1. Population Health Success:
Three Ways to Leverage Data

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Population Health Success
The United States spends more
money on healthcare than any
other country, but its outcomes are
poor compared to nations with
significantly lower expenditures.

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Population Health Success
Population health management is
gaining traction as a way to close the
spending-quality gap by improving
health outcomes on a population level
while also reducing healthcare
expenses, in line with the ongoing
shift from volume to value and quality-
driven CMS reimbursements.

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Population Health Success
To realize these population health goals,
organizations must rely on actionable
data to manage patients with chronic
disease, focus on prevention, and apply
the right interventions to help patients
reach and maintain optimum health.

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Three Ways Comprehensive Data Access
Drives Favorable Population Health Results
Many health systems lack access to
accurate, real-time data, making it
challenging to manage the health of
significant populations effectively.
Care teams often must base
decisions on outdated data with no
way to measure the effectiveness
of their improvements.

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Three Ways Comprehensive Data Access
Drives Favorable Population Health Results
A comprehensive analytics platform,
such as the Health Catalyst Data
Operating System (DOS™), can
improve data access and quality for
health systems, enabling organizations
to focus on improving population health
efforts with confidence that the data
behind their decisions is accurate,
reliable, and up to date.

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Access to Timely Data Lays the Groundwork
for Success in Value-Based Care
Without a reliable analytics platform,
accessing the “latest” data isn’t possible.
For example, it can take some health
systems up to six weeks on average to
review data reports.
The delay means the data is out of date
by the time the decision maker sees it,
forcing leaders to make decisions based
on outdated information.

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Access to Timely Data Lays the Groundwork
for Success in Value-Based Care
Delayed data is also a roadblock to
effective value-based care because it
makes it difficult for health systems to
respond to new, upcoming legislation.
For example, before the University of
Texas Medical Branch (UTMB Health)
implemented DOS, decision makers
had to wait over one month on average
to access data.

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Access to Timely Data Lays the Groundwork
for Success in Value-Based Care
The lack of timely data made it difficult for
UTMB Health to respond to the new Medicaid
1115 Waiver in Texas—Delivery System Reform
Incentive Payment (DSRIP) performance—an
alternative reimbursement model based on
outcomes for Medicaid and low-income,
uninsured patients.

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Access to Timely Data Lays the Groundwork
for Success in Value-Based Care
With a comprehensive analytics platform
to produce up-to-date analytics (e.g.,
DOS), population health teams can
measure success in value-based
performance.
In this case, UTMB used timely data to
determine which strategies achieved the
desired results to improve DSRIP
performance metrics and saved $2.1
million in additional pay-for-performance
dollars and improved performance
measures by 72 percent.

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Improved Care Coordination Improves
Patient Outcomes
Another common challenge population
health teams face is leveraging data to
improve poor care coordination, which can
lead to worse outcomes.
Many health systems lack the data
infrastructure and tools to identify gaps in
the care continuum, making it difficult to
pinpoint the problem and create a solution.

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Improved Care Coordination Improves
Patient Outcomes
One of the opportunities for care coordina-
tion care teams often overlook is increasing
clinician engagement and input.
Providers play a crucial role in delivering
quality care to populations, but health
systems need to have the tools to
measure clinician engagement to
identify it as a problem.

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Improved Care Coordination Improves
Patient Outcomes
When population health teams leverage
data to drive not only patient stratification,
workflow, and interventions but measure
clinician engagement, they can implement
the right processes to increase engage-
ment and therefore improve care
coordination and delivery.

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Improved Care Coordination Improves
Patient Outcomes
For instance, MultiCare Health System’s
Pulse Heart Institute (Pulse Heart)
improved cardiovascular outcomes by
enhancing care team coordination.
After implementing a robust analytics
platform that offered widespread access
to meaningful data around care team
performance, providers were engaged
more and aligned better with overall
strategies.

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Improved Care Coordination Improves
Patient Outcomes
Improved clinician engagement and
organizational alignment—which access
to analytic insights drove—helped
MultiCare generate $48,000 in revenue
and increase overall market share in
every submarket.

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Accurate Data Reveals Need for
Patient-Centric Programs
After population health teams have
stratified patient groups and studied
each group, they have an idea which
interventions or treatments the
patients need.
However, without accurate data, care
teams can’t know for sure that they
are targeting appropriate groups
according to a specific illness.

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Accurate Data Reveals Need for
Patient-Centric Programs
With healthcare delivery so fluid, even
processes that have been effective for
years might not work in the future,
making it critical for health systems to
evaluate interventions and measure
progress continually.

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Accurate Data Reveals Need for
Patient-Centric Programs
For example, after Allina Health identified
patients with Type 2 diabetes, it needed to
optimize its diabetes self-management
program to more effectively meet the needs
of patients across 42 different clinics.
To better align limited resources and meet
patient demand while also maintaining high-
quality clinical outcomes, the care team
needed accurate analytics.

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Accurate Data Reveals Need for
Patient-Centric Programs
With an analytics engine that acted as one
source of analytics truth for Allina Health’s
data, the health system better understood
what changes to make in the new process
and how to measure effectiveness.
Its data-informed diabetes self-management
program sustained an average 13.4 percent
reduction in HbA1c, completed 1,567 more
visits, and generated $142,000 in new net
revenue during its first year.

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Data Proves Essential in
Population Health Success
As health systems closely examine the
challenges of the populations they manage,
they must base care decisions on near real-
time, accurate data.
For providers to make data-informed decisions
that have far-reaching effects on the health and
well-being of significant patient populations,
health systems can’t afford to rely on outdated,
siloed data that doesn’t offer the big picture.

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Data Proves Essential in
Population Health Success
As reimbursements focus more on quality
over quantity and resources grow scarce,
reliable, actionable data is a critical piece
in the population health success puzzle.

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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.
Population Health Success: Three Ways to Leverage Data
Four Population Health Management Strategies that Help Organizations Improve Outcomes
Holly Rimmasch, Chief Clinical Officer
Succeeding in Population Health Management: Why the Right Tools Matter
Amy Flaster, MD, MBA, Senior VP, Population Health Management and Care Management
Eric Just, Senior VP and General Manager, Product Development
Achieving Stakeholder Engagement: A Population Health Management Imperative
Health Catalyst Editors
Identifying Vulnerable Patients and Why They Matter
KimSu Marder, RN, CCM, Lead Care Manager
Three Must-Haves for a Successful Healthcare Data Strategy
David Grauer, MBA, MHSA, Senior Vice President Professional Services

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