Five Action Items to Improve HCC Coding Accuracy and Risk Adjustment With Analytics

Five Action Items to
Improve HCC Coding
Accuracy and Risk
Adjustment With Analytics

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As enrollment in Medicare Advantage plans increases,
healthcare organizations need to be able to anticipate
future healthcare financial resources and predict
appropriate reimbursement for physicians.
Coding Accuracy and Risk Adjustment

The Hierarchical Condition Category (HCC)
risk adjustment model is used by CMS to
estimate predicted costs for Medicare
Advantage beneficiaries, and the results
directly impact the reimbursement healthcare
organizations receive.
The HCC risk adjustment model was
originally implemented in 2004, but is
becoming more prevalent as value-based
payment models gain popularity.

The HCC model assigns a Risk Adjustment
Factor (RAF) to each Medicare patient as
measurement of probable costs, which is then
used to adjust capitation payments for patients
enrolled in Medicare Advantage plans.
Accurate HCC coding and risk adjustment
can have a significant impact on healthcare
organizations’ financial viability and care
delivery.

CMS requires that all qualifying conditions be
identified each year by provider organizations.
Documentation linked to a non-specific
diagnosis, as well as incomplete
documentation, negatively affects
reimbursement.
Healthcare organizations that optimize
their EMR, data, analytics, and education
can enable better documentation of
care for patients with chronic diseases,
leading to more accurate HCC risk
adjustment coding.
HCC Model Complexities and
Risk Adjustment Use

The number of Medicare Advantage beneficiaries
has continued to rise over the past ten years, with
roughly one-in-three Medicare beneficiaries now
enrolled in a Medicare Advantage plan.
As with starting any new initiative, HCC
coding is not intuitive, but accurate
HCC coding is necessary for healthcare
organizations in order to receive fair
compensation.
Risk Adjustment Use

There are a few highlights to know about the CMS HCC model complexities
and risk adjustment use:
CMS requires an encounter each calendar year and diagnosis by an APRN, PA or
physician.
Documentation must be accurate and support the diagnosis.
Some codes have RAF value. Some do not. Increased severity doesn’t usually
increase risk adjustment factor (RAF).
HCC codes are not always intuitive. Physicians may require decision support.
HCC codes are additive, and some have multipliers.
Population complexity/severity affects payment in many Medicare contracts.
RAF is used for benchmarking for quality and safety.
RAF enables identification and stratification for patient management.
Risk Adjustment Use
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Even though the payment model is not intuitive,
an organization’s ability to perform well within
this model should increase over time.
For example, in Figure 1, the table shows
sample patient data from a 76-year-old
female patient with an RAF score of .448.
The two options show how different
diagnoses change the patient’s risk
score, and, as a result, the annual
member payment.
The Impact of Appropriate HCC Coding

Impact of Appropriate HCC Coding on Payment
Female, age 76, Not: originally disabled, Medicaid, ERSD, or
institutionalized, Demographic RAF score = .488
Option 1 HCC Risk Score
Obesity 0
Type 2 diabetes, exudative retinopathy .104, 0
Major depression disorder,
Single episode, unspecified
0
CHF .323
Asthma 0
Pressure ulcer of right heel, unspecified 0
CHF*DM .154
RAF score: 1.029
Sample MedicareAdvantage member payment,Annual: $9K
Option 2 HCC Risk Score
Morbid obesity, BMI 42 .273
Type 2 diabetes, w/diabetic retinopathy .318
Major depression disorder,
Single episode, mild
.395
CHF, class 3 .323
COPD .328
Pressure ulcer of right heel, stage 3 1.204
CHF*DM; CHF*COPD .154, .19
RAF score: 3.633
Sample MedicareAdvantage member payment,Annual: $32K
Figure 1: The impact of appropriate HCC Coding on payment

The two different options show a patient of similar
complexity but varying diagnoses, which results
in vastly different annual member payments.
Option one showed a total RAF score 1.029 and
an annual Medical Advantage member payment
of $9,000.
Option two showed a RAF score of 3.633 and a
Medicare Advantage member payment of
$32,000 annually.
While physicians should not change their
diagnoses, it is important to code accurately
and take credit, where deserved, for serving
a complex population.

The example provides a compelling rationale
for organizations to improve their HCC coding
accuracy.
However, the first step is obtaining accurate
data about Medicare populations before trying
to make improvements in this space.
It may also be beneficial to form a workgroup
that is responsible for improving the accuracy
of documentation and HCC coding.
Driving Improvement Through
Interdisciplinary Workgroups

This workgroup could include members of:
• The analytics team
• Accountable Care Organization (ACO) team
• Clinicians
• Clinic managers
• Operations
• Medical coders.

