Based on a 2018 Healthcare Analytics Summit presentation, this report details the four phases necessary for successful healthcare data governance: Elevate a vision and agenda that align with organizational priorities. Establish an organizational structure to fulfill the data governance mandate. Execute with prioritized data governance projects, people and resource assignment, and disciplined focus on the work. Extend data governance investments and efforts through established practices. Each step must follow the core principles of stakeholder engagement, shared understanding, alignment, and focus. Effective healthcare data governance is not a one-time event and requires ongoing and iterative efforts.

1. Four Critical Phases for
Effective Healthcare
Data Governance

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Four Critical Phases for
Effective Healthcare Data Governance
This presentation is based on the 2018 Healthcare Analytics Summit
presentation by Thomas Burton and Mike Noke entitled, “The Data
Maze Game: Navigating the Complexities of Data Governance.”
Thomas Burton, MBA
Sr. VP, Professional Services &
Health Catalyst Co-Founder
Mike Noke
Sr. VP, Professional Services
Health Catalyst

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Four Critical Phases for
Effective Healthcare Data Governance
Data drives healthcare improvement and is
an imperative resource for navigating a
changing healthcare landscape.
It allows healthcare organizations to
evaluate how care is delivered and funded,
how patients are engaged and educated,
and how payers and providers can work
together to improve value.

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Four Critical Phases for
Effective Healthcare Data Governance
But healthcare data is complex, and it
can be difficult to leverage.
A principle-based approach to data,
through good data governance
practices, can bridge the gap.
Data governance allows organizations
to maximize the value of their data to
improve outcomes.

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Defining Healthcare Data Governance
Healthcare data governance is the discipline
of managing data as a strategic asset.
It paves the way for data to support
organizational priorities through the
orchestration of people, processes, and
technology.
Through a focus on enhanced decision-
making, data governance helps
organizational leaders improve clinical,
operational, and financial outcomes.

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Defining Healthcare Data Governance
Importantly, data governance is an
ongoing, enterprise-wide, cross-
functional effort to optimize data for the
benefit of patients, staff, and community.
Data governance cannot serve as an
end to itself—governance for
governance’s sake.
It will fail if approached with the “one
and done” mentality of a one-time event.
And it cannot be restricted to the IT
department in the organizational
hierarchy.

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Today’s Healthcare Challenges & Data Governance
Organizations urgently need data
governance to confront today’s challenges.
By ensuring that people have access to the
right data and information at the right time
and in the right format to make clinical and
business decisions, data governance
shows the value of organizational
investment in data.

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Today’s Healthcare Challenges & Data Governance
Too often, organizations face:
An inability to respond to new analytic use cases
and requirements.
Poor or unknown data quality; data that is siloed,
inaccurate, inconsistent, unstandardized, etc.
Lengthy and inaccurate decision cycles.
Inconsistent analytic results from different sources
attempting to answer the same question.
A lack of accountability or process for fixing
data quality problems.
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Today’s Healthcare Challenges & Data Governance
Each of these issues has negative implications
for organizations and their patients.
Through better data governance,
organizations can overcome financial
risks, operational inefficiencies, and
safety concerns to return value to the
entire system—patients included.

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Tomorrow’s Healthcare Imperatives and
Data Governance
Eventually, data governance will enable even
more transformation.
By maximizing the value of data through good
governance practices, organizations will be
able to see and use all factors that affect a
patient’s health, such as incorporating
socioeconomic and wearable data into the
hospital data ecosystem.

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Tomorrow’s Healthcare Imperatives and
Data Governance
The shift to value-based care drives the need for
reliable data that measure cost of care, margin,
and productivity across the continuum of care.
It also necessitates the ability for leaders to
evaluate the expected return on investments to
improve specific healthcare outcomes.

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Tomorrow’s Healthcare Imperatives and
Data Governance
Done well, data governance is an
accelerant to transformation.
It allows organizations to achieve the
breadth and speed of integration required
by healthcare reform, powered by clinical
and technical innovations, and vital for
improving the cost and quality of care for
patients and communities.

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Four Phases of Healthcare Data Governance
Strong data governance is built from four phases, all enabling improved
decision-making from the boardroom to the bedside.
ELEVATE
ESTABLISH
EXECUTE
EXTEND

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Four Phases of Healthcare Data Governance
The first phase for effective data governance
is to elevate governance in importance by
developing a vision and agenda that align
with organizational priorities.
The goal is to shift the perception of data
from an expensive technology to a
valuable resource.
PHASE ONE ― ELEVATE

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Four Phases of Healthcare Data Governance
As with any collaborative effort, it’s best to
begin with a shared understanding of the goals
and to define a limited, achievable, and
strategically targeted scope for the work.
Using an incremental approach, so
organizations can work on what matters most
first, this step promotes executive buy-in by
defining expected outcomes and
demonstrating how they relate to the
clinical and business activities central
to the organization’s strategic direction.
PHASE ONE ― ELEVATE

