neny hfma annual institute / icr roadshow wednesday, april ... · neny hfma annual institute / icr...
TRANSCRIPT
NENY HFMA Annual Institute / ICR RoadshowWednesday, April 5th, 2017
How Quality and Risk Adjustment is Impacting Hospital and Physician Payments
Kim Charland, Vice President Strategic Initiatives
Pena4, Inc.
Valerie Fernandez, Manager Coding Client Program Development
H.I.M. On Call. Inc.
2017 Pena4 1
Agenda
Healthcare Payment Reform Environment
Risk Adjustment and Hierarchical Condition Categories (HCCs)
Clinical Documentation Improvement (CDI), Coding and Quality Challenges
Best Practices for Moving Forward
2017 Pena4 2
Healthcare Payment Reform Environment
2017 Pena4 3
Healthcare Payment Reform Environment
2017 Presidential Election
Repeal and Replace Obama Care – With What?
Accountable Care Organization (ACO) Reform
Medicaid Reform
Mandatory vs. Elective Participation in Value-Based-Payment Initiatives
Continued Movement to Value-Based-Payment
2017 Pena4 4
Top Issues Confronting Hospitals in 2016
Issue 2016 2015 2014
Reorganization (e.g., mergers, acquisitions, restructuring, partnerships)
7.8 7.4 --
Technology 7.2 7.1 7.3
Population Health Management 6.6 6.3 6.8
Physician-Hospital Relations 5.9 5.7 5.9
Access to Care 5.8 6.2 --
Patient Satisfaction 5.5 5.3 5.9
Personnel Shortages 4.8 5.1 7.4
Patient Safety and Quality 4.6 4.2 4.7
Governmental Mandates 4.2 4.5 4.6
Financial Challenges 2.7 3.2 2.5
Source: American College of Healthcare Executives
2017 Pena4 5
Risk Adjustment and Hierarchical Condition Categories (HCCs)
2017 Pena4 6
What is Risk Adjustment?
An actuarial tool used to predict healthcare costs and adjust payments to healthcare plans to cover expected relative costs for providing coverage to enrollees.
Ensures that health plans have adequate funding to provide care to people who are likely to have high healthcare costs while at the same time preventing overcompensation for healthy patients.
Health plans compete on the basis of quality and service, which are the foundation of value-based payments and healthcare reform.
2017 Pena4 7
Why is Risk Adjustment so Important?
Promotes fair payments to health plans by rewarding efficiency and encouraging the provision of high-quality care for the chronically ill.
For example, risk scores can be used to identify those patients who may benefit from disease management intervention to prevent costly emergency department visits of inpatient admissions.
Risk scores help predict post-discharge costs more effectively than inpatient costs because patients with higher risk scores have a greater number of medical conditions and therefore have significantly higher post-discharge costs.
Risk scores can then be used to design post-discharge care plans to flag those patients for more intense follow-up.
2017 Pena4 8
Who Uses Risk Adjustment?
Payers
Medicare
Medicare Advantage
Medicaid
Managed Care
Commercial Insurance
2017 Pena4 9
Who Uses Risk Adjustment?
CMS Programs Using Risk Adjustment
Inpatient Hospital Programs:
Hospital Value-Based Purchasing Program (HVBP)
Hospital Readmissions Reduction Program (HRRP)
Accountable Care Organizations (ACO)
Medicare Shared Savings Programs (MSSP)
2017 Pena4 10
Who Uses Risk Adjustment?
CMS Programs Using Risk Adjustment
Quality Payment Program (QPP)
Medicare Access and CHIP Reauthorization Act of 2015 (MACRA)
Two reimbursement tracks:
MIPS: payment based on 4 performance categories:
Quality, Resource use, Clinical Practice Improvement, Advancing Care
Advanced alternative payment methods,(APM):
Examples include ACOs, Patient Centered Medical Home
2017 Pena4 11
How Will MACRA Impact the Bottom Line
Merit Based Incentive Payment System,(MIPS)
Move from fee for service to value based purchasing
Two reimbursement tracks:
MIPS: payment based on 4 performance categories:
Quality, Resource use, Clinical Practice Improvement, Advancing Care
Advanced alternative payment methods,(APM):
Examples include ACOs, Patient Centered Medical Home
Program begins in 2017 with potential 4% penalty culminating in a 9% penalty in 2022
2017 Pena4 12
Risk adjustment model initially implemented in 2000 with a phased in
methodology
Calculates risk scores
Adjusts capitated payments made for beneficiaries in Medicare Advantage plans
Diagnosis related, based on 79 hierarchical condition categories (HCCs)
Based on age, sex, disability, living circumstances, i.e. home, nursing home, long term care facility
Medicaid status is also a determinant in the calculation
How Does Risk Adjustment Work?
