cdi horizon: cms' hierarchical · pdf file– diagnosis must be reported ... in...

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Vaughn Matacale, MDDirector, Clinical Documentation Advisor Program

Donald Butler, RN, BSNManager, Clinical Documentation Advisor Program

Vidant Health, Greenville, NC

On the CDI Horizon: CMS' Hierarchical Condition Categories

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Learning Objectives

• At the completion of this educational activity, the learner will be able to:

– Describe the development and refinements of CMS HCCs

– Identify the current applications of the HCC methodology

– Explain strategies to focus CDI activities on enhancing accurate capture of HCC diagnoses

– List the fundamentals required to begin to incorporate HCCs into daily CDI practice

– Collect knowledge enabling a CDI program to develop the possibility of incorporating HCCs into CDI practice

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Literature Review

• Evaluation of the CMS‐HCC Risk Adjustment Model Final Report, Pope et al, March 2011

• https://www.cms.gov/Medicare/Health‐Plans/MedicareAdvtgSpecRateStats/downloads/evaluation_risk_adj_model_2011.pdf

• 2015 Condition‐Specific Measures Updates and Specifications Report Hospital‐Level 30‐Day Risk‐Standardized Readmission Measures

• https://www.cms.gov/Medicare/Quality‐Initiatives‐Patient‐Assessment‐Instruments/HospitalQualityInits/Measure‐Methodology.html

• Also includes information at the link for mortality, payment, and readmission measures

• ACDIS Conference 2015

– CDI for Risk Adjustment Coding; Adele L. Towers, MD, MPH

– Medicare Risk Adjustment, the New Payment Methodology: What Your Physicians Need to Know; Lynn H. Lowery, CPC, CFPC; Trey A. La Charité, MD

• The Healthcare Executive’s Guide to ACO Strategy, 2nd ed, Feb 2015

– http://store.healthleadersmedia.com/the‐healthcare‐executive‐s‐guide‐to‐aco‐strategy‐second‐edition

• Florida Hospital Association Medicare Advantage Payment Methodology and Area Rates for Jan–Dec 2015; June 2014

• https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwjjr6OC9K7LAhULaz4KHbBDAwEQFggcMAA&url=http%3A%2F%2Fwww.fha.org%2FshowDocument.aspx%3Ff%3DMAPaymentMethodology2015.pdf&usg=AFQjCNFp5lfweOsobZjhZDcjMDEcWFNk7g&sig2=wjuGszEWbUNKyQ59szeGaA&bvm=bv.116274245,d.cWw

• The HHS‐HCC Risk Adjustment Model for Individual and Small Group Markets Under the Affordable Care Act, Medicare & Medicaid Research Review, 2014: Vol 4, #3

• https://www.cms.gov/mmrr/Downloads/MMRR2014_004_03_a03.pdf


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Introduce, Define, & Discuss

• Historical development and structure

• Areas of refinement or readjustment

• Initial application current areas of application

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Historical Development and Structure

• CMS recognized a need to prospectively adjust for anticipated costs that varies across beneficiaries

• Specifically wanted to incentivize enrollment of high‐risk and high‐cost patients to Medicare Advantage plans

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Historical Development

• Medicare is one of the largest healthcare programs in the world and has about 50 million beneficiaries. One quarter are enrolled in private health insurance Medicare Advantage (Medicare Part C) plans.

– Medicare Advantage–styled plans have been available on at least a limited basis since 1982

– Medicare Advantage plans are subject to risk‐adjusted capitation payments

– The risk adjustment methodology currently in use is the CMS Hierarchical Condition Categories (HCC) Version 22


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• Pooling of risk as well as risk adjustment are fundamental concepts for all types of insurance (or similar programs)– Pooling of risk among a large population is needed

• To create stable and measurable characteristics that can be used to easily predict future costs

• Spreads the relatively rare risk of high‐medical‐cost events across a large group, so that the majority trade a slightly higher cost of care to protect against catastrophic events and costs

– Risk adjustment methodologies allow for more accurate and predictable cost planning for a given (large enough) population

– Medicare Advantage and ACO/Medicare Shared Savings programs incentivize for both quality and efficiency of care, sharing both the risk and rewards

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• Medicare risk adjustment models over time & explanatory power as measured by R2

– (percentage variation of individual expenditures predicted)

Risk adjustment model Payment years

R2

Adjusted Average Per Capita Cost (AAPCC) Pre‐2000 0.0077 0.8%

Principal Inpatient Diagnostic Cost Group (PIP‐DCG) 2000–2003 0.0550 5.5%

CMS—HCC 2004–2008 0.0997 10%

CMS—HCC Version 12 (2005 recalibration) 2009–2014 0.1091 11%

CMS—HCC Version 21 (2007 recalibration & 2009 clinical revision)

2014–current 0.1246 13%

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• AAPCC– Age, sex, Medicaid enrollment, institutional status, working aged status,

disability status

– County based, and MA paid 95% of county AAPCC

– Five‐year moving averages of per beneficiary spending at the county level for fee‐for‐service Medicare