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Four Phases of Healthcare Data Governance
Building an organizational structure to fulfill
the data governance mandate helps
establish good governance practice.
Governing data is an effort that impacts
many groups across the system.
Getting organized and bringing the right
people and teams to the table is important
for the success of any new initiative.
PHASE TWO ― ESTABLISH

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Four Phases of Healthcare Data Governance
An organization’s approach to data governance
must overcome substantial complexities.
Often governance decisions sit at the
intersection of competing priorities (financial vs.
clinical vs. operational).
The governance team must be curated with
this cross-functionality in mind. Additionally,
resources for data governance are likely
limited, especially at first.
Ensuring the right people in the right groups
will help make the most of what’s available.
PHASE TWO ― ESTABLISH

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Four Phases of Healthcare Data Governance
Finally, organizations have different needs and
there’s no single, “one size fits all” template for
structuring data governance resources.
Leaders must work on establishing teams only
after a high-level agenda for data governance
is set.
Organizing people around the work that most
needs doing, rather than setting up teams that
then look for work, will help guide the way.
PHASE TWO ― ESTABLISH

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Four Phases of Healthcare Data Governance
Create prioritized data governance projects,
with people and resource assignments, to
execute the governance mandate.
The Data Governance Committee, created in
phase two, should sponsor a set of discrete
projects with unambiguous goals to support
disciplined focus on the work.
This project-portfolio approach helps break
the work into manageable units that can be
phased over time, and it allows for different
people to be called upon to support different
projects in the data governance portfolio.
PHASE THREE ― EXECUTE

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Four Phases of Healthcare Data Governance
Ensure data investments and efforts will last
and extend throughout the entire organization
into the future.
Establishing a set of practices to continually
support and improve data governance work
is important to ensure ongoing relevance
and value for the data governance portfolio
and to uphold the gains made early.
PHASE FOUR ― EXTEND

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Four Phases of Healthcare Data Governance
Data governance opportunities are seemingly
endless, but people’s time, energy, and focus
are limited.
Looking forward, organizations can bring new
energy and fresh perspectives into the
governance work that help build and continue
the momentum for achievement.
Continued investment in data governance
also helps to nurture a data-driven culture,
reinforcing desired behaviors across the
organization.
PHASE FOUR ― EXTEND

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Principles of Effective Healthcare Data Governance
Each data governance phase must incorporate four core principles to
support success, regardless of its specific structures or leadership:
STAKEHOLDER
ENGAGEMENT
SHARED
UNDERSTANDING
ALIGNMENT FOCUS

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Principles of Effective Healthcare Data Governance
Stakeholder Engagement
Organizations must move beyond the IT
department, and engage clinical, operational,
and financial stakeholders around an
awareness of data as a strategic asset—
highlighting its value for supporting better
decisions from the boardroom to the bedside.

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Principles of Effective Healthcare Data Governance
Shared Understanding
Promote the goals and accomplishments of
data governance across the organization and
nurture a data-driven culture.

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Principles of Effective Healthcare Data Governance
Alignment
Ensure that data governance clearly
supports the priorities and strategies of
the organization, serves the needs of
users throughout the data life cycle, and
balances polarities (apparent conflicts).

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Principles of Effective Healthcare Data Governance
Alignment
Organizational leaders should think lean
and do what matters most, then adjust as
the project advances.
It’s important to govern data to the least
extent necessary to achieve the greatest
common good.

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Effective Healthcare Data Governance Requires
Ongoing Transformation
Successful data governance is not a one-
time event.
These steps cannot be a one-off effort
because healthcare is continuing to
evolve and change; healthcare
organizations must be able to react.
As an ongoing and iterative process, data
governance is responsive to changing
circumstances, and enables leaders to
re-balance priorities to manage conflict.

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Effective Healthcare Data Governance Requires
Ongoing Transformation
Finally, data governance efforts must be
promoted by leaders, throughout the
organization, who emphasize a data-driven
culture and thinking of data as an asset to
the organization’s goals and improvement.

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For more information:
“This book is a fantastic piece of work”
– Robert Lindeman MD, FAAP, Chief Physician Quality Officer

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More about this topic
Link to original article for a more in-depth discussion.
Four Critical Phases for Effective Healthcare Data Governance
Effective Healthcare Data Governance: How One Hospital System is Managing its Data Assets to
Improve Outcomes ― Health Catalyst Success Story
Outcomes Improvement Governance: A Handbook for Success and Achieving More with Less
David Grauer, MBA, MHSA, SVP Professional Services; Tom Burton, President of Professional Service
7 Essential Practices for Data Governance in Healthcare
Dale Sanders, President of Technology
Demystifying Healthcare Data Governance: An Executive Report
Dale Sanders, President of Technology
3 Phases of Healthcare Data Governance in Analytics
Mike Doyle, Sales VP

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Other Clinical Quality Improvement Resources
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