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Who MOPPS Your Hospital?(Measuring Outpatient Prospective Payment Systems)
Andrei M. Costantino, MHA, CFE, CHCDirector, Organizational Integrity & Audit ServicesAmy M. Gendron, RHIT, CCSManager, Organizational Integrity
Health Care Compliance AssociationApril 29, 2012Las Vegas, NV
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Agenda / Overview• Overview of Trinity Health
• Current Regulatory Environment
• Data Resources for Benchmarking
• Techniques Used to Audit and Monitor– Outpatient Services Benchmarking– Outpatient Services Monitoring
• OPPS Scorecard
• Sampling Approach
• Reporting
• Current Issues
• Questions and Answers
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3Copyright 2011 Trinity Health – Novi, Michigan 3
• One of the largest Catholic health systems in the United States (based on Operating Revenue)
• 53,400 full-time equivalent employees
• More than 9,000 active staff physicians(over 2,000 employed)
• 20 Ministry Organizations, encompassing 47 hospitals 35 owned, 12 managed
• 401 outpatient centers
• Revenues of $8.5 billion
• Over $455 million in Community Benefit Ministry
Trinity Health: Unified Enterprise Ministry
Serving Ten States Nationwide
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Who’s Who in Health Care Enforcement
• Recovery Audit Contractors (RACs) Medicare and Medicaid
• Medicaid Integrity Contractors (MICs)
• Medicare Administrative Contractors (MACs)– Replacing Fiscal Intermediaries and Carriers– Responsible for both Part A and Part B claims– Accountable by CMS for reducing payment errors to providers
on front-end
• Zone Program Integrity Contractors (ZPICs)– Data mining and analytics
• Health Care Fraud Prevention and Enforcement Action Team (“HEAT”)
• Medicare Fraud Strike Teams
• HHS - Office of Inspector General (OIG)– Hospital Audits
• Department of Justice (DOJ)
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Oversight by Compliance and Legal as Records are Submitted
RISK
OV
ER
SIG
HT
CERT
QIO
FI/Carrier/MACProbes
MIC
RAC
Z-PIC/PSC
OIG
DOJ
Legal OversightLegal Oversight
Compliance OversightCompliance Oversight
Routine BusinessRoutine Business
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Predictive Modeling of Claims Data• September 2010, as part of the Small Business Jobs Act, Congress
mandated that HHS use “predictive modeling techniques” to identify and prevent fraud, waste and abuse in Medicare.
• By January 1, 2014 the program will include all states, and by April 1, 2015, the program must be expanded to apply to Medicaid and CHIP.
• Through data analytics, CMS looks at provider billing or beneficiary utilization patterns or provider networks that represent a high risk of fraud.
• Predictive modeling technologies analyze large data sets for suspicious patterns, anomalies or other factors that may be linked to fraud, waste or abuse.
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Brown Dog Analogy
Brown / GovernmentShiny Objects / Provider Services
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Benchmarking – Hospital Data
• Use of Benchmark Data
– Analysis of hospital outpatient data
– Establish goals/targets
– Prioritize outpatient services for auditing and monitoring
– Make your case for additional resources
– Develop audit plans
– Identify Outliers / Target risk areas
– Develop compliance scoring system
– Acquisition Due Diligence
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Data Resource for Benchmarking
• CMS produces an OPPS limited data set file on yearly basis.
• Raw data file containing bill type, revenue codes, HCPCS, charges, units, modifiers etc.
• File on average includes more than 50 – 60 million claims
• Third party vendors
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What To Do With It
• Develop Hospital Snapshot that includes the following:– E/M Coding Distribution– Modifier -25 appended to an E/M service, identifies the
service as significant and separately identifiable from a procedure on the same date of the service
– Modifier -59 under certain circumstances, the hospital may need to indicate that a procedure or service was distinct or independent from other services performed on the same day
• Analyze data to develop risk and audit strategies
• Use data to develop a hospital scorecard
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Modifier -25 Distribution
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Modifier -25 Example
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Modifier -59 Monitor
• Trend the use of modifier -59 across each facility
• Running monthly average
• Identifies top 10 codes reported with -59 appended
• Contact to individual facility when spike occurs
• Annual summary report
• Can dive deeper into data to identify specific code sets when data indicates anomaly
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Sample: Modifier -59 Report
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OIG Inspired Monitors
• Medicare Compliance Investigations of South Shore, Norwood, Kendall etc.