– Was found to actually increase total Medicare expenditures as MA enrollees healthier than FFS beneficiaries and AAPCC not able to account for this favorable risk selection

• PIP‐DCG– Intended as a transition model, with the initial inclusion of some sort of

health‐based risk adjuster

– Used the most serious principal inpatient diagnosis from the previous year along with demographics similar to AAPCC

– Most serious shortcoming was the restriction to inpatient—no inclusion for outpatient diagnosis or for patients not admitted


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• CMS—HCC model– Developed by researchers with RTI International and Boston University with clinical input from physicians at Harvard

– Incorporates 1 year of diagnosis from inpatient and outpatient settings from a variety of licensed providers

• Physicians, NPs/PAs, … from both hospital inpatient/outpatient and physician office environments

– Easily updated with both ICD coding and clinical changes, as well as with CMS FFS data and experiences

– Diagnosis must be REPORTED every year

• And yes, that does mean if not coded yearly, an above the knee amputation apparently does grow back

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10 principles1. Diagnostic categories should be clinically meaningful

– Should all relate to a reasonably well‐specified disease or medical condition that defines the category

– Conditions must be sufficiently clinically specific to minimize opportunities for gaming or discretionary coding

– Clinical meaningfulness improves the face validity of the classification system to clinicians, its interpretability, and its utility for disease management and quality monitoring

2. Diagnostic categories should predict medical expenditures– Diagnoses should be reasonably homogeneous with respect to

their effect on both current and future yearly costs

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10 principles3. Diagnostic categories that will affect payments should have

adequate sample sizes to permit accurate and stable estimates of expenditures – Diagnostic categories should have adequate sample sizes in available data sets – The data cannot reliably determine the expected cost of extremely rare

diagnostic categories

4. In creating an individual’s clinical profile, hierarchies should be used to characterize the person’s illness level within each disease process, while the effects of unrelated disease processes accumulate – Because each new medical problem adds to an individual’s total disease burden,

unrelated disease processes should increase predicted costs of care. – However, the most severe manifestation of a given disease process principally

defines its impact on costs. Therefore, related conditions should be treated hierarchically, with more severe manifestations of a condition dominating (and zeroing out the effect of) less serious ones.


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10 principles5. The diagnostic classification should encourage specific

coding – Vague diagnostic codes should be grouped with less severe and

lower‐paying diagnostic categories to provide incentives for more specific diagnostic coding

6. The diagnostic classification should not reward coding proliferation – The classification should not measure greater disease burden

simply because more ICD codes are present

– Hence, neither the number of times that a particular code appears, nor the presence of additional, closely related codes that indicate the same condition should increase predicted costs

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10 principles7. Providers should not be penalized for recording

additional diagnoses (monotonicity) – This principle has two consequences for modeling:

1) No condition category (CC) should carry a negative payment weight, and

2) A condition that is higher‐ranked in a disease hierarchy (causing lower‐rank diagnoses to be ignored) should have at least as large a payment weight as lower‐ranked conditions in the same hierarchy

8. The classification system should be internally consistent (transitive)– If diagnostic category A is higher ranked than category B in a

disease hierarchy, and category B is higher ranked than category C, then category A should be higher ranked than category C

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10 principles9. The diagnostic classification should assign all ICD‐9/10‐

CM codes (exhaustive classification) – Because each diagnostic code potentially contains relevant

clinical information, the classification should categorize all ICD codes

10. Discretionary diagnostic categories should be excluded from payment models – Diagnoses that are particularly subject to intentional or

unintentional discretionary coding variation or inappropriate coding by health plans/providers, or that are not clinically or empirically credible as cost predictors, should not increase cost predictions

– Excluding these diagnoses reduces the sensitivity of the model to coding variation, coding proliferation, gaming, and upcoding


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• Principles 7 (monotonicity), 8 (transitivity), and 9 (exhaustive classifications) were followed absolutely

• There are trade‐offs among other principles– Clinical meaningfulness (1) drives toward a larger number of detailed

groups vs. adequate sample sizes (3)

– Specific coding (5) vs predictive power (2)—if non‐specific codes are excluded, there may be a loss of predictive power

– Excluding discretionary codes (10) can also lower predictive power (2)

• The trade‐offs were approached in model development– Empirical evidence on frequencies and predictive power

– Clinical judgment on relatedness, specificity, and severity of diagnosis

– Professional judgment on incentives and likely provider responses to classification systems

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CMS HCC Structure

• HCC development & structure (V21)– Diagnostic groups, condition categories, & hierarchies

• Hierarchy examples (V22)

• Additional HCC weight factors (V22)– Demographics

– Disease interactions

• Note, V22 is the current version with ICD‐10, same concepts; differences in specific numbers, example HCC n = 79

• Also some changes in a few of the categories and hierarchies• Best available reference however discusses V21

• Note, V22 is the current version with ICD‐10, same concepts; differences in specific numbers, example HCC n = 79

• Also some changes in a few of the categories and hierarchies• Best available reference however discusses V21

