Laboratories
as a data architect. John has a Master of Science degree in biomedical informatics
from the University of Utah, School of Medicine.