Using Technology to Capture Hierarchical Condition...

Using Technology to Capture Hierarchical Condition Categories (HCC’s)

Connecticut HIMAAugust 16, 2019

The Cost of Technology in Healthcare?

© 2017 MModal IP LLC, All rights reserved – Confidential Information2

What are Hierarchical Condition Categories (HCCs)? Chronic conditions documented in the medical record, identified by an

ICD-10 code, that are associated with a “risk score”

Not every diagnosis qualifies as an HCC (>71k ICD-10 codes, ~9k are HCCs)

Fully specified qualifying HCC diagnoses may carry higher risk weights than less specified diagnoses (i.e. type 2 diabetes vs. type 2 diabetes with diabetic nephropathy)

Patient risk score is used by Medicare Advantage Plans and some commercial payers to identify the severity of patient comorbidities

Payment to the provider is determined based on the risk severity of the patient population (i.e. sum of all risk scores for all patient diagnoses)

Providers receive a portion of the shared savings when their costs to treat their patients are below the capitated payment amount

© 2019 3M|M*Modal, All rights reserved – Confidential Information3

CMS-HCC Model Structure


What is the difference between CMS-HCC and HHS-HCC?

CMS-HCC HHS-HCC

Used by CMS to pay Medicare Advantage plans for enrolleesUsed by CMS to pay health insurers in Affordable Care Act

marketplace

Base year (current year) diagnoses determine next year’s ratesUses current year diagnosis coding to set risk payments in current

year

Developed for >65 year olds and disabled patients of all ages Developed for all age patients

Pediatrics and obstetrics diagnosis codes are not assigned risk values

Includes categories for infants, children and adults, and includes obstetrical diagnoses

Does not include drug costs Includes drug costs

Model used by many software programs, integrated into EMR systems.

Model less well known by medical practices

Rule making: proposal at the end of December, final rates in April Payment to health insurers for caring for sicker patients in ACA.


Why the Buzz? An increasing number of provider organizations – hospital networks and physician practices

– are entering into value based contracts with their payers.

It is estimated that by 2030 up to 40% of patients will participate in a Medicare Advantage risk based plan... And the number will continue to grow!

Providers establish a contract where they are paid a flat rate per patient; the amount paid to cover the annual patient care is determined based on documentation and billing.

The need for capturing chronic conditions qualifying as an HCC is important for both ambulatory and inpatient providers: Risk adjusted diagnoses can be captured regardless of place of service Patient risk score is based on their health status across the care continuum While not every HCC diagnosis is a CC or MCC affecting DRG assignment, such

conditions still contribute to the overall “risk” for treating that patient


What Are HCC’s & Why Are They Important?What

Chronic conditions Diagnosis used to risk adjust quality and

cost measures for both inpatient and outpatient encounters

Focusing on CMS‐HCCs in general should capture approximately 90% of the risk adjustment for all these programs

Predicts next year’s cost based on this year’s diagnoses

Why Fully specified conditions may

equal higher “risk” weighted category Diabetes (HCC 19, RAF

0.018) Diabetes with peripheral

neuropathy (HCC 18, RAF 0.368)

Accuracy of the record and reimbursement

HCC Documentation Requirements Qualifying ICD-10 code-able diagnoses must be fully documented

Supporting clinical evidence for all diagnoses must also be documented

“M.E.A.T” Criteria Monitor - Signs, symptoms, disease progression or regression

Evaluate - Review of test results, medication effectiveness, response to treatment

i.e. “stable,” “improving,” “exacerbation,” “worsening,” “poor”

Assess - Ordering tests, discussion, review records, counseling

Treatment - Referral, medication(s), planned surgery, therapies


KEY TAKEAWAY: Evidence of an HCC can be obtained from any qualified document/claim. It is important that provider documentation and billing be consistent across care continuum.

“H” is for “Hierarchy” Hierarchy (noun) - ‘hī(ə)ˌrärkē’ - 1A system or organization in which people or

groups are ranked one above the other according to status or authority. 2An arrangement or classification of things according to relative importance or inclusiveness.

For HCC coding, the most severe presence of a qualifying condition is considered for a patient risk score.

Therefore, providers must have all conditions fully specified in their documentation and claim, at least once annually.


Diabetes – importance of specificity HCC (RAF)

No complications captured HCC 19 (0.118)

Chronic complication captured (CKD, retinopathy, neuropathy, nephropathy, etc.) HCC 18 (0.368)

Difference in relative weight 0.250

Risk Adjustment Factor (RAF) Score

Calculated annually per patient


RAF Score

Demographics

Disease Interactions

Risk-Adjusted Diagnoses

Age, gender, residence, etc.

