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

Transcription

1 Claims vs. Submission: Understanding the Difference Sonia Trepina, MPA Director, Risk Adjustment & Ambulatory CDI Services Enjoin Asheville, NC Brett Senor, MD, CRC, CCDS Physician Associate, CDI Quality Initiatives Enjoin Asheville, NC 1 Learning Objectives At the completion of this educational activity, the learner will be able to understand: Describe how HCCs are submitted to and validated by CMS Discuss challenges of claims and submission processes Identify the impact of the varying processes on an organization s risk scores Explain how CDI can support accuracy and specificity for risk adjustment capture and scoring 2

2 3 Polling Question #1 What department/role do you represent? 1. CDI 2. Coding 3. Data analytics 4. Compliance 5. Other 4

3 Polling Question #2 What is your familiarity with HCCs? 1. I understand the concept and details 2. I understand the concept but have not worked with HCCs 3. I ve heard the term before but don t know what it means 4. I ve never heard of HCCs before 5 What Are HCCs? One risk adjustment methodology Predicts or explains future healthcare expenditures of individuals based on diagnoses and demographics Predicts the variations in resources required to care for different patients and to reimburse providers appropriately based on those variables Used for Medicare Advantage payment models, ACOs Age, Sex, Disability Status, etc. Health Status Adjusts Future Payments 6

4 CMS Hierarchical Condition Categories (HCC) HCC requirements: Face to face qualifying visit >71,000 ICD 10 codes (conditions) Eligible provider type Supported by documentation Captured at least once per calendar year 9,500 ICD 10 codes associated with increased resource intensity 79 categories (HCCs) 7 CMS Hierarchical Condition Categories (HCC) A coefficient or weight is assigned to each category of chronic complex diagnoses as well as severe acute diagnoses Each HCC that applies is additive HCC Category Description Label Coefficient HCC01 HIV/AIDS HCC02 Septicemia, Sepsis, Systemic Inflammatory Response Syndrome/Shock HCC06 Opportunistic Infections HCC08 Metastatic Cancer and Acute Leukemia HCC09 Lung and Other Severe Cancers HCC10 Lymphoma and Other Cancers HCC11 Colorectal, Bladder, and Other Cancers HCC12 Breast, Prostate, and Other Cancers and Tumors HCC17 Diabetes with Acute Complications HCC18 Diabetes with Chronic Complications HCC19 Diabetes without Complication HCC21 Protein Calorie Malnutrition HCC22 Morbid Obesity HCC23 Other Significant Endocrine and Metabolic Disorders HCC27 End Stage Liver Disease HCC28 Cirrhosis of Liver E0800 E0801 E0810 E0811 E08641 E0900 Diabetes mellitus due to underlying condition with hyperosmolarity without nonketotic hyperglycemic hyperosmolar coma (NKHHC) Diabetes mellitus due to underlying condition with hyperosmolarity with coma Diabetes mellitus due to underlying condition with ketoacidosis without coma Diabetes mellitus due to underlying condition with ketoacidosis with coma Diabetes mellitus due to underlying condition with hypoglycemia with coma Drug or chemical induced diabetes mellitus with hyperosmolarity without nonketotic hyperglycemic hyperosmolar coma (NKHHC) 8

5 CMS Hierarchical Condition Categories (HCC) HCCs are grouped into related families Disease groupings with progressively higher severi es Establishes a hierarchy that allows the highest severity to receive the highest "weight" CMS pays for the most severe form of disease reported in a given year HCC Category Description Label HCC08 Metastatic Cancer and Acute Leukemia HCC09 Lung and Other Severe Cancers HCC10 Lymphoma and Other Cancers HCC11 Colorectal, Bladder, and Other Cancers HCC12 Breast, Prostate, and Other Cancers and Tumors Hierarchical Condition Category If the Disease Group is Listed in this column (HCC) Hierarchical Condition Category (HCC) LABEL 8 Metastatic Cancer and Acute Leukemia 9 Lung and Other Severe Cancers 10 Lymphoma and Other Cancers 11 Colorectal, Bladder, and Other Cancers Coefficient Then drop the Disease Group(s) listed in this column 9,10,11,12 10,11,12 11, CMS Hierarchical Condition Categories (HCC) Some combinations of diseases have a synergistic impact on complexity and cost When both conditions are documented, coded and submitted on claim: The weights from both conditions are added Model triggers an additional increase in RAF score Disease interaction description label Weight Cancer*Immune Disorders Congestive Heart Failure*Diabetes Group Congestive Heart Failure*Chronic Obstructive Pulmonary Disease Congestive Heart Failure*Renal Group Cardiorespiratory Failure Group*Chronic Obstructive Pulmonary Disease Group CY 2018 disease interactions and weights Community, NonDual, Aged category weight 10