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CMS HCC Version 21 Development

• Additional Medicare risk assessment weight factors

– Demographics

• Age

• Disability status

• Community vs. institutionalized

• Medicaid

• ESRD is separate


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ICD‐9 codes (n = 14,000+)ICD‐9 codes (n = 14,000+)

Diagnostic Groups (DXGs) (n = 805)Diagnostic Groups (DXGs) (n = 805)

Condition Categories (CCs) (n = 189)Condition Categories (CCs) (n = 189)

Hierarchical Condition Categories (HCCs) (n = 189)Hierarchical Condition Categories (HCCs) (n = 189)

CMS Hierarchical Condition Categories (n = 70)CMS Hierarchical Condition Categories (n = 70)

Hierarchies imposedHierarchies imposed

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• Each Diagnostic Group represents a well‐specified medical condition

• Condition Categories describe a broader set of similar diseases that are related clinically and have similar cost

• Finally, the Hierarchies are imposed to ensure that a person is credited (or applied weight) with the most severe manifestation of related diseases

• HCCs are also grouped from an organizational standpoint into body systems

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CMS HCC Hierarchy Structure

Category

short name

HCC For these HCCs,

drop the listed

HCCs

Description Community

Diabetes HCC 17 18, 19 Diabetes with acute complications 0.368

HCC 18 19 Diabetes with chronic complications 0.368

HCC 19 Diabetes without complication 0.118

Vascular HCC 106 107, 108, 161,

189

Atherosclerosis of the extremities

with ulceration or gangrene

1.413

HCC 107 108 Vascular disease with complications 0.410

HCC 108 Vascular disease 0.299

HCC 161 Chronic ulcer of skin, except

pressure

0.536

HCC 189 Amputation status, lower

limb/amputation complications

0.779


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Example: Diabetes HCCs & Hierarchy

HCC 17 (0.368)Diabetes with acute complications

HCC 17 (0.368)Diabetes with acute complications

HCC 18 (0.368)Diabetes with chronic complications

HCC 18 (0.368)Diabetes with chronic complications

HCC 19 (0.118)Diabetes without complication


HCC 17 HCC 18 HCC 19DM (1 or 2 or induced) with • Coma or • Hyperosmolarity or • Ketoacidosis

DM (1 or 2 or induced) with: • Nephropathy; CKD; other kidney complication; retinopathy; cataract; neuropathy; other neuro complication; peripheral angiopathy; neuropathic arthropathy; dermatitis; ulcer; periodontal disease; hyperglycemia; hypoglycemia without coma

DM

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Detail of HCC 19



Diagnosis code

Description CMS‐HCC model category V22

E089 Diabetes mellitus due to underlying condition without complications 19E099 Drug or chemical induced diabetes mellitus without complications 19E109 Type 1 diabetes mellitus without complications 19E119 Type 2 diabetes mellitus without complications 19E139 Other specified diabetes mellitus without complications 19Z794 Long‐term (current) use of insulin 19

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Example: Cardiac HCCs & Hierarchy

HCC 86 (0.275) Acute myocardial infarctionHCC 86 (0.275) Acute myocardial infarction

HCC 87 (0.258) Unstable angina and other acute ischemic heart diseaseHCC 87 (0.258) Unstable angina and other acute ischemic heart disease

HCC 88 (0.141) Angina pectorisHCC 88 (0.141) Angina pectoris

HCC 86 HCC 87 HCC 88• STEMI or NSTEMI• Subsequent STEMI or NSTEMI• Chordae tendinea or papillary

muscle rupture (current complication following AMI or NEC)

• USA (with OR without identified atherosclerotic heart disease of vessels or grafts)

• Current complications following AMI: Hemopericardium; Atrial or ventricular septal defects; Thrombosis of atrium, auricular appendage and ventricle;

• Acute ischemic heart disease• Postinfarction angina; Dressler’s syndrome

• Angina pectoris,

unspecified (as well as

specified atherosclerotic

heart disease; as well as

with spasm)

HCC 96: Specified heart arrhythmias (0.295)

• Complete AV block• SVT, VT, re‐entry ventricular arrhythmia• A‐fib or A‐flutter (unspecified or specified)• Sick sinus syndrome

HCC 85: Congestive heart failure (0.368)

• Multiple: Cardiomyopathies; HF; PE• Pulmonary hypertension


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Example: Neoplasm HCCs & Hierarchy

HCC 8 (2.484)Metastatic cancer and acute leukemia

HCC 8 (2.484)Metastatic cancer and acute leukemia

HCC 9 (0.973)Lung and other severe cancers

HCC 9 (0.973)Lung and other severe cancers

HCC 10 (0.672)Lymphoma and other cancers

HCC 10 (0.672)Lymphoma and other cancers

HCC 11 (0.317)Colorectal, bladder, and other cancers

HCC 11 (0.317)Colorectal, bladder, and other cancers

HCC 12 (0.154)Breast, prostate, and other cancers and tumors

HCC 12 (0.154)Breast, prostate, and other cancers and tumors

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Example: Neoplasm HCCs & Hierarchy

