Three analytics strategies enable health systems to focus on patients while also meeting the financial standards for VBC delivery: 1. Prioritize patient outreach by risk level. 2. Deploy data tools to combat COVID-19. 3. Promote data literacy.

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Three Analytics
Strategies to Drive
Patient-Centered Care

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This report is based on a 2020
Healthcare Analytics Summit (HAS 20 Virtual)
presentation by Tyler Gauthier, MHA, CPHQ,
CSM, Director of Value-Based Care, OneCare
Vermont, and Katelyn Muir, CPQH, CSM,
MPH, Supervisor of Population Health
Analytics, OneCare Vermont, titled,
“Prioritizing the Patient in Value-Based Care:
A Data-Informed Approach.”

3. Article
Summary
The cost of uncoordinated care that fails to prioritize patient
needs is estimated to be over $27.2 billion. One of the primary
reasons behind these wasted healthcare dollars is a failure to
effectively leverage data to understand patient needs— a must-
have to deliver patient-centered, value-based care (VBC).
Three analytics strategies enable health systems to focus
on patients while also meeting the financial standards for
VBC delivery:
1 2 3
Detailed information from comprehensive data sets allows
health systems to understand patient needs at a granular level
and then use that insight to drive care decisions. More informed
care ensures health systems are also meeting the core elements
of VBC—managing costs, delivering quality, and ensuring an
excellent patient experience.
Prioritize patient
outreach by risk level.
Deploy data tools to
combat COVID-19.
Promote data
literacy.

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Curb Healthcare’s Rising Costs
In an attempt to curb healthcare’s rising costs, CMS is increasing the pressure on health systems to
deliver and measure value with value-based care (VBC). One way CMS is promoting this value-driven
healthcare model is by offering health systems and providers financial incentives to work more
closely together and better coordinate care through formal networks, such as ACOs. Even without
CMS’s financial incentives, organizations already feel the pressure to eliminate uncoordinated care,
costing health systems between:
Financial Incentives
$27.2 billion and $78.2 billion a year.

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Curb Healthcare’s Rising Costs
As more health systems shift from fee-for-service
to value-based payments, they struggle to balance
the financial focus of VBC with the patient-focused
needs of clinical care. Managing rising costs and
meeting criteria to qualify for reimbursements and
bonuses can easily distract from prioritizing
patients in a value-based landscape.
Shift From Fee-For-Service to Value-Based Payments

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Curb Healthcare’s Rising Costs
However, in spite of competing priorities, health systems can rely on data to manage the financial
demands of value-based payment models and ensure patient-centric care. Access to accurate,
comprehensive patient data allows care teams to understand complex patient populations and
tailor care delivery to unique patient needs while also meeting the criteria for reimbursement in
value-based contracts.
Data to Manage the Financial Demands

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Prioritize Patients with Comprehensive
Data and a Patient-Centered Care Model

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Aggregated Data in One Place
With a variety of data sources (e.g., claims, clinical,
social determinates of health) across multiple
locations, health systems must first aggregate all of
their data into one place. Without comprehensive data
in one place, leaders deliver care based on disjointed,
incomplete data. Having aggregated data in one place
also means every provider can make decisions based
on the same data (e.g., a shared MRI)—even when
patients receive care at different facilities.
Data Sources

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Patient-Centered Care Delivery Model
With data driving a patient-centered care
delivery model, and providers and resources
supporting patients, patient needs guide care
priorities and resource allotment (versus
team members’ opinions or budget numbers
driving care decisions). Health systems should
use the patient-centric support model as a
systemwide reminder that every initiative,
strategy, and goal must focus on the patient.
Patient Focused

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Patient-Centered Care Delivery Model
A patient-centered care model also allows health
systems to identify patient-centered metrics to help
them reach targets and evaluate current and future
interventions’ effectiveness. Without patient-focused
metrics that align with the care model, health
systems fail to accurately measure value. Relying on
data-driven insights aligned with a patient-centered
care model helps organizations meet the stringent
standards of VBC reimbursements (e.g., target rates
for low hospital readmission). A data-driven approach
also helps team members stay in sync with strategic
goals because they understand the value of data, the
role it plays in delivering patient-centered care, and
how the organization uses data to define success.
Data-Driven Approach

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Three Analytics Strategies to Keep the
Spotlight on Patient-Centered Care

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Analytics Strategies
As health systems continually learn the best way to prioritize patient-centered care while
simultaneously managing the financial demands of VBC, they can rely on three analytics
strategies to keep them on track:
Keeping the Spotlight on Patient-Centered Care
1 2 3
Prioritize
patient outreach
by risk level.
Deploy data tools
to combat
COVID-19.
Promote data
literacy.