6 How It All Adds Up All conditions precisely documented Demographics 84 yr old Female -- Full Benefit (FB) dual aged Diagnoses supported in encounter documentation Interaction coefficients added by CMS Risk score COPD J44.9 (HCC 111) Type II Diabetes w/ Diabetic CKD E11.22 (HCC 18) CKD Stage 5 N18.5 (HCC 136) Chronic Diastolic CHF I (HCC 85) Disease Interaction (Diabetes and CHF) Disease Interaction (CHF and Renal Failure) Disease Interaction (CHF and COPD) Total RAF: (Demographics and HCC) PMPM Payment $2,066 Risk adjustment payment Annual Payment $24,787 $800 PMPM base rate. Values are for illustrative purposes only 11 When Are Diagnoses Used for HCC Capture? Quality program submission ACO submission Medicare Advantage (MA) submission Changes in submission process for MA Percent /FFS/ 12

7 MA Submission Processes/Systems Fee for service (FFS) claims Risk Adjustment Processing System () CSSCOperations MA Communications Handbook Amazon CMS 1500 order Encounter data system Risk Adjustment Model Updates Data used to calculate risk scores: 75% calculated with 2017 CMS HCC model and diagnoses submitted on and FFS claims 25% calculated 2019 CMS HCC model (without count variable) and diagnoses submitted on encounter data records, inpatient records, and FFS claims 14

8 Encounter Data Transition Transition Plan Actual Centers for Medicare & Medicaid Services Transition from Risk Adjustment Processing System () Data to Medicare Advantage (MA) Encounter Data for Risk Score Calculation; GAO Medicare Advantage Rates & Statistics; Announcements ; Plans/MedicareAdvtgSpecRateStats/Announcements and Documents.html?DLSort=2&DLEntries=10&DLPage=1&DLSortDir=descending. 15 Encounter Data Process Providers Submit Data MAO Submit Data CMS EDFES Edits CMS EDPS Edits & Format Data CMS IDR Stores Data Encounter Data Front End System (EDFES) edits Encounter Data Processing System (EDPS) edits DME claims Professional claims Institutional claims Integrated Data Repository (IDR) CMS accesses this data for risk adjustment calculations and data analyses 16

9 Why Is This Important? 17 Finding Discrepancies? Payer provides risk scores but different from internal analytics You receive a list of open or suspected HCCs but can t validate them through medical record reviews You reach out to providers with volumes of HCCs to capture and realize the list contains false positives 18

10 vs. Encounter Data Characteristics data Encounter data Number of data elements data elements data elements Types of data elements Diagnoses Diagnoses, procedures, items provided to enrollees and costs Maximum number of diagnoses May include up to 10 diagnosis groupings Up to 12 diagnoses for professional services Up to 25 diagnoses for institutional services Process for identifying diagnoses for Identified and submitted by MA Identified by CMS, which requires MA organizations to risk adjustment purposes submit all encounters regardless of whether they contain diagnoses used for risk adjustment Types of providers submitting data Frequency of data submission Collected from physicians and hospital inpatient and outpatient facilities Submitted at least quarterly by MA organizations Source: GAO summary of Centers for Medicare & Medicaid Services Information. GAO Collected from physicians, hospital inpatient facilities, hospital outpatient facilities, ambulance providers, clinical laboratories, durable medical equipment suppliers, home health providers, mental health providers, rehabilitation facilities and skilled nursing facilities Submitted every week, every other week or every month by MA organizations, depending on their number of enrollees 19 What s the Impact of the Variances? Study conducted in 2017 with eight Medicare Advantage payer accounting for approx. 1 million beneficiaries to compare difference in scores and HCC capture based on methodologies Prevalence rate for top 10 HCCs 11.5% in % in 2015 % of HCCs per patient 28.2% with 0 HCCS 25.3% with 1 HCC 15.5% with 2 HCCs 29.0% with 3 or more HCCs Prevalence rate for top 10 HCCs 6.9% in % in 2015 % of HCCs per patient 39.3% with 0 HCCS 24.7% with 1 HCC 15.3% with 2 HCCs 20.7.% with 3 or more HCCs to Collaboration: A Data Driven Analysis; National Medicare Advantage Summit; April