HCC 8: Metastatic cancer

and acute leukemia

HCC 9: Lung and other

severe cancers

HCC 10: Lymphoma and other

cancers• (almost) Any metastatic site• Disseminated malignant neoplasm

unspecified• Various ACUTE leukemias

• Esophagus, stomach, small intestine• Meckel’s diverticulummalignant• Liver, bile duct, gall bladder, pancreas• Trachea, lung• Mesothelioma, unspec & sites• Multiple myeloma• Chronic leukemias• Myeloid sarcoma & leukemia• Monocytic or mast cell or other

specified leukemias• KS

• Various neoplasms not included elsewhere

(includes 114 codes)

• Metastatic dz of UNSPECIFIED lymph node;

axilla & upper limb nodes; skin, breast,

genital organs

• Malignant immunoproliferative dz

• Plasmacytoma

• Leukemias:

Chronic lymphocytic; prolymphocytic, hairy

cell, lymphoid, Burket, UNSPECIFIED

HCC 11: Colorectal, bladder, and other cancers

HCC 12: Breast, prostate, and other cancers and tumors

• Head & neck structures(oral structures; pharynx, oropharynx, nasopharynx; larynx & associated; ear, nasal, sinuses)

• Additional GI(large bowel structures including anus; spleen; UNSPECIFIEDintestinal tract)

• Heart & mediastinum• UNSPECIFIED parts of upper respiratory tract• Female genital organs (NOT uterus)• Urinary organs—kidney, bladder, etc.

• Melanoma sites• Merkel cell carcinoma• Breast & structures• Uterus• Male genital organs• Eye structures

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Example: Vascular

HCC 106 (1.413)Atherosclerosis of the extremities with ulceration or gangrene

HCC 106 (1.413)Atherosclerosis of the extremities with ulceration or gangrene

HCC 107 (0.410)Vascular disease with complications

HCC 107 (0.410)Vascular disease with complications

HCC 108 (0.299)Vascular diseaseHCC 108 (0.299)Vascular disease

HCC 161 (0.536)Chronic ulcer of skin,

except pressure

HCC 161 (0.536)Chronic ulcer of skin,

except pressure

HCC 189 (0.779)Amputation status, lower limb/amputation complications

HCC 189 (0.779)Amputation status, lower limb/amputation complications


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• CMS HCC disease interactions

– The presence of specific combinations of HCCs provides a “bonus” weight, which is in ADDITION to the existing HCC weights

– These disease interactions are presented in detail over the next 4 slides

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Disease Interactions (Community Based)

• CANCER_IMMUNE Cancer*Immune Disorders 0.947

• CHF_COPD Congestive Heart Failure*Chronic Obstructive Pulmonary Disease 0.259

• CHF_RENAL Congestive Heart Failure*Renal Disease 0.317

• COPD_CARD_ RESP_FAIL Chronic Obstructive Pulmonary Disease*Cardiorespiratory Failure 0.456

• DIABETES_CHF Diabetes*Congestive Heart Failure 0.182

• SEPSIS_CARD_RESP_FAIL Sepsis*Cardiorespiratory Failure 0.214

• Sepsis = HCC 2 • Cancer = HCCs 8–12 • Diabetes = HCCs 17–19 • Immune Disorders =

HCC 47 • Cardiorespiratory

Failure = HCCs 82–84 • Congestive Heart

Failure = HCC 85 • Chronic Obstructive

Pulmonary Disease = HCCs 110–111

• Renal Disease = HCCs 134–137

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Disease Interactions (Institutional Based)

• CHF_COPD Congestive Heart Failure*Chronic Obstructive Pulmonary Disease 0.221

• COPD_CARD_RESP_FAIL Chronic Obstructive Pulmonary Disease*Cardiorespiratory Failure 0.506

• DIABETES _CHF Diabetes*Congestive Heart Failure 0.189

• ARTIF_OPENINGS_PRESSURE_ULCER Artificial Openings for Feeding or Elimination*Pressure Ulcer 0.282

• ASP_SPEC_BACT_PNEUM_PRES_ULCER Aspiration and Specified Bacterial Pneumonias*Pressure Ulcer 0.495

• COPD_ASP_SPEC_BACT_PNEUM Chronic Obstructive Pulmonary Disease*Aspiration and Specified Bacterial Pneumonias 0.319

• SCHIZOPHRENIA_CHF Schizophrenia*Congestive Heart Failure 0.212

• SCHIZOPHRENIA_COPD Schizophrenia*Chronic Obstructive Pulmonary Disease 0.389

• SCHIZOPHRENIA_SEIZURES Schizophrenia*Seizure Disorders and Convulsions 0.452

• SEPSIS_ARTIF_OPENINGS Sepsis*Artificial Openings for Feeding or Elimination 0.553

• SEPSIS_ASP_SPEC_BACT_PNEUM Sepsis*Aspiration and Specified Bacterial Pneumonias 0.339

• SEPSIS_PRESSURE_ULCER Sepsis*Pressure Ulcer 0.522

• Sepsis = HCC 2.

