By Kameron Gifford, CPC
As we enter the
third quarter of 2020, healthcare organizations have been struggling for months
to balance priorities and resources while navigating new technologies and
processes to keep employees and patients safe during the coronavirus.
The AAFP
and MGMA
both recently reported, “Medical group practices of all sizes and
specialties have felt the direct and indirect financial impact... On average, patient
volumes have dropped 60% nationally since the start of the pandemic attributing
to a 55% decrease in fee-for-service revenues.
Medical practices
are not alone, hospital revenue is dropping
by an average of $1.4 billion per day as COVID-19 continues to impact
patient volumes, according to Crowe RCA Benchmarking analysis.
Risk Scores
and Value-Based Payments
As more and
more healthcare organizations are moving away from traditional fee-for-service
payment models, how will this decrease in utilization impact risk scores and value-based
payments in the future?
According to Avalere,
the deferral of care has resulted in fewer claims and diagnoses among Medicare
Advantage (MA) enrollees, which will likely lead to a 3%–7% reduction in
2021 risk scores and lower plan payments.
Mitigating
the Impact to Risk and Quality
Inaccurate risk
scores not only impact payments to Medicare Advantage plans, but also skew the
costs in ACOs and hinder performance in value-based contracts. This further
underscores the need to capture an accurate health status on every patient.
What steps can organizations
take today to achieve accurate risk scores and mitigate future losses?
Common
Errors Leading to Inaccurate Risk Scores
The 2020
ICD-10-CM code set includes 72,184 diagnoses and the 2021 ICD-10-CM code set includes
72,616 diagnoses. With less than 14% of ICD-10-CM codes mapping to an HCC, lack
of specificity is the most common cause of inaccurate risk scores.
Review the six
most common coding errors below that lead to inaccurate risk scores and payments.
E11.9 – Type 2 Diabetes without Complications
According to
the most recent data released by MedPAC
on July 17, 2020, 28.2% of Medicare beneficiaries had a diagnosis of diabetes
on a claim in 2019. Roughly 70% of these mapped to HCC 18, Diabetes with chronic
complications, while 30% of these mapped to HCC 19, Diabetes without
complications.
How does your
coding for diabetes compare to MedPAC data? What percentage of patients are
coded as E11.9 by primary care providers? What percentage are coded as E11.9 by
specialists such as hospitalists and endocrinologists?
Per ICD-10
Guidelines, approximately 30 conditions have an assumed relationship with type
2 diabetes. Meaning, they are always coded as a complication unless the medical
record explicitly states otherwise.
Examples include:
- Type 2 Diabetes with CKD, E11.22
- Type 2 Diabetes with dermatitis, E11.620
- Type 2 Diabetes with foot ulcer, E11.621
- Type 2 Diabetes with gastroparesis, E11.43
- Type 2 Diabetes with hyperglycemia, E11.65
- Type 2 Diabetes with hypoglycemia, E11.649
- Type 2 Diabetes with mononeuropathy, E11.41
- Type 2 Diabetes with myasthenia, E11.44
- Type 2 Diabetes with nephropathy, E11.21
- Type 2 Diabetes with neuralgia, E11.42
- Type 2 Diabetes with neuropathy, E11.40
- Type 2 Diabetes with PAD, E11.51
- Type 2 Diabetes with periodontal disease, E11.630
- Type 2 Diabetes with polyneuropathy, E11.42
- Type 2 Diabetes with retinopathy, E11.319
Review 5 – 10 encounters
per provider. What percentage of encounters coded as E11.9, had a complication documented
in the medical record? Target education, prospective chart checks and
pre-billing review per the results.
How it
Happens
Several factors
contribute to the high error rate related to coding for E11.9. The two most
common reasons are failure to update the diagnosis as the disease progresses
and failure to follow the ICD-10 Guidelines for “with”.
Why it Matters
The 2020 CMS-HCC
RAF for HCC 19 is 0.105 and the 2020 CMS-HCC RAF for HCC 18 is 0.302. That is a
loss of 0.197 per error. This adds up quickly across populations, accounting
for annual average losses of $60,000 - $130,000 per 1000 MA beneficiaries.
F32.9, Major Depression, Single Episode, Unspecified
According to
the most recent data released by MedPAC
on July 17, 2020, 11.3% of MA beneficiaries were diagnosed with a condition
mapping to HCC 59, Major Depressive, Bipolar or Paranoid Disorders.