– Inpatient and Outpatient reimbursement greater than charges
– Inpatient Payments greater than $150,000
– Outpatient Payments greater than $25,000
– Outpatient Surgery Units greater than 1
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Examples of OIG Inspired Monitoring Reports
IP Payment > $150K
IP or OP Payment > $1K over charges
OP Payment > $25K
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OP Surgery Units of Service > 1
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Benchmark - Reporting
• Summary of Benchmarking Analyses:
– E/M coding Distribution
– Modifier -25 Utilization
– Modifier -59 Utilization
• Recommended Actions– Discussion with providers
– Medical record documentation coding review
– Validate modifier usage
– Follow-up
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Disclaimer
• Disclaimer is very important:
– The analyses are for benchmarking purposes only and to assist in prioritizing areas for further review by hospital management
– Coding and billing is dependent upon the services rendered by the hospital as determined to be medically necessary and appropriate based on the patient’s presenting medical condition
– No conclusions regarding the accuracy of coding and billing, nor compliance with government and third-party payer rules and regulations can be made without further review of the provider’s underlying medical records documentation.
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Outpatient Services Compliance Scorecard
• “At-a-Glance” Compliance with OPPS– Procedural and diagnosis coding accuracy
– APC assignment
– charge capture issues
• Focus education, mitigation and monitoring resources
• Measures effectiveness of process improvement activities over time
• Ability to compare performance across Trinity Health hospitals.
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What is Measured on the Scorecard?
• Four specific areas1. Net Reimbursement Accuracy Rate
2. Line Item Accuracy Rate
3. HIM APC Accuracy Rate
4. Diagnosis Accuracy Rate
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Using Internal Data to Define Scope
• Identify highest reimbursement; highest volume services within the organization– Sort and analyze data to determine top 5 departments in facility
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Analyzing Internal Data
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Category I: Net Reimbursement Accuracy
• Net Reimbursement Accuracy• Direct impact on reimbursement received by the
facility
• APC assignment
• Medical necessity
• Condition code or value code reporting
• Other OPPS coding requirements • Modifier assignment
• Composite Payments Calculations
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Net Reimbursement Accuracy Example• Please see Handout #1
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Category II: Line Item Accuracy Rate
• Line Item Accuracy Rate– Hard coded and soft coded items
– Includes packaged services
– Value Code/Condition Codes
– Report sorts by revenue code categories
– Examples of errors noted• Charged not documented
• Documented not charged
• Incorrect date of service
• Evaluation and Management service over or under coded
• Incorrect use/application of modifier
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Line Item Accuracy Rate Example
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Category III: HIM APC Accuracy Rate
• HIM APC Accuracy Rate
• Only the “soft coded” procedures that are the responsibility of the HIM coding department.– Correct CPT/HCPCS codes assigned
– APC assignment
– Modifier assignment
– Units of service
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HIM APC Accuracy Rate Example
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Category IV: Diagnosis Accuracy Rate
• Diagnosis Accuracy Rate – evaluation of the overall quality of the diagnostic coding performed based upon correct primary and secondary diagnoses reported.
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Outpatient Services Scorecard
The Net Reimbursement Accuracy Rate is weighted at 40% of the total score, the line item accuracy is weighted at 30%, the HIM APC Accuracy Rate is weighted at 20% and the HIM Diagnosis Accuracy Rate is at 10% for a total of 100%.
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Scoring
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Old Scoring & Lessons Learned
10 points = Excellent score with 97.2% accuracy
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Sampling…………
• Prospective vs. Retrospective audit
• Random vs. Judgmental sample
• Risk Assessment– Focus on Government payers– OIG Work Plan– Scope data driven by High Volume/High reimbursement/High Risk– Issues identified by Ministry Organization – Noted findings at other Organizations– Previous audit findings– Usually a few services account for 70% - 80% of charges– Goal is to review services that make up 60% to 80% of charges
• Five records per department; 25 – 30 records each review
• Not all departments will be reviewed
• Cycle review vs. Yearly follow-up
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Putting it All Together
• Narrative Section of the report– Objective and Scope– Executive Summary
• Scorecard data & analysis• High level findings impacting scorecard• Conclusion and Instructions
– Detailed Report of Findings• Details scorecard with figures by department• Issues Discovered (See Handout #2)
– Cases Impacted– Corrective Actions– Target and Completion Dates of Actions– Responsible Party
• Detailed Case by Case Line Items Reviewed• Exception Summary
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Current Issues
• Injection and Infusion Services– Complex CMS Reporting Instructions
– Documenting Drug Waste
• Evaluation and Management Assignment– Various methodologies for assignment
• Making strides to standardize
– Physician/facility differences
• Wound Care Services– Complex coding guidelines/Multiple LCD’s
• Inpatient/Outpatient Condition Code 44
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Reality
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Questions/Discussion
• Thank-You for Your Attendance and Participation!
• Follow-up questions can be directed to:
Andrei M. Costantino, MHA, CFE, CHC, CPC-H, CPCDirector, Organizational Integrity
Trinity Health(248) 324-8479
Amy M. Gendron, RHIT, CCSManager, Organizational Integrity
Trinity Health(248) 324-8351