Forming the workgroup can help oversee these five
key action items necessary for improving HCC
coding accuracy:
1. Having an accurate problem list
2. Ensuring patients are seen in each calendar year
3. Improving decision support and EMR optimization
4. Widespread education and communication
5. Tracking performance and identifying opportunities

1: Having an accurate problem list
Many healthcare organizations have been
inputting data in an EMR for years now,
resulting in lots of data, and most likely an
inaccurate problem list.
Ensuring an accurate problem list involves
removing duplicative and inactive diagnoses,
identifying key areas with discrete data in the
EMR, and using a diagnosis preference list to
include HCC suffix codes and RAF values as
well as prioritize results.

2: Ensuring patients are seen in each calendar year
The first step is to identify patients with chronic
illnesses who have not been seen during the
calendar year and once found, schedule that
patient for a visit.
One way to do this at a glance is to build a
clinical dashboard that provides a snapshot
of both EMR and claims data that provides a
complete picture of patients not yet seen in
a calendar year.
Once the workgroup can identify these
patients, they can match them with both
visit and HCC coding gaps.

3: Improving decision support and EMR optimization
Although educating providers is necessary to
improve HCC coding accuracy, it’s also
important to build appropriate coding into the
daily encounter workflow.
Some potential strategies include having an
ACO identifier flagged in the EMR, decision-
support tools that can be activated for select
populations, and HCC diagnosis alerts for
past codes.

4: Widespread education and communication
Because this is new work and certainly not
intuitive, it’s important to educate clinicians.
The biggest educational point to drive home to
clinicians is not what score they should look for,
but the importance of accuracy.
Workgroups can educate clinicians on the
clinical and financial value of specificity.
They can also educate clinic staff about
the specifics of the tools and workflows
for patient management and reporting.

5: Tracking performance and identifying opportunities
The last, and perhaps most important key
initiative of the workgroup is to track
performance and identify future opportunities
for improvement.
Measuring results provides the workgroup with
compelling data to bring to stakeholders that
shows what improvements were made, such
as an increase in average RAF score,
improvement in key problem list diagnoses,
decrease in the number of members without
an annual visit, an increase in the percentage
of persistent condition diagnoses resolved.

5: Tracking performance and identifying opportunities
Once the workgroup has data to bring to
stakeholders, the next step is to identify future
opportunities for further improvements.
One place to look for these is by reviewing
unresolved persistent conditions for specific
populations.

Key Lessons
For organizations that are looking to embark on
an effort to improve their HCC coding accuracy
and risk adjustment, below are four valuable
lessons learned:
The magnitude and presence of coding accuracy
opportunities are not evident without data.
Using data to focus efforts helped find topics that
were practice and valuable to end users and
improve engagement.
It is manageable and effective to use the EMR
upstream and during encounters.
Clinic staff want reports to see how they are
doing compared to peers.
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Fair Reimbursement for Serving
Complex Patient Populations
Although HCC coding accuracy and risk adjustment
requires changes to the way healthcare organizations
are documenting and coding chronic conditions,
doing so can help the organization capture more
complete diagnoses, resulting in higher and more
appropriate reimbursement and improved care
delivery for complex patient populations.

With increasing Medicare Advantage numbers,
healthcare organizations need to improve
coding accuracy to remain financially viable.
Creating a workgroup that’s responsible for
key action items is crucial to the success
of this initiative.
They can help ensure the organization has an
accurate problem list, chronically ill patients
are seen once per calendar year, improve
decision-support and EMR optimization,
educate clinicians and staff, and track
performance of the initiatives to share
with stakeholders.

If healthcare organizations appropriately
document the complexity of their patients,
they are eligible for greater CMS revenue
that can then be reinvested to better meet
the needs of their patient population.

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.
Five Action Items to Improve HCC Coding Accuracy and Risk Adjustment With Analytics
ACOs: Four Ways Technology Contributes to Success
Health Catalyst Editors
Understanding Risk Stratification, Comorbidities, and the Future of Healthcare
Eric Just, SVP of Product Development
Healthcare Data Management: Three Principles of Using Data to Its Full Potential
Sean Whitaker
Why Clinical Quality Should Drive Healthcare Business Strategy
Health Catalyst Editors
Linking Clinical and Financial Data: The Key to Real Quality and Cost Outcomes
Bobbi Brown, MBA, SVP

Other Clinical Quality Improvement Resources
Click to read additional information at www.healthcatalyst.com
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