11 Inputs and Edits Providers Submit Data MAO Submit Data CMS EDFES Edits CMS EDPS Edits & Format Data CMS IDR Stores Data Minimum set of required data elements, not every FFS claim field Rendering provider NPI vs. billing provider NPI HCC capture is limited to eligible providers Qualifying visit type based on HCPCS Ability to resubmit claims could lead to duplicated services 21 Why Does This Matter? Impacts HCC CDI program design and development Must be face to face visit HCPCS filter edits for this Must be eligible provider type Rendering provider NPI 22

12 Eligible Provider Types CSSC Operations Acceptable Physician Types 23 Why Does This Matter? Impacts HCC CDI program design and development Must be face to face visit HCPCS filter edits for this Must be eligible provider type Rendering provider NPI Actionable data & information support program development and evolution Helps organization stay compliant with documentation, coding, and billing practices 24

13 Polling Question #3 What is the focus of your current ambulatory CDI program? 1. HCCs 2. E/M 3. Combination of HCCs and E/M 4. Emergency department 5. Other 25 Designing & Implementing Your Program 26

14 Starts With Data Determine what to analyze based on your organization s priorities and data availability Understand the data What is the source? What has been filtered? Organize the data into actionable information Use the data to drive decisions on priorities and next steps 27 Ends & Evolves With Data Back to the analysis! Analyze areas with opportunity and adjust plans based on data Data will drive the next steps in program evolution 28

15 Monitoring for HCC Opportunity Trending by provider and/or by practice can help prioritize education efforts and provides friendly competition for organization Sum of Open HCC wt. by Provider Opportunities by Physician Provider 1 Provider 2 Provider 3 Provider 4 Provider 5 Provider 6 Provider 7 Provider 8 Provider 9 Provider 10 Provider Yr 1 Q1 Yr 1 Q2 29 Organizational Impact of HCCs Quality Dept. Contracting Dept. Finance Dept. Revenue Cycle ACO Physician Group HIM Compliance Documentation Integrity is at the core of success for all these departments Image Source: management/why do silos form and how can we knock them down HCCs are important for the following programs: Medicare Advantage plans CPC+ programs ACOs Quality Payment Program (QPP) Medicare Spending per Beneficiary measures 30

16 In Summary Understand the source of your data Realize that processes impact your data Understand the inputs, analytics logic, and outputs Use the information to drive decisions but only after understanding the data and information! 31 References Barton, D. and Court, D. Making Advanced Analytics Work for You. Harvard Business Review, October 2012, Volume 90, Number 10, pp advanced analytics work for you Medicare Advantage Rates & Statistics; Announcements Plans/MedicareAdvtgSpecRateStats/Announcements and Documents.html?DLSort=2&DLEntries=10&DLPage=1&DLSortDir=descending. Murrin, S. Medicare Advantage Encounter Data Show Promise for Program Oversight, But Improvements Are Needed. DHHS Office of Inspector General (OEI ), January asp Palmetto GBA. Medicare Advantage & Part D Communications Handbook. August pdf/$FIle/Medicare%20Advantage%20Communications%20Handbook% pdf Risk Adjustment for & User Group. April 19, Data%20and%20%20Data~User%20Group~AZJ8PF0127?open&navmenu=Medicare^Advantage^Encounter^Data^and^RAP S^Data Risk Adjustment for & User Group. May 17, Data%20and%20%20Data~User%20Group~AZJ8TX8643?open&navmenu=Medicare^Advantage^Encounter^Data^and^RAP S^Data Swadi, A. to Collaboration: A Data Driven Analysis. National Medicare Advantage Summit. April 6, The Henry J. Kaiser Family Foundation. Medicare Advantage Fact Sheet. October advantage/ United States Government Accountability Office. Medicare Advantage: Limited Progress Made to Validate Encounter Data Used to Ensure Proper Payments. GAO , January

17 Thank you. Questions? Sonia Trepina Brett Senor 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. 33