According
to CMS, mood disorders (mainly MDD and bipolar disorder) are the second
leading cause of disability in Medicare patients under the age of 65. Depression
is a major predictor of the onset of stroke, diabetes, and heart disease; it
raises patients’ risk of developing coronary heart disease and the risk of
dying from a heart attack nearly threefold.
Overall, the
economic burden of the disease is significant to managed care organizations,
with direct medical costs estimated at $3.5
million per 1000 plan members with depression.
Identify Errors and Opportunities
From a coding
perspective, MDD is classified by episode, severity, and remission.
According to AMJMED,
75% to 90% of patients experience >1 episode of depression. This suggests
that only 10 - 25% of MDD diagnoses would be assigned to F32 with the remaining
75 – 90% being classified as F33.
Analyze your
coding for MDD. What percentage of MDD diagnoses are single episodes (F32.x)
vs. recurrent episodes (F33.x) What percentage of single episodes are
classified as “unspecified” (F32.9) when a PHQ-9 was completed and/or the documentation
supported a more specific diagnosis? What percentage of patients taking an SSRI
or other antidepressant have a current diagnosis to support medical necessity?
Review 5-10
encounters per provider with a diagnosis of F32.9. Was the correct diagnosis
assigned? Target education, prospective chart checks and pre-billing review per
the results.
Why it
Matters
From a risk
adjustment perspective, F32.9, is the only MDD diagnosis that does not map to an
HCC. The 2020 CMS-HCC RAF for HCC 59, Major Depressive, Bipolar and Paranoid Disorders
is 0.309. Missed opportunities relating to the use of F32.9 average 20% across
populations accounting for an average annual loss revenue of $77,500 per 1000
members.
How it
Happens
Two factors
contribute to the high use of this code. First, the GEM files mapped the ICD-9
code 311 to the ICD-10 code F32.9 and these files were widely used by EHR vendors.
The second factor involves the number of boxes providers must check in their EHR
to get to the more specific MDD diagnosis.
One way to
avoid these extra clicks is by typing the diagnosis code directly into the search
box of your EHR. For example, typing F32.0 (MDD, single episode, mild) vs
depression will reduce clicks from 13 to 4 and reduce search results from 800+
to 1. Searching for F33.0 (MDD, recurrent, mild) vs recurrent depression will
save even more clicks with the same results.
I25.9, Chronic Ischemic Heart Disease and I25.10, CAD without Angina
According to the NIH, an
estimated 10 million adults in the United States carry the diagnosis and
ischemic heart disease remains the number one cause of death for male as well
as female patients. Furthermore, the increasing survival with the use of modern
therapies has produced an aging population where more than 20% of women and 35%
of men above the age of 80 have coronary artery disease.
Identify
Errors and Opportunities
From a coding
perspective, chronic ischemic heart disease is classified to category I25 and
CAD is further classified as with or without angina.
Analyze your
coding of chronic ischemic heart disease (I25.9) and CAD without angina
(I25.10). Depending on your results you may also want to include old MI (I25.2)
and chest pain (R07.9) in your search.
Review 5-10
encounters per provider. How many of these patients had evidence of angina
documented, history of CABG and/or a current prescription for nitroglycerin? Target
education, prospective chart checks and pre-billing reviews per the results.
How it
Happens
The term stable
ischemic heart disease (SIHD) is often used synonymously with chronic coronary
artery disease (CAD) and encompasses a variety of conditions. Many EHR’s include
an IMO to assist providers in searching for codes. This “tool” adds multiple
code descriptions for each ICD-10 code and can increase search results by 70%. Many
providers do not have the time to search dozens of code descriptions for
multiple diagnoses prior to closing their note. This often results in the selection
of the first or second result, even when a more specific diagnosis is supported
by the documentation.
Why it
Matters
From a risk
adjustment perspective, I25.9 and I25.10 are included in the Rx-HCC Model V05,
but not in the CMS HCC Model V24. However, CAD with Angina (I25.110 – I25.119)
and Angina (I20.0 – 120.9, I23.7) are all included in the CMS HCC Model V24. The
2020 RAF for HCC 87 is 0.195 and HCC 88 is 0.135.
According to
the CMS Chronic Disease Warehouse, 10,238,321 (or 17.1%) Medicare beneficiaries
had a diagnosis of ischemic heart disease. While the most recent MedPAC
data published on July 17, 2020 reveals only a 4% prevalence rate among MA
beneficiaries in the same year.
