Poor healthcare data stewardship is part of the problem for health systems that feel like they are “data rich and information poor.” But this can be fixed two ways: implementing a data warehouse and improving data stewardship. Without appropriate healthcare data stewardship, even the best infrastructures become underutilized and poorly understood by knowledge workers who could be generating value with the data every day. Data stewards will become critical partners to the data warehouse team in creating a thriving user base. They are the data librarians who advise and guide users, and help them get the most value out of the enterprise data warehouse.

1. Healthcare Data Stewardship:
The Key to Going from Information Poor
to Information Rich
By Eric Just
© 2014 Health Catalyst
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© 2014 Health Catalyst
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Proprietary. Feel free to share but we would appreciate a Health Catalyst citation.

2. “We are data rich and
information poor.”
© 2014 Health Catalyst
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Data vs. Information
We hear this often from health
systems with years of data
collection and have terabytes of
stockpiled data.
There are two key components to
turning that data into information.
1. Ready access – Using a solid a
healthcare analytics system to
provide access and
accountability
2. Good healthcare data
stewardship
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Healthcare Data Stewardship
Data stewardship is the aspect
of healthcare data governance
that focuses on providing the
appropriate access to users,
helping users to understand the
data, and owns the data quality.
With poor data stewardship
even the best infrastructures
become underutilized and
poorly understood by
knowledge workers who could
be generating value from the
data every day.
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4. Who Should be the Data Steward?
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Because no single person can know
everything about every system, it’s
best to have many data stewards —
at least one for every major source
of data in the organization.
The best person to perform this role
is the person who knows the most
about how and why the data is
collected in each of the various
source systems.
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Data Steward Tools for Success
Once you’ve identified who
should become data stewards,
there are a few things they will
need to succeed.
First, make sure there’s a good
data warehouse architecture.
This will promote good data
stewardship because it will
eliminate the fragmented data
systems.
A centralized data warehouse
delivers a single reporting
platform and point of entry into
an organized repository of data.
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Data Steward Tools for Success
Provide the data stewards with
a solid set of metadata tools.
These tools will allow stewards
to share their knowledge about
the data mart or marts they are
responsible for.
Metadata tools that allow data
stewards and users to create
and edit descriptions for objects
in the data warehouse provide
this forum and will aid in
creating a self-sufficient data
warehouse user community.
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Creating Long-term Value using
Data Stewardship
Once the data is unlocked in an
EDW, the best way to create
long-term value is to have a
thriving user base.
Data stewards are critical
partners to the data warehouse
team in creating the user base.
They are the data librarians
who advise and guide users,
and help them get the most
value out of the EDW.
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8. Data Warehouse Tools: Faster Time-to-Value for Your Healthcare Data Warehouse
Doug Adamson, Vice President and Chief Technical Officer
© 2014 Health Catalyst
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More about this topic
7 Essential Practices for Data Governance in Healthcare
Dale Sanders, Senior Vice President, Strategy
6 Reasons Why Healthcare Data Warehouses Fail
Steve Barlow, Co-Founder and Senior VP of Client Ops
Five Reasons Healthcare Data Is Different
Dan LeSueur, Technical Director
It All Starts with a Data Warehouse: A Detailed Technical Overview
Dale Sanders, Senior Vice President, Strategy
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For more information:
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10. Other Clinical Quality Improvement Resources
© 2013 Health Catalyst
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Eric Just joined the Health Catalyst family in August of 2011 as Vice
President of Technology, bringing over 10 years of biomedical informatics
experience. Prior to Catalyst, he managed the research arm of the
Northwestern Medical Data Warehouse at Northwestern University's Feinberg
School of Medicine. In this role, he led the development of technology, processes,
and teams to leverage the clinical data warehouse.
Previously, as a senior data architect, he helped create the data warehouse
technical foundation and innovated new ways to extract and load medical data. In
addition, he led the development effort for a genome database. Eric holds a Master
of Science in Chemistry from Northwestern University and a Bachelors of Science in
Chemistry from the College of William and Mary.