• Diabetes = HCCs 17–19.

• Cardiorespiratory Failure = HCCs 82–84.

• Congestive Heart Failure = HCC 85.

• Chronic Obstructive Pulmonary Disease = HCCs 110–111.

• Schizophrenia = HCC 57.

• Seizure Disorders and Convulsions = HCC 79.

• Aspiration and Specified Bacterial Pneumonias = HCC 114.

• Pressure Ulcer = HCCs 157–158. HCCs 159–160 are no longer included in the pressure ulcer interaction terms.

• Chronic Ulcer of Skin, except Pressure = HCC 161.

• Artificial Openings for Feedings or Elimination = HCC 188.


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Disabled Interactions

COMMUNITY

• D_HCC5 AND DISABLED_HCC6 Disabled, Opportunistic Infections 0.451

• DISABLED_HCC34 Disabled, Chronic Pancreatitis 0.548

• D_HCC44 AND DISABLED_HCC46 Disabled, Severe Hematological Disorders 1.347

• D_HCC51 AND DISABLED_HCC54 Disabled, Drug/Alcohol Psychosis 0.331

• D_HCC52 AND DISABLED_HCC55 Disabled, Drug/Alcohol Dependence 0.331

• D_HCC107 AND DISABLED_HCC110 Disabled, Cystic Fibrosis 2.415

• DISABLED_HCC176 Disabled, Complications of Specified Implanted Device or Graft 0.503

INSTITUTIONAL

• DISABLED_HCC39 Disabled, Bone/Joint Muscle Infections/Necrosis 0.383

• DISABLED_HCC77 Disabled, Multiple Sclerosis 0.407

• DISABLED_HCC85 Disabled, Congestive Heart Failure 0.441

• DISABLED_HCC161 Disabled, Chronic Ulcer of the Skin, Except Pressure Ulcer 0.430

• DISABLED_PRESSURE_ULCER Disabled, Pressure Ulcer 0.270

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Current Areas of Application:HCC Success = Expansion Into Other Applications

• ACOs

• Physician VBP: Physician services payment in the outpatient setting

• Risk adjustment (specifically re‐admits & mortality measures)

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Initial Application Current Areas of Application

Medicare risk adjustment (i.e., HCC system) applies to:

• ACOs & Medicare Advantage plans

• Hospital Value‐Based Purchasing (FY2016 1.75%)• 30‐day all‐cause mortality

• AMI, HF, PNA

• Care/cost efficiency

• Readmissions Reduction Program (HRRP) (FY2016 3%)• AMI, HF, PNA (expanding FY17), COPD, elective knee/hip, CABG (FY17)

• Physician VBP: Physician services payment (outpatient setting)• Combines quality and risk‐adjusted cost efficiency:

• Starting Jan 2015 100+ providers now ‐2% to +3%

• Starting Jan 2016 10–99 providers now 0% to 3%

• HHS—HCC model for the ACA marketplace


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ACO and Medicare Advantage Application of HCCs

• CMS’ goal is to move away from fee‐for‐service models and toward population health

• Moving incentives from volume of care and services to efficiency and quality of care and services

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• Relies upon the use of predictive models of cost (risk adjustment)

– Data from this year used to predict the costs for the next year

– Medicare Advantage

• Provides a health plan with prospective payment

• Efficiency yields less expenditures and money is saved

– ACO/MSSP

• Use data to estimate the predicted costs

• If quality goals are met, and savings exceed a set threshold, then shared savings are achieved

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How is this done?• Medicare risk adjustment

– Redistributes payments in favor of those providing care to higher‐risk populations

– Transfer of funds from low‐risk populations to high‐risk populations

– HCC‐based system

– Based on claims data (diagnosis codes) and demographics

• General formula

CMS rate Demographic weight

HCC weight

Exp cost/reimburse

ment


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Clinical Example of HCC Application and Impact

Documentation from an outpatient encounter

75 y/o female presents for ankle sprain and follow‐up

Assessment and plan:

• Ankle sprain—ice avoid NSAIDs due to CKD. Check BMP.

• Colon cancer—s/p colectomy and liver bx. Following with heme/onc for chemo. Check CBC, LFTs.

• Type 2 DM—insulin adjusted.

• CAD—CP at rest, cardiology eval, increase beta blocker.

• Hypertension—continue current meds.

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Diagnoses on the Claim

Submitted by provider

C189 Malignant neoplasm of colon

E119 Type 2 DM

N189 CKD

I208 Angina

S93402A Ankle sprain

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HCC Weights Applied to MD Claim Dx

Factor/diagnosis HCC HCC weight

75‐year‐old female Demographics 0.437

C189Malignant neoplasm of colon11—Colorectal bladder and other cancers

0.317

E119 Type 2 DM 19—Diabetes without complication

0.118

N189 CKD ‐‐‐ 0

I208 Angina 88—Angina pectoris 0.141

S93402A Ankle sprain ‐‐‐ 0

Total risk 1.013

Expected cost/reimbursement $7,200


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Improvement in Documentation

Documentation from an outpatient encounter75 y/o female presents for ankle sprain and follow‐upAssessment and plan:• Ankle sprain—acute, ice avoid NSAIDs due to CKD. Check

BMP.• Colon cancer with liver mets—active, s/p colectomy and

liver bx. Following with heme/onc for chemo. Check CBC, LFTs.

