Medical Practices’ Survival Depends on Four Analytics Strategies

Medical Practices’ Survival Depends on
Four Analytics Strategies

© 2020 Health Catalyst
Proprietary. Feel free to share but we would appreciate a Health Catalyst citation.
Andy Choens, MS
Leader and Architect,
Data Science and Engineering,
Acuitas Health
This article is based on a Healthcare Analytics Summit (HAS 20
Virtual) breakout presentation by Keegan Bailey, MS, Senior Leader,
Acuitas Health, and Andy Choens, MS, Leader and Architect for Data
Science and Engineering, Acuitas Health, titled, “Advanced Analytics
for Medical Practices: Value-Based Care in the New Normal.”
Medical Practices’ Survival
Keegan Bailey, MS
Senior Leader,
Acuitas Health

Challenges for healthcare providers in today’s
competitive market include stagnant
reimbursement rates for value-based care
(VBC), high overhead, stiff competition from
healthcare conglomerates, and as of 2020,
COVID-19.
Increasing demands to deliver better care
with fewer resources, combined with the
pandemic, have heightened the pressure for
all organizations, especially for independent
medical and physician practices with fixed
resources and less financial flexibility than
larger organizations.

While some smaller providers are joining large
health systems, those aiming to stay independent
must strategize for a viable financial future.
Many independent practices struggle to survive
because they rely on manual processes or
technology that fails to maximize data.

With technology that surfaces meaningful
information based on analytics insight,
providers have the most relevant information
when it matters—from managing the practice
to the point of care.
Not only do analytics for medical practices
drive better patient care, but also better
financial and operational decisions by
automating practice management, regulatory
requirements, and staffing decisions so that
providers can spend more time with patients.

Delivering quality care to patients is critical
for independent practices because it is the
primary source of income.
Without patients, these practices can
eliminate waste and improve resource
utilization but cannot generate the new
revenue that comes from patient visits.

Analytics for Medical Practices Guide
Better Care with Limited Resources
The burdens facing physician practices
include spending $15.4 billion annually to
report over 2,000 quality measures to
CMS, a costly requirement to qualify for
reimbursements around VBC that takes
providers away from patient care.
Medical practices also face new
pandemic-related challenges, such
as added financial strain from paused
elective procedures, delayed primary
care visits, and transitioning from in-
person to virtual care.

Typical care coordination between medical
practices and health systems—critical for
communication about patients who receive
care at multiple locations—is also more
difficult due to the lack of interaction
between providers and health systems
amid the COVID-19 response.

While these challenges are ubiquitous to
health systems of all shapes and sizes,
medical practices, in particular,
experience more pressure compared to
large health systems because they have
fewer resources to share the burden of
an unexpected crisis, like COVID-19.
Limited financial, clinical, and operational
resources make it critical for medical
practices to rely on analytics to maximize
every asset, supply, and material they
have.

Four Analytics-Based Strategies Help
Medical Practices Stay Viable
Despite new and existing pressures, medical practices
can leverage four analytics-based strategies to navigate
growing healthcare challenges, swiftly respond to market
changes like COVID-19, get back on the road to
recovery, and plan for a sustainable future:
1. Prioritize Access to Up-To-Date,
Comprehensive Data Sources
2. Form a Multidisciplinary Approach to
Data Governance
3. Translate Data into Analytics Insight
4. Invest in Analytics Infrastructure to
Support Rapid Response

#1: Prioritize Access to Up-To-Date, Comprehensive Data Sources
Analytics for medical practices only offer
peak value if they are based on broad
and varied data sources.
A singular data set can be useful but has
limited value because it lacks context
from other data sets.
Therefore, medical practices need
access to a variety of data sets from
diverse sources to derive analytics
insight about their operational, financial,
and clinical well-being.