Billed diagnoses from the prior calendar year. This means diagnoses have to be captured again year over year!!

Also based on billed diagnoses!


Risk Adjustment Factor (RAF) Score

Value of Accurate Coding and Documentation


Value of Accurate Coding and Documentation


No Chronic Conditions Documented Chronic Conditions Documented, Not Fully Specified

Chronic Conditions Documented, Fully Specified

76 year old female 0.437 76 year old female 0.437 76 year old female 0.437

Medicaid eligible 0.151 Medicaid eligible 0.151 Medicaid eligible 0.151

Acute UTI (N39.0 – no HCC) 0.0 Acute UTI (N39.0 – no HCC) 0.0 Acute UTI (N39.0 – no HCC) 0.0

DM not documented 0.0 DM (E11.9, HCC 19) 0.118 DM w/ PVD (E11.51, HCC 18) 0.368

CHF not documented 0.0 CHF (I50.9, HCC 85) 0.368 CHF (I50.9, HCC 85) 0.368

No Condition Interactions 0.0 Interaction DM and CHF 0.182 Interaction DM and CHF 0.182

RAF Score 0.588 1.256 1.506

*Assuming the CMS Annual Base Rate is $9,600

$5,644 $12,057 $14,457

Chronic disease is reconfirmed only 45% of the time


0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

All Chronic Diseases Diabetes withoutComplication

Chronic ObstructivePulmonary Disease

Congestive Heart Failure Vascular Disease Morbid Obesity

% of Chronic HCCs Reconfirmed Year-Over-YearMedicare Population

HCC Buyer Profiles

Laggards No current process for HCC

reviews

No physician education programs

Not one to buy without references and ROI

Will be a challenge to sell here until we have more success stories


Early Adopters Some process for outpatient code reviews and

physician education, or looking to expand their inpatient CDI program for risk adjustment

Considering the use of technology to address HCC gaps and revenue leakage

Affiliated with an ACO or otherwise have a growing risk based patient population

Position our technology and services, pointing out we have the most complete offering available in the market today

Innovators Existing HCC workflows

Looking for automation and process improvement

Buyers that we should partner with now to prove outcomes

What problem are we trying to solve?

16

You Reap What You SowIt takes continuous work throughout the year in order to reach the expected risk management goals, and proxy measures help ensure you’re on track for a positive ROI

© 2019 3M|M*Modal, All rights reserved – Confidential Information

First you plant your seeds...


Managing HCCs is like farming a corn field:

...and water them throughout the year.


The stalks mature during growing season...


...your crop grows on the stalks until ripe...


...and then at harvest time you collect your corn!


So how did the Farm do? We... Followed the process (billed diagnoses) Grew some corn (measured a RAF score)

Yet... Our corn looks a little off indicating we could

probably do a little better throughout the growing process (work, work, work, work)

And, another farm – right down the road and of similar acreage – earned triple the profit we did ... At the same farmers market! (our patient risk scores are not as high, accurate as they should be based on how sick we know the local population is)

Why??© 2019 3M|M*Modal, All rights reserved – Confidential Information23

First you plant your seeds... Notice that Other Farm checked the soil quality periodically throughout the early

stages to ensure proper growth rate, pulling weeds and spraying for pests


...and water them throughout the year. But Other Farm has an advanced

irrigation system to accelerate, scale, and normalize the process.


The stalks mature during growing season... With the optimal soil management and

watering processes, Other Farm has a much nicer looking field than the first Farm.


...your crop grows on the stalks until ripe...


...until harvest time when you collect your corn!


What’s the point?


When you plant the seeds it is impossible to know whether or not the corn will end up like what we saw from the first or second Farm.

When the stalks are knee high we can tell if the plant looks healthy or not, but it is still impossible to know if the corn will be sweet or not.

And when we’re harvesting the corn we can tell how big the yield will be, but still cannot tell how much profit (or loss!) we’ll have...

Therefore, “We need proxy measurements that are good, valid representations of progress

before we can measure the outcome. " –Dr. Jim Manz, Mayo Clinic

Proxy Measures: Soil quality Seed sprouting rates Rain and watering patterns Plant growth rate and appearance throughout the year ...

All the info needed to predict if we will have a good yield in September

And it takes a lot of work (weeding, watering, pest control, etc.) to achieve the desired outcomes!


And the same is true for risk managing patients“We need proxy measurements that are good, valid representations of progress

before we can measure the outcome. " –Dr. Jim Manz, Mayo Clinic

Proxy Measures: Prioritize focus on patients with the greatest amount of risk and opportunity Filter by focus conditions to ensure capture rates for the most critical diagnoses Measure RAF gap closure and reconfirmation rate by month to check progress Review utilization data to identify HCC Auditors and Physicians that are performing well

or struggling so we can provide targeting interventions

All the info needed to predict if we will have accurate and appropriate RAF scores next year

And it takes a lot of work (pro-active reviews, physician engagement, etc.) to achieve the desired outcomes!