• Type 2 DM with diabetic CKD 4—stable, insulin adjusted.• CAD—unstable angina, active, cards referral, increase beta

blocker.• Hypertension—stable, continue current meds.

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Improved Codes

New diagnoses HCC HCC weight



0.317

C787 Secondary neoplasm of liver8—Metastatic cancer and acute leukemia

2.484

E1122 Type 2 DM with diabetic CKD18—Diabetes with chronic complication

0.368

N184 CKD 4 137—CKD severe stage 4 0.224

I200 Unstable angina87—Unstable angina andother acute isch hrt dz

0.258


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Applying the Hierarchies

HCC 12

0.154

• Breast, Prostate, and other cancers and tumors

HCC 11

0.317

• Colorectal, bladder, and other cancers

HCC 10

0.672

• Lymphoma and other cancers

HCC 90.973

• Lung and other cancers

HCC 8

2.484

• Metastatic cancer and acute leukemia


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Revised HCC Weights

New diagnoses HCC HCC weight



xxxx

C787 Secondary neoplasm of liver8—Metastatic cancer and acute leukemia

2.484

E1122 Type 2 DM with diabetic CKD18—Diabetes with chronic complication

0.368

N184 CKD 4 137—CKD severe stage 4 0.224

I200 Unstable angina87—Unstable angina andother acute isch hrt dz

0.258


Total risk 3.771

Expected cost/reimbursement $26,379

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HCC Expansion

Risk adjustment (specifically re‐admits & mortality measures)

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CMS Mortality & Readmission Risk Adjustment Overview

• Model unique for each mortality or readmission condition, though similar pattern

• Certain Condition Categories are included in the risk adjustment calculation – (NOT hierarchical)

• 12‐month look‐back for diagnosis (from index admit)• Certain diagnosis if occurring only during the index

admission are excluded—as likely complications of that index admission

• FY15 baseline data includes index admissions– July 2011 to June 2014– Both CMS and VA (VA for AMI, HF & PNA) administrative data

sources


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Example: HF Readmission Cohort Criteria

Inclusion criteria for HF measure

• Principal discharge diagnosis of HF – Rationale: HF is the condition targeted

for measurement (Table D.2.1).

• Enrolled in Medicare FFS or are VA beneficiaries

– Rationale: Claims data are consistently available only for Medicare FFS and VA beneficiaries.

• Age 65 or over – Rationale: Medicare patients younger

than 65 usually qualify for the program due to severe disability. They are not included in the measure because they are considered to be too clinically distinct from Medicare patients 65 and over.

• Discharged alive from a non‐federal acute care hospital or VA hospital

– Rationale: Patients who are alive are eligible for a readmission.

• Not transferred to another acute care facility

– Rationale: Readmission is attributed to the hospital that discharged the patient to the non‐acute care setting. Transferred patients are still included in the measure cohort, but the initial admitting hospital is not accountable for the outcome.

• Enrolled in Part A and Part B Medicare for the 12 months prior to the date of admission, and enrolled in Part A during the index admission

– Rationale: The 12‐month prior enrollment criterion ensures that patients were Medicare FFS beneficiaries and that their comorbidities are captured from claims for risk adjustment. Medicare Part A is required at the time of admission to ensure no Medicare Advantage patients are included in the measure. This requirement is dropped for patients with an index admission within a VA hospital.

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Example: HF Readmission Cohort Criteria

Exclusion criteria for HF measure

• Without at least 30 days of post‐discharge enrollment in FFS Medicare

– Rationale: The 30‐day readmission outcome cannot be assessed in this group since claims data are used to determine whether a patient was readmitted

• Discharged against medical advice (AMA)

– Rationale: Providers did not have the opportunity to deliver full care and prepare the patient for discharge

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Example: HF Readmission Risk Variables (2015)

• Variable Description

• n/a Age minus 65 (years above 65, continuous)

• n/a Male

• ICD‐9 codes V45.81, 36.10–36.16 History of coronary artery bypass graft (CABG)

• CC 7 Metastatic cancer or acute leukemia

• CC 8–12 Cancer

• CC 15–20, 119–120 Diabetes mellitus (DM) or DM complications

• CC 21 Protein‐calorie malnutrition

• CC 22–23 Disorders of fluid/electrolyte/acid‐base

• CC 25–30 Liver or biliary disease

• CC 34 Peptic ulcer, hemorrhage, other specified gastrointestinal disorders

• CC 36 Other gastrointestinal disorders

• CC 44 Severe hematological disorders

• CC 47 Iron deficiency or other unspecified anemias and blood disease

• CC 49–50 Dementia or other specified brain disorders

• CC 51–53 Drug/alcohol abuse/dependence/psychosis

• CC 54–56 Major psychiatric disorders

• CC 58 Depression

• CC 60 Other psychiatric disorders

• CC 67–69, 100–102, 177–178 Hemiplegia, paraplegia, paralysis, functional disability