When medical practices have access to expansive
data sets from a robust data infrastructure (e.g., the
Health Catalyst Data Operating System (DOS™)),
they can leverage analytics insight as often as they
need to review information about patients,
interventions, or the practice’s operational status.
By drawing on the latest analytics insight, health
systems don’t waste time or resources on a
substandard solution because the analytics will
reveal any wrong direction in near real-time.

Constant guidance from comprehensive
analytics allows for a flexible problem-solving
approach and better understand challenges
along the way.
This flexibility in an ever-changing healthcare
market leads to optimum solutions.
For example, EHRs fail to effectively
synthesize information, hiding key data
points in hard-to-find places so that clinicians
have to click multiple times to find one piece
of information.

In such cases, analytics based on comprehensive
data sets would reveal that providers waste time
clicking in the EHR searching for information.
With this insight, medical practices could
create an automated solution to surface
insights in the EHR and save provider time
and avoid burnout, leading to better patient
care, as the clinician could easily view a
patient’s comprehensive history in one
place before making a healthcare decision.

#2: Form a Multidisciplinary Approach to Data Governance
Along with a diverse approach to data
sources, medical practices should also take
a diverse approach to data governance.
Historically, a data analyst has focused on
technical elements, including algorithms,
predictive models, and plugging numbers
into spreadsheets.

In contrast, the subject matter expert (SME)
only focuses on delivering in-depth subject
matter content.
However, this approach doesn’t advance
analytics for medical practices beyond the
surface level because neither the analyst
nor the SME understands the other’s role,
keeping their contribution limited to their
subject areas and creating hard-to-break
information silos.

In a multidisciplinary analytics setting, data
analysts learn the subject matter, and SMEs
understand data’s technical aspects.
This cross pollination across different
areas of expertise allows a medical
practice to approach problem solving
with analytics from all critical viewpoints.

For example, a data analyst might interpret or
value a specific data set differently than a SME.
With data analysts, SMEs, and other contributors
working together to govern data, a medical
practice ensures meaningful solutions
across the organization.

#3: Translate Data into Analytics Insight
Translating data into analytics insights is the
key to deriving value from data and ensuring
it can drive real-world improvement.
The translation process involves members of
specific teams (e.g., business management,
data science, and administration) working
together to interpret the problem and
proposed solution for team members less
versed in advanced healthcare analytics.

Historically, non-clinical workers at an
independent practice might focus on tasks
like accounting or quality metrics data entry
to track physician performance.
Now, every team member who interacts with
data should act as a strategic partner in
driving organizational change, from non-
clinical to clinical personnel.

Additionally, including the data governance team
early in the data process, before the team
commits to a solution and course of action,
allows for additional questions and contributions
that can lead to further analytics clarification and
insight the core team might have missed.
Regardless of the problem, medical practices
should include different team members in data
analysis to ensure the data translates to
information that can drive real-world
improvement at a medical practice.

#4: Invest in Analytics Infrastructure to Support Rapid Response
The rapid onset of COVID-19 forced many
medical practices to quickly modify their
operations to address pandemic challenges.
During the acute phases of the COVID-19
outbreak, medical practices have gone (in
just a few days) from delivering no or few
telemedicine visits to thousands.
In the past, many health systems delayed
implementing or scaling telemedicine, but
with suspended in-person visits, medical
practices have had to turn to virtual care.

#4: Invest in Analytics Infrastructure to Support Rapid Response
Robust analytics infrastructures with access
to aggregated data from multiple sources
have helped medical practices visualize
COVID-19-driven changes on operational
and financial performance and how to best
respond.
For example, if a medical practice has to
deliver 100 telemedicine visits to meet a
specific financial goal, leaders will know
how many virtual visits to aim for weekly.

Analytics for Medical Practices—
Essential for Survival
Without access to accurate data, medical
practices must guess where they should
expend their precious resources, rather than
knowing for certain.
If larger organizations misuse resources, they
generally have a pool of back-ups. But with a
small, if any, safety net, medical practices can’t
afford to use any resources in a way that isn’t
data-informed.
Every wasted resource becomes a resource
that the medical practice can’t get back and now
has to take from another area of the practice.