Ok, clearly we’re not growing corn, so what’s the difference between these “farms”?

Limited view into the true scope of the problem

Only as good as existing structured data (hint: not great)

Reactive, retrospective tools

Most require onsite server footprint or have limited cloud capabilities

Some AI capabilities but no workflow for engaging the physician or CDI support

Limited reporting

No service offerings to support technology

Identify true severity of illnesses by reviewing structured data and narrative documentation, which contains the most rich clinical information

Real time, proactive tools

Natively cloud based, part of an integrated clinical platform

Strong AI capabilities for physician engagement and scaling CDI programs

Comprehensive outcomes-based reports

Knowledgeable services team for education, training, and optimization

First Farm Second Farm


Next Steps


Patient Care Continuity

Patient

Inpatient DRG

OutpatientRAF

ICD 10

HCC

How do we get Providers to Do This?

• Make the right thing to do the easy thing to do

• We don’t need more education, we need process improvement

• Technical change (installation)

• Adaptive change (implementation)

Top 10 Medicare Risk Adjustment Coding Errors Health record does not have a legible signature with credentials. Electronic health record was not authenticated and electronically signed. Highest degree of specificity was not assigned to diagnosis. A discrepancy exists between billed diagnosis and actual description of the condition noted

in documentation. Documentation does not indicate a condition as being monitored, evaluated, assessed, or

treated. Cancer status is unclear and treatment is not documented. Chronic conditions such as hepatitis are not documented as chronic. Lack of specificity is an issue, such as unspecified arrhythmia versus a specific type of

arrhythmia. Chronic conditions and status codes are not documented on an annual basis. Required linking language, causal relationship, or manifestation codes are missing.

Barriers

Volume of encounters/records to review

Manual tracking inefficiencies

Prioritizing-which cases need reviewed first?

Physician coding

Impacts of Technology Use

Automation of workflow Improved coverage with prioritization algorithms Coders, CDS and Provider collaboration Reduced Denials secondary to:

– Insufficient provider documentation

– Lack of medical necessity

– Incorrect coding of ICD/CPT/HCPCS codes

Value of Technology UseQuality Drive higher data quality that will enable better patient care and communication Real time documentation integrity and education with providers

Efficiency Save physicians time, close gaps at time of documentation Prioritize patients, improve scheduling and audit timeliness Lifts the manual operation of chart review Allows greater patient/payer coverage

• Able to review more than one specific “set” of patients/payers with same number of staffRevenue Defend against audits Ensure accurate measurement of patient RAF score in support of appropriate reimbursement and bundle

payment Provides more “audit” opportunity

• Identify conditions pre-visit • More accurate reconciliation audits


Reporting & Outcomes Identify patients gaps in RAF score, prioritize schedule and follow up

Transparency into population RAF and progress YTD for reconfirmation

Improved performance, reimbursement in ACO shared savings program

Last thoughts….


Thank you!


Contact InformationKathy Harkness, RN, BSN, CCDS

[email protected]

References

• Cubanski, Juliette et al. “How Much Is Enough? Out-of-Pocket Spending Among Medicare Beneficiaries: A Chartbook.” The Henry J. Kaiser Family Foundation. July 21, 2014.

• Feder, Judith and Jeanne Lambrew. “Why Medicare Matters to People Who Need Long-Term Care.” Health Care Financing Review 18, no. 2 (Winter 1996).

• National Institute of Diabetes and Digestive and Kidney Diseases. “Kidney Disease Statistics for the United States.” December 2016.

• University of California, San Francisco Schools of Pharmacy and Medicine. “The Kidney Project: Creating a Bioartificial Kidney as a Permanent Solution to End Stage Renal Disease: Statistics.”

• Valerie Fernandez ([email protected]) is the manager of coding program development at H.I.M. ON CALL, Inc. and is an AHIMA-approved trainer for ICD-10-CM/PCS.

• Fernandez, Valerie. "Ins and Outs of HCCs" Journal of AHIMA 88, no.6 (June 2017): 54-56.

http://kff.org/medicare/report/how-much-is-enough-out-of-pocket-spending-among-medicare-beneficiaries-a-chartbook/

http://www.ssa.gov/history/pdf/WhyMedicareMatters.pdf

http://www.niddk.nih.gov/health-information/health-statistics/Pages/kidney-disease-statistics-united-states.aspx

https://pharm.ucsf.edu/kidney/need/statistics

mailto:[email protected]

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