Merging ACS NSQIP and Medicare Spend per Beneficiary Data Cleveland Clinic Approach. Jacqueline Matthews, RN, MS Nirav Vakharia, MD Cleveland Clinic

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Merging ACS NSQIP and Medicare Spend per Beneficiary Data Cleveland Clinic Approach Jacqueline Matthews, RN, MS Nirav Vakharia, MD Cleveland Clinic

Guiding Principles: - Use accessible data - Minimize resource investment - Look beyond the discharge - Compare and learn Quality Measures Patient Experience Readmissions Mortality Value = Outcomes Cost? Cost and Reimbursement

National Surgical Quality Improvement Program Clinical Registry Medicare Episode Payment Data Hospitalization + 30 days Impact of Quality on Financial