2017 Pena4 13
How Does Risk Adjustment Work?
Prospective review of health status in a base year to predict costs in the following year
Assessments of Medicaid dual eligible beneficiaries, those eligible for both Medicare and Medicaid, who have a higher cost than Medicare only beneficiaries
In recent years there has been a greater focus on dual eligible beneficiaries
CMS conducts ongoing reviews to determine the accuracy of the expenditure and prospective payment assessments
Predictive analysis is based on the Medicare Fee-for-Service population
2017 Pena4 14
Objective
Compensate health insurance plans, Medicare Part C, Medicare Advantage Plans, for differences in enrollee health mix
It is an important element of value based purchasing
It assesses actual rates and predicted rates to confirm quality of care that includes care planning and coordination of care
It is used to set capitation payments to Managed Care Plans
It is also used in combination with fee for service to compensate Accountable Care Organizations,(ACO) and Medicare Shared Savings Programs,(MSSP)
2017 Pena4 15
Medicare Coverage
47 million beneficiaries
Approximately one fourth or 11,750,000 are enrolled in Medicare Advantage Plans
CMS samples approximately 1 million beneficiaries’ claims to estimate predicted costs
Capitation payments are reduced for low risk beneficiaries and are increased for high risk beneficiaries eliminating the incentive for Medicare Advantage Plans to seek enrollees who are healthier and are in the low risk category
2017 Pena4 16
Formula Used for Calculating Risk
Raw Risk Score = Patient Demographic Score + Health Status
Higher risk scores represent members suffering from a greater set of medical conditions
Lower risk scores represent a healthier population:
Medicare Advantage Adjusted Bid Rate
X
Patient’s Risk Adjustment Factor
=
Medicare Advantage Plan Reimbursement for Member
2017 Pena4 17
Risk Adjustment Factors and Impact to Medicare Advantage Plan Budget
Several HCCs Some HCCs No HCCs
82 y o male
0.597 82 yo Male
0.597 82 yo Male
0.597
MedicaidEligible
0.166 Medicaid Eligible
0.166 Medicaid Eligible
0.166
DM/RenalDisease
0.508 Diabetes 0.162 Not coded NA
RA 0.346 RA 0.346 Not Coded NA
Renal Failure
0.368 Not Coded
NA Not Coded NA
Hemiplegia
0.437 Not Coded NA Not coded NA
DiseaseInteraction
0.102 No Interaction
NA No interaction
NA
Risk Factor
2.524 1.271 0.763
Monthly $2,282 $1,149 $690
Annual $27,382 $13,789 $8,278
2017 Pena4 18
Risk Score Impact based on Documentation
Condition I-10 Dx Code HCC Factor
66 yo male 0.288
DMuncomplicated
E11.9 19 0.118
Neuropathy G62.9 n/a ---
Major Depression
F32.9 n/a ---
Obesity E66.9 n/a ----
BMI 42.5 Z68.41 22 0.365
Great Toe Amputation
Z89.419 189 0.779Risk Score 1.55
2017 Pena4 19
Risk Score Impact based on More Specific Documentation
Condition I-10 Dx Code HCC Factor
66 yo male 0.288
DiabeticNeuropathy
E11.40 18 0.368
CHF I50.9 85 0.368
Major Depression mild
F32.0 58 0.330
Morbid Obesity E66.01 22 0.365
BMI 42.5 Z68.41 22 Included above
Great Toe LT Amputation
Z89.412 189 0.779Risk Score 2.68
2017 Pena4 20
Ten Diagnostic Category Principles
Clinically meaningful: well specified diagnosis to minimize discretionary coding
Predict medical expenditures: diagnosis in the same category should have similar expenditures
Adequate sample size: there must be sufficient information related to the treatment of a diagnosis rather than using a rare diagnosis to calculate expenditures
Clinical profile should categorize individual in to an HCC
Diagnostic classification should encourage specific coding
Coding proliferation i.e. listing of multiple, related diagnosis should not be a determinant of increased expenditure
2017 Pena4 21
Ten Diagnostic Category Principles (Continued)
Providers should not be penalized for recording additional diagnosis
Hierarchy should be consistent and order of assignment should have no impact
The diagnostic classification should categorize all diagnosis codes
Discretionary diagnostic categories should be excluded from the payment models. This prevents a financial impact from coding variation, coding proliferation, gaming and up coding
2017 Pena4 22
Diagnostic Groups,(DXG)
Each diagnosis code maps to one DXG
Each DXG represents a well specified medical condition or set of conditions
Example: Type II Diabetes with Ketoacidosis or Coma