• CC 79 Cardiorespiratory failure or shock

• CC 80 Congestive heart failure

• CC 81–82 Acute coronary syndrome

• CC 83–84 Coronary atherosclerosis or angina

• CC 86 Valvular or rheumatic heart disease

• CC 92–93 Specified arrhythmias and other heart rhythm disorders

• CC 94 Other or unspecified heart disease

• CC 95–96 Stroke

• CC 104–106 Vascular or circulatory disease

• CC 108 Chronic obstructive pulmonary disease (COPD)

• CC 109 Fibrosis of lung or other chronic lung disorders

• CC 110 Asthma

• CC 111–113 Pneumonia

• CC 129–130 End‐stage renal disease or dialysis

• CC 131 Renal failure

• CC 132 Nephritis

• CC 136 Other urinary tract disorders

• CC 148–149 Decubitus ulcer or chronic skin ulcer


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Example: HF Readmission Risk Variables EXCLUDED (2015)

• Variable Description

• CC 17 Diabetes with acute complications

• CC 23 Disorders of fluid/electrolyte/acid‐base

• CC 28 Acute liver failure/disease

• CC 34 Peptic ulcer, hemorrhage, other specified gastrointestinal disorders

• CC 79 Cardiorespiratory failure and shock

• CC 80 Congestive heart failure

• CC 81 Acute myocardial infarction

• CC 82 Other acute/subacute forms of ischemic heart disease

• CC 92 Specified heart arrhythmias

• CC 93 Other heart rhythm and conduction disorders

• CC 95 Cerebral hemorrhage

• CC 96 Ischemic or unspecified stroke

• CC 100 Hemiplegia/hemiparesis

• CC 101 Diplegia (upper), monoplegia, and other paralytic syndromes

• CC 102 Speech, language, cognitive, perceptual

• CC 104 Vascular disease with complications

• CC 105 Vascular disease

• CC 106 Other circulatory disease

• CC 111 Aspiration and specified bacterial pneumonias

• CC 112 Pneumococcal pneumonia, emphysema, lung abscess

• CC 129 End‐stage renal disease

• CC 130 Dialysis status

• CC 131 Renal failure

• CC 132 Nephritis

• CC 148 Decubitus ulcer of skin

• CC 177 Amputation status, lower limb/amputation

• CC 178 Amputation status, upper limb Excluded from risk adjustment if ONLY occurrence of the dx is from the index admission

50

Operational Considerations: HCCs

• CDI workflows

• CDI concepts

• Application of CDI resources

51

Traditional CDI & HCCs

• Natural component of the CDI approach to focus:

– Completeness and accuracy without regard to financial or other focused concerns

– This approach attempts to capture all relevant codes to the highest levels of specificity

– Naturally leads to better HCC capture and profiles


52

Traditional CDI & HCCs: MUSIC

MUSIC (Dr. James Kennedy)

• Manifestation– Chest pain

• Underlying cause or pathology– Angina, GERD, CAD, coronary spasm, complication of stent, etc.

• Severity or Specificity– Stable or unstable angina, AMI

• Instigating or precipitating cause– Cocaine abuse, trauma, anemia, etc.

• Complications or Consequences– Shock, acute systolic heart failure, ventricular tachycardia, etc.

• Place a diagnosis existing in the medical record into the appropriate category, then look for the other four– Either documented or clinically indicated

– Obtain the appropriate linkages needed (due to, resulting, etc.)

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Operational Areas of Focus

• Inpatient:

– Improving perceived readmission, mortality, and cost‐efficiency measures by impacting the EXPECTED side of these measures

• Outpatient:

– Physician payments

• ACO—combined inpatient and outpatient areas

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Operational Areas of Focus

Inpatient setting• Existing CDI programs

– Layer HCC into existing

• Professional coding staff• Identify areas of primary

focus – Subset

• (Specific readmit or mortality measures)

– All HCC categories in play• Cost‐efficiency measure

• Support partner/related ACO

• Leverage with MA plans

Outpatient setting• Rare CDI existing program• Often no professional coding

(physicians report codes)• Most patients do not have

acute inpatient stay• Much larger volume• Leverage processes of care• Possible key resource—

existing MA contractor• Focus:

– All HCCs in play

• Availability of software/EHR/data analytics tools• Education and knowledge to providers VS. chart review


55

Traditional CDI & HCCs

• Conceptual low‐hanging fruit:– Commonly missed HCC Dxs– CMS HCC disease interactions– Linkage (due to)– Move up the hierarchy

• Diagnosis NOT INCLUDED:– Documentation present but not billed– Clinical evidence without documentation– Absence of chronic conditions in documentation– Self‐imposed limits on # of codes reported

• Related diagnosis– COPD/CHF/O2 use: Chronic respiratory failure– cancer/dementia: malnutrition