Missed opportunities
relating to the use of I25.9, I25.10, I25.2 and/or R07.9 average 25% across populations
accounting for an average annual loss of $64,638 - $93,366 per 1000 MA members.
I49.9, Cardiac arrythmia, unspecified
According to
the most recent data released by MedPAC
on July 17, 2020, 11.4% of Medicare Advantage members had a diagnosis that
mapped into HCC 96, Specified Heart Arrythmias.
In the CMS-HCC
Model V24, 18 ICD-10 codes are mapped into HCC 96.
Examples
include:
- AV Block, Complete, I44.2
- SVT, I47.1
- Paroxysmal A. Fib, I48.0
- A. Flutter, I49.92
- Sick Sinus, I49.5
Identify
Errors and Opportunities
Analyze your
coding for cardiac arrythmias. What percentage of encounters/claims are coded
with I49.9, Cardiac arrhythmia, unspecified when the medical record supported a
more specific diagnosis?
You may also
want to include the use the ICD-10-CM code Z95.810, Presence of automatic
(implantable) cardiac defibrillator, in your analysis. Target education,
prospective chart checks and pre-billing reviews per the results.
How it
Happens
AHA Coding Clinic
recently updated their guidance on coding for sick sinus syndrome treated with
a pacemaker. This change in guidance has led to an increased number of opportunities
identified in HCC 96. Additional opportunities are identified from diagnostic
test results and specialists’ reports.
Why it
Matters
I49.9, Cardiac arrhythmia,
unspecified is not included in the 2020 CMS-HCC Model V24.
Missed
opportunities relating to HCC 96 average 20% across populations accounting for
average annual lost revenue of $67,214 per 1,000 MA beneficiaries.
N18.9, CKD, unspecified
According to the
CMS Chronic Condition Warehouse, there were 9,360,944 Medicare beneficiaries (15.6%)
with a diagnosis of CKD on a claim in 2018. However, a review of the most
recent data released by MedPAC
on July 17, 2020, does not include CKD, meaning the prevalence for MA
members in the same year was less than 1.5%.
Why Is Chronic
Kidney Disease Important?
The total
Medicare spending on both CKD and ESRD patients was in excess of $120 billion
in 2017. For identified
CKD (not ESRD) the total Medicare expenditure was $84 billion.
Identify
Errors and Opportunities
Analyze your
coding for CKD. What percentage of encounters/claims are coded with N18.9, CKD,
unspecified, vs. a more specific code such as N18.3 and/or N18.4?
You may also
want to include the ICD-10 code N28.9, disorder of kidney and ureter,
unspecified, in your analysis.
Review 5-10
encounters per provider. What percentage of encounters/claims are coded with an
unspecified diagnosis such as N18.9 and/or N28.9, when a more specific
diagnosis is supported by the medical record? Target education, prospective
chart checks and pre-billing reviews per the results.
How it Happens
There are several
factors that contribute to this large opportunity. Lack of documentation is the
most common reason. CKD must be staged by the provider. Pasting a copy of the
patient’s most recent labs into the current encounter supports the provider’s
medical decision making but does not replace the need for the stage to be
documented.
The fluctuating
nature of the disease also contributes to the lack of specificity in coding, as
providers are less likely to update.
Historically,
multiple terms have been applied to chronic kidney disease (CKD), eg,
chronic renal insufficiency, chronic renal disease, and chronic renal failure,
the National Kidney Foundation Kidney Disease Outcomes Quality Initiative™ (NKF
KDOQI™) has defined the all-encompassing term, CKD. This recent change in terminology
also contributes to the size of the opportunity. The IMO search tool in EHR’s
will lead providers using
older terminology such as, renal insufficiency, to select a diagnosis of N28.9
CKD stage 3 was
removed from the HCC model in 2014 and this likely contributed to the decrease
in coding by MA plans as well. CMS reversed course in PY 2019, and added HCC
138, CKD stage 3, back into the model.
Why it
Matters
Missed
opportunities relating to HCC 138, CKD stage 3, average 60% across MA
populations accounting for annual average lost revenue of $73,625 per 1000
members.
Want to learn
more? Visit www.erm365.org and www.ermconsultinginc.com
ERM Consulting Inc. works with healthcare organizations across the country to optimize their risk adjustment operations.
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