DXGs are aggregated in to condition categories, (CC)
CCs describe a broader set of similar diseases
Example: Diabetes with Acute Complications this includes the DXG for Type II Diabetes with Ketoacidosis or Coma along with Type I and Secondary Diabetes with this manifestation
2017 Pena4 23
Condition Categories,(CC) become Hierarchical Condition Categories,(HCC)
Hierarchies ensure an individual is coded for only the most severe manifestation among related diseases
Example:
Diabetes Hierarchy has three CCs
These are arranged according to severity and cost
Diabetes with Acute Complications
Diabetes with Chronic Complications
Diabetes without Complications
These three CCs are mutually exclusive so an individual can only be placed in one category
2017 Pena4 24
Hierarchical Condition Categories Aggregation of Diagnosis Codes
Diagnosis Codes
Diagnostic Categories,(DXG)
Condition Categories,(CC)
Hierarchical Condition Categories.(HCC)
CMS Hierarchical Condition Categories,(CMS,HCC)
Selection for Payment
Model
Hierarchies Imposed
2017 Pena4 25
Risk Adjusted Payment Models- Federal
CMS-HCCs-Medicare
ICD-10-CM Codes: 9,548 (complete, accurate, consistent)
HCCs: 79 (severity and specificity)
HCC range:1- 189
110 are not used in payment calculations
HHS-HCCs(Non-Medicare)
ICD-10-CM codes: 7,768
HCCs: 127
HCC Range: 1-254
2017 Pena4 26
HCC Conditions
High Cost Medical ( current cancer, heart disease, hip fracture)
Highest Weighted; HIV, Sepsis, Opportunistic infections, Cancer
Acute, Chronic, Status Codes, Etiology and Manifestation
Hip fracture, COPD, status amputation great toe, diabetic neuropathy
Common Conditions, Rare Conditions, Curable Conditions, Incurable Conditions, Congenital and Acquired Conditions
Must be current and require Monitoring, Evaluation, Assessment and Treatment,(MEAT)
2017 Pena4 27
Exclusions from HCC Mapping
Diagnosis are excluded when
They do not predict future cost i.e. appendicitis
There is a high degree of discretion or variability in diagnostic coding or treatment i.e. symptoms without definitive diagnosis
Diagnosis codes from laboratory, radiology and home health claims are not used as they are not reliable and may indicate a rule-out diagnosis
2017 Pena4 28
Example of Patient falling in to Multiple HCCs
Description HCC Weight CumulativeWeight
80 y o incommunity
Demographic 0.543 0.543
Unstable Angina 87 0.258 0.801
COPD 111 0.346 1.147
Primary Malignant Neoplasm Prostate
12 0.154 1.301
2017 Pena4 29
Disease Interactions Impact Payment
The CMS-HCC model recognizes higher costs for comorbidities
Example: 76 y o female with diabetes type II with acute complication and CHF
DM Type II HCC 18 WT 0.368
CHF HCC 80 WT 0.368
Disease Interaction 0.182
Cumulative weight 0.918
Other impacts may relate to age , gender and whether or not the patient is a dual eligible beneficiary living in the community or an institution
If Unrelated conditions are present their payment coefficients are added together Example: diabetes and hip fracture
2017 Pena4 30
Examples of Disease Interactions
Cancer and disorders of immunity
CHF and diabetes
CHF and COPD
CHF and Renal Disorders
CHF and specified heart arrhythmias
COPD, CVD and CAD
DM and CVD
RF and CHF
RF, CHF and DM
2017 Pena4 31
Case Study of Risk Adjustment Factor Impacts
88 y o with angina, peripheral vascular disease, diastolic heart failure:
Risk Score
Age/gender = .683
Angina = .141
PVD = .299
Diastolic HF = .368
Total Score = 1.491
Financial Impact for Subsequent Year 1.491 x $9,276.26 = $13,830.90
2017 Pena4 32
Each Calendar Year Starts a New Risk Factor Calculation Period
Ensure all comorbid conditions are reported annually
Elements of a Risk Factor Calculation
Payment year
Age
Gender
Residing in the community or an institution
Dual Eligibility
Reason for Medicare eligibility i.e. aged or disabled
Disease burden
2017 Pena4 33
Guidelines for Code Assignment
Official Coding Guidelines
Coding Clinic
CMS Risk Adjustment Participant Guide
Mapping tables and rate year risk factors
2017 Pena4 34
Challenges to Accurate Reporting
Documentation that supports each mapped diagnosis
Accurate coding
Timely and comprehensive billing
Risk Adjustment Data Validation Audits are conducted regularly and can trigger identification of improper payments
Extrapolation to total enrollment can occur
False Claim Act violations can result in triple damages