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#1 Prioritize Patient Outreach by Risk Level
Leadership teams set targets and goals based on risk stratification that reveals the highest-risk
patients (e.g., comorbidities by zip code), who are candidates for outreach. With data-driven
insight into at-risk populations, care teams can focus on effective care coordination and early
care management interventions targeted to these populations’ needs.
Target Populations’ Needs

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#1 Prioritize Patient Outreach by Risk Level
Using data to understand the health of
patients is imperative to managing large
populations. Accurate, comprehensive patient
data allows care teams to track and identify
risk trends over time. Reviewing and
identifying data-informed trends enables
health systems to proactively address health
concerns and provide preventive solutions in
at-risk areas. For example, if a specific group of
people based in one area code shows signs of
prediabetes, a health system could implement
preventive measures and additional health
monitoring in that community.
Identify Risk Trends

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#2 Deploy Data Tools to Combat COVID-19
Although COVID-19 has brought
unprecedented challenges, health systems
that prioritized data- and patient-centric
strategies before the pandemic have been
more prepared to respond to the outbreak.
With team members already analytics
versed, these health systems focused on
deploying data-driven tools to identify
patients with the highest risk of
contracting COVID-19, rather than first
educating team members about the need
for data in identifying at-risk patients and
then developing the tracking tools.
Data-Driven Tools

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#2 Deploy Data Tools to Combat COVID-19
Certain health systems responded to the virus better than others by developing data-informed
tools and processes soon after the onset of COVID-19. The fast response prevented the spread of
COVID-19 and proactively protected communities by monitoring exposure through pandemic
support tools, such as contact tracing.
Proactively Protect

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#2 Deploy Data Tools to Combat COVID-19
Because COVID-19 is novel, there is very little data
or information about the virus, making data sharing
across organizations more critical than ever. Health
systems that didn’t have a data-centered culture and
a data-friendly infrastructure were ill-equipped to
share data and gain more insights about the virus as
it evolved. This deficit delayed patient care, leading
to worse outcomes. Inversely, health systems with
an existing data infrastructure had already prepared
for effective data interoperability, continually
learning more about the virus and, in turn, adapting
patient care and emergency planning according to
those changes. With constant, updated data coming
in, health systems can continually pivot their
strategy to fight COVID-19 and target metrics to stay
patient-centric amid constant change.
Data Sharing

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#2 Deploy Data Tools to Combat COVID-19
Leveraging data throughout the pandemic has allowed health systems to understand capacity,
utilization, and the resources they should allot for different healthcare delivery methods, such
as telemedicine. Using data to understand how to continue care delivery prioritizes patients over
processes in any circumstance.
Leveraging Data

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#3 Promote Data Literacy
Health systems can improve how they
use data to make patient-centric decisions
and improve outcomes by cultivating
data literacy. With a patient-centered
model and patient-centered metrics,
team members need the literacy tools to
understand and apply data throughout
the care delivery process. Data-literate
team members who can access actionable
data understand how that data drives
patient-centered care during the
COVID-19 crisis and future challenges.
Cultivate Data Literacy

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#3 Promote Data Literacy
Data teams can start by developing various in-person and
virtual data literacy training opportunities (especially with
team members working remotely due to COVID-19). A data
literacy program can begin with a data readiness checklist
that defines a literacy baseline. Organizations can use that
baseline to measure progress. Health systems can also
improve data literacy by creating data literacy champions
to promote data-informed processes and decision making
throughout the health system. For example, health
systems can train physicians, nurses, and administrators as
data champions within their teams, units, and
departments. Leveraging existing leaders as data
champions extends the data beyond analysts and leaders,
increasing the likelihood that team members will model
the behavior of their managers and also turn to data
before making decisions about patient care.
Data Literacy Program

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Data Powers Patient-Centered Care
in Value-Based Care

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Data Powers Patient-Centered Care in Value-Based Care
When health systems leverage analytics
insight to understand a patient’s complete
health, they can use that insight to guide
quality care that qualifies for the
demanding CMS reimbursement standards
of VBC (e.g., cost, quality, and provider
performance). Without actionable insight,
care teams can’t effectively identify at-risk
patients, or ensure they are delivering
high-quality, cost-effective care. Analytics
is essential to VBC because it prevents care
teams from wasting resources, spending
too much time on the wrong interventions,
or failing to prioritize the patient.
Analytics Is Essential to VBC

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Data Powers Patient-Centered Care in Value-Based Care
Detailed information from comprehensive data sets
allows patient needs to drive care interventions,
essential to patient-centered care in VBC. Whether
health systems are facing populations with chronic
diseases like diabetes or responding to COVID-19, a
culture that values data in the care delivery process
will have the tools to deliver sustainable VBC.
Patient Driven Intervention

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1 The Medicare Shared Savings Program: Four Tools for
Better Profit Margins and High-Quality Care
3 Activity-Based Costing in Healthcare During COVID-19:
Meeting Four Critical Needs
2 From Volume to Value: 10 Essential Strategies for Navigating
the Healthcare Shift
4 Population Health Management: A Path to Value
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