Analytics insight from comprehensive, diverse
data supports an effective response to any
demand, including maximizing limited
resources or responding to a global pandemic.
However, medical practices cannot rely on
analytics insight alone to drive change.

Analytics for medical practices, coupled with
team members who understand data and can
translate it into real-world analytics, lead to
operational, financial, and clinical long-term
viability, critical to surviving in the pandemic
and VBC landscape.
Access, teamwork, and infrastructure are vital
in pushing analytics beyond their basic use,
unlocking insights that could make the difference
for a medical practice’s survival and empowering
them to worry less about their financial future
and more about delivering first-class care.

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

More about this topic
Link to original article for a more in-depth discussion.
Shifting to Virtual Care in the COVID-19 Era: Analytics for Financial Success and an Optimized
Patient Experience
Six Proven Methods to Combat COVID-19 with Real-World Analytics
Health Catalyst Editors
How to Run Analytics for More Actionable, Timely Insights: A Healthcare Data Quality Framework
Taylor Larsen, DOS Marts Data Quality, Director
How to Optimize the Healthcare Revenue Cycle with Improved Patient Access
Health Catalyst Editors
Healthcare Relief Funding: Five Steps to Maximize COVID-19 Dollars
Greg Anderson, CPA/ABV, CVA, HORNE LLP; Jeff Grandia, MBA, Senior VP, Sales
Healthcare Revenue Cycle: Five Keys to Financial Sustainability
Marlowe Dazley, Senior VP and Managing Director of Financial Advisory Services;
Todd Halpin, Senior VP, Financial Advisory Services

Serving as Acuitas Health’s Senior Leader providing leadership and subject matter
expertise in value-based health care. Building an agile and responsive organization
focused on customer outcomes, and supporting customers through the market transition
from fee-for-service to value-based health care. Overseeing the organization’s core
functions including, but not limited to Outcomes Engineering, Practice Intelligence, Data
Architecture/Data Science, Project and Product Management, and Care Management.
Keegan also founded a successful strategy and technology consultancy, Navaste Health
(navastehealth.com). Beyond passion for transforming the health care landscape, Keegan is also
passionate about food in community giving, and in business. Keegan supports the Regional Food Bank
for Northeastern New York, and founded a food business, Send Me Waffles (sendmewaffles.com).
Other Clinical Quality Improvement Resources
Click to read additional information at www.healthcatalyst.com
Keegan Bailey, MS

Andy Choens is a data scientist at Acuitas in Troy, NY. He earned his B.S. from the
Georgia Institute of Technology in Atlanta, GA and his MSW from SUNY Albany in
Albany, NY. Andy then worked as a program evaluator for Hornby Zeller Associates for
seven years working primarily in child welfare, juvenile justice, and elder care. Andy
then spent two years at the New York State Department of Health where he led the
internal evaluation of the New York State Health Homes initiative. At Acuitas, Andy is
responsible for data architecture, reporting, evaluation, and office birthdays. In addition to enjoying
books on Bayesian statistics, Andy enjoys mountain biking, downhill skiing, and rock climbing.
Andy Choens, MS

Health Catalyst is a mission-driven data warehousing, analytics and outcomes-improvement
company that helps healthcare organizations of all sizes improve clinical, financial, and operational
outcomes needed to improve population health and accountable care. Our proven enterprise data
warehouse (EDW) and analytics platform helps improve quality, add efficiency and lower costs in
support of more than 65 million patients for organizations ranging from the largest US health system
to forward-thinking physician practices.
Health Catalyst was recently named as the leader in the enterprise healthcare BI market in
improvement by KLAS, and has received numerous best-place-to work awards including Modern
Healthcare in 2013, 2014, and 2015, as well as other recognitions such as “Best Place to work for
Millenials, and a “Best Perks for Women.”

Medical Practices’ Survival Depends on Four Analytics Strategies

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Medical Practices’ Survival Depends on Four Analytics Strategies