2017 Pena4 35
Capturing CCs and MCCs
Optimize MS DRG assignments and confirm assignment of severity of illness, (SOI) and risk of mortality,(ROM)
42% of HCCs are Complications and Comorbidities,(CCs)
16% of HCCs are Major Complications and Comorbidities,(MCCs)
Ensure you maximize the use of the HCC tables in capturing diagnosis
2017 Pena4 36
Status Codes Can Impact Reimbursement
Dialysis status
Amputation status
Asymptomatic HIV status
Ostomy site
2017 Pena4 37
Top Ten HCC Groups
COPD
CHF
Vascular Disease
Cancer
Ischemic Heart Disease
Specified Heart Arrhythmia
Diabetes
Ischemic or Unspecified Stroke
Angina
Rheumatoid Arthritis and Inflammatory Connective Tissue Disease2017 Pena4 38
Other Common HCCs
Multiple Sclerosis
Parkinson’s Disease
Seizure Disorder
Proliferative Diabetic Retinopathy
HIV
Liver Cirrhosis
Ulcerative Colitis
Paraplegia
Quadriplegia
2017 Pena4 39
Hierarchies
About one third of the HCCs are in hierarchies
For example, Diabetes occurs in the following HCCs 18,19 and 122 based on the type of complication:
HCC 18 chronic diabetic manifestations
HCC 19 due to underlying condition with no complications
HCC 122 Diabetes with diabetic retinopathy
2017 Pena4 40
Example of an Annual Payment Methodology
Risk Factor
No Risk Factor/BasePayment
History of MI
AtrialFibrillation
CHF DM w CKD stage 3
Age $4,000.00 $4,000.00
$4,000.00
$4,000.00 $4,000.00
History MI $2,000.00
$2,000.00
$2,000.00 $2,000.00
Sepsis $7,000.00
$7,000.00 $7,000.00
CHF $4,000.00 $4,000.00
DM w CKDstage 3
$10,000.00
TotalAnnual Assessment
$4,000.00 $6,000.00
$13,000.00
$17,000.00
$27,000.00
2017 Pena4 41
Top 10 Medicare Risk Adjustment Coding Errors
Medical record does not have a legible signature with credentials
EMR was not authenticated i.e. electronically signed
Highest degree of specificity not assigned to diagnosis
Discrepancy between billed diagnosis and actual description of condition in the medical record
Documentation does not indicate condition is being monitored, evaluated, assessed or treated ( MEAT)
2017 Pena4 42
Top 10 Medicare Risk Adjustment Coding Errors (Continued)
Status of cancer is unclear, treatment not documented
Chronic conditions such as hepatitis are not documented as chronic
Lack of specificity i.e. unspecified arrhythmia instead of a specific type of arrhythmia
Chronic conditions or status codes are not documented in the medical record on an annual basis
A link or cause relationship is missing for a diabetic complication or there is a failure to report a mandatory manifestation code
2017 Pena4 43
Risk Adjustment Benefits
Ensures allocation of resources to treat high cost patients
Identifies the need for disease management interventions
Assists in improving quality of care
Emphasizes the importance of accurate documentation and coding
Enables more meaningful data exchange between provider and carrier as well as across institutions
2017 Pena4 44
Website link to Retrieve HCC List
You can use this link to access information on the CMS website about HCCs. Select ICD10 Mappings for a comprehensive list of diagnosis codes and associated HCCs
www.cms.gov/Medicare/Health-Plans/MedicareAdvtgSpecRateStats/Risk-Adjustors.html
2017 Pena4 45
CDI, Coding and Quality Challenges
2017 Pena4 46
Quality Team
Focus today on three key areas:
CDI
HIM
Quality
C-Suite
Medical Staff
Nursing
CDI
HIM
Quality
IT
Finance
2017 Pena4 47
Clinical Documentation Improvement Program
Inpatient Setting
Most familiar with
MS-DRG / APR-DRG focus
MCCs and CCs
Severity of Illness (SOI)
Hospital Acquired Conditions(HACs)
Present on Admission (POAs)
Unspecified diagnoses
Beginning to incorporate ICD-10-PCS (procedures)
More payers being added for review
2017 Pena4 48
Clinical Documentation Improvement Program
Outpatient Setting
New concept
Outpatient departments to include will be identified based on:
Volume of edits
Volume of services
Volume of denials
Usually start and include:
Emergency Department
Infusion / Chemotherapy Services
Observation Services
2017 Pena4 49
Clinical Documentation Improvement Program
Outpatient Setting
Focus on
Diagnosis specificity (HCCs, LCDs and NCDs)
Procedures – HIM coded and CDM generated
Outpatient Code Editor (OCE)
Medical necessity
2017 Pena4 50
Clinical Documentation Improvement Program
Physician Setting
New concept
CDI Specialists should focus ICD-10-CM diagnosis documentation on:
Condition specificity:
Acuity
Severity
Chronic conditions
Relationship (with, due to, caused by secondary)
History of vs. current
HCC Risk Adjustment (may be necessary)
2017 Pena4 51
Clinical Documentation Improvement Program
Physician Setting
Don't forget CPT / HCPCS
Evaluation and Management (E/M)
Procedures
Category II Codes (Physician Performance Measure)
Medical necessity
LCDs and NCDs
2017 Pena4 52
Coding
New ICD-10 coding system
Decrease in coding accuracy (remember coding accuracy rates in ICD-9 after 30+ years)
Decrease in coding productivity
Encoder dependent
Reluctant to query Physicians
Clinical significance
2017 Pena4 53
Quality
“Quality” functions can be scattered among various departments (i.e., quality assurance, internal quality improvement, external quality mandates)
Poorly set up electronic health records (EHRs)
Limitations on quality management systems
2017 Pena4 54
CDI, Coding, and Quality Challenges
No pre-bill reconciliation of the data (ICD-10 codes and DRG)
Conflicts in data
Duplicate or mixed messages to Physicians
No time for continuing assessment and education
Often report to different VPs
Working in silos
Can be territorial
Poor communication
Insufficient staffing levels
2017 Pena4 55
Best Practices Moving Forward
2017 Pena4 56
It’s All About the Data – Questions to Ask Yourself
What does your medical record documentation support?
Are you effectively communicating and building relationships with your Physicians?
Do you have a high functioning CDI Program?
Is your coding department struggling between coding accuracy and productivity?
How is your quality department(s) functioning?
Do you have duplicate or complicated processes?
What are your processes for documenting, querying, coding, collecting, reconciling, and reporting quality data?
2017 Pena4 57
Assessment
Perform an assessment on your current CDIP to ensure that is functioning optimally or create one if you don’t have one
Perform individual coding assessments on each Coding Professional
Assess coding accuracy and productivity expectations
Assess the need for outsourced coding assistance
Perform an assessment on all quality functions and processes
2017 Pena4 58
Data Reconciliation Process
Create a sub-team between CDI, Coding and Quality
Create an internal process for reviewing and reconciling cases when there is documentation / coding differences prior to billing
Use an external resource to assist in reconciling cases when no agreement can be reached internally
Assess all reporting and audit mechanisms to assess for duplication of efforts and conflicting messages
Development of multidisciplinary task force to develop workflow and shared processes with single point reference for providers
Investment in comprehensive data collection and reporting systems
2017 Pena4 59
Financial Impact
Assess for:
Case Mix Index (CMI) vs Quality Payments and Penalties (2-year lag)
Risk Adjustment and HCC financial impact
Payer contract negotiations
Participation in Value-Based-Payment Initiatives such as:
Bundled Payments
Alternative Payment Models
Physician services impact as more health systems and hospitals purchase Physician practices
Cost reduction
2017 Pena4 60
Final Thoughts Accurate and complete clinical documentation impacts:
Code assignment
Severity of Illness (SOI)
Risk Adjustment and HCCs
Patient Safety Indicators (PSI)
Present on Admission (POA)
Hospital Acquired Conditions (HAC)
Core Measures
Outcome measures
Readmissions
Length of Stay (LOS)
Patient Costs
Case Mix Index (CMI)
Quality Payments
And more……
2017 Pena4 61
Final Thoughts
Determine problem data quality issues and develop a focused corrective action plan
Provide continuing education for entire team
Run and share reports with team
Communicate
2017 Pena4 62
Resources
Top Issues Confronting Hospitals in 2016, American College of Healthcare Executives
VBPmonitor, Risk Adjustment and Value-Based Purchasing Together Strengthening Quality of Care, by Angela Carmichael, December 2014.
2017 Pena4 63
Speakers Contact Information:
Kim Charland, BA, RHIT, CCS
Vice President Strategic Initiatives
Pena4
(cell) 610-417-4021
Valerie Fernandez, MBA, CCS, CPC, CIC, CPMA, AHIMA Approved Trainer for ICD-10-CM and PCS
Manager Coding Client Program Development
H.I.M. On Call. [email protected]
(cell) 862-668-4042
2017 Pena4 64
Questions
2017 Pena4 65