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Operational Considerations: CDI Applied to ACO and MA Models

• Fundamental concepts

• Opportunity analysis

• Strategic application

57

Before We Start …

Fundamental concepts to set the stage• HCC score (MRA) is reset to 0 each year

– Diagnoses must be resubmitted on ANY claim at least once EACH year

• Amputations grow back

• All diseases cured

• ACO HCC scores may be locked in for a 3‐year cycle– They can decrease annually

– They do not increase annually

• Newly attributed patients (new to Medicare) need to establish an HCC score


58

Before We Start …

Fundamental concepts to set the stage• Concepts for reportability, documentation, and coding still

apply – MEAT (monitored, evaluated, assessed, treated)– Face‐to‐face encounter– Condition on claim must match the documentation– Each diagnosis should have an assessment and plan

• Documentation:– Legible, physician signature & credential, dated– Condition status, labs, exam, symptoms, education, plan– Code ALL conditions that affect the patient’s care at time of visit

• Common CDI principles & concerns apply• ASSUME CMS will audit

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How Do You Apply a Limited Resource to a Large Problem?

Find high‐opportunity targets and issues• Frequency of unspecified codes

• Patient volumes and HCC score per provider

• Identify high‐volume users of unspecified codes (e.g., diabetes)

• Cost of care and HCC score per provider

• New providers—start them on the right track

• Patients with no HCC score (other than demographics)

• Unmanaged patients

• ?? use of registries, benchmarked dx capture

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How Do You Apply a Limited Resource to a Large Problem?

Timing for “capture” opportunities

• Newly attributed patients

– Build the HCC score

• Annual wellness visits

– Reaffirm old diagnoses

– Establish new diagnoses

– Clarify disease interactions and relationships

– Specify unspecified


61

Leverage Your Assets With CDI Knowledge

Tools to use• EHR

– BPAs• DM and related conditions• CKD staging• Obesity, other diagnoses

– Diagnosis picker/calculator• Help get to specified codes• Assist providers to get required details and complications/manifestations

– Problem list and templates• Ensure documentation and claims data match• GET RID OF “HISTORY OF”

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Use Your Staff Wisely

Where can CDI directly impact OP?It’s impossible to review all visits for all patients.

• Prescreen annual wellness visits– Look for HCC opportunities– Pre‐populate the documentation issues for the provider– Continuous workload (as opposed to end‐of‐year blitz)

• Work with OP coding/audit team (if you have one)– Examine audit results (missing dx, unsupported dx, unspecified

dx)– Train the audit team to look for opportunities for feedback to the

providers

• Train annual wellness visit nurses• Train physicians and providers

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Use Your Staff Wisely

How can we utilize existing CDI processes?

A portion of your ACO/MA patients will be seen for inpatient care.

• Add areas of HCC knowledge and focus for your inpatient CDI staff

– DM and manifestations

– Secondary sites of cancer

– Comorbid conditions (PVD, COPD, angina, etc.)


64

Modes of Communication

How can/should CDI staff spread the word?• Documentation tips

– Hit the hot topics/low‐hanging fruit

• Office visits– Lunch and learns

– Staff meetings

– Annual wellness training

• New provider training– Hit the highlights for good documentation and coding

• Collect and use case examples– Audit results (internal or external)

• Video training– Saves time and repetition

– Can be accessed anytime

65

Summary

66

Summary

• RISK ADJUSTMENT methodologies are widespread

• Dig into literature review and associated web pages

• Provider education (repeated, focused, motivate)

– Use data analysis to prioritize initial & focus

• Understand & leverage hierarchy structure

• Time frame RESETS

• Leverage existing data, tools, & processes of care

– BPAs, EHR, Dx picker/calculator, etc.

• Process of care—annual wellness visits


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Summary: Diagnostic Low‐Hanging Fruit

• Morbid obesity• Malnutrition• CKD staging (4 or 5)• Complications of care

– Mechanical problems– Prosthetic devices– Infections– Implants– Grafts

• PVD/claudication• Diabetes manifestations• Afib, PSVT

• Cirrhosis (due to …)• Transplant status• Artificial openings• Amputation status• Late effects of CVAs• Status of MIs • Neoplasms and metastatic cancers

• ESRD and the need for dialysis (HD or PD)

• Major depression, etc.

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Summary: Broad Strategies

• Diagnosis capture– Moving up within a hierarchy

• Cancer, diabetes, cardiac

– Related Condition Category

• Commonly coexisting diagnosis to capture

– Increasing specificity of existing diagnosis

– Complete capture of ALL conditions

• Monitored, evaluated, assessed, treated

– Supportive documentation present for reported codes

• Additionally worth focus– Vascular/PVD; skin/ulcer; end‐stage liver dz; spinal

• Review and understand ALL of the hierarchies

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Thank you. Questions?

[email protected]@vidanthealth.com

In order to receive your continuing education certificate(s) for this program, you must complete the online evaluation. The link can be found in the continuing education section at the front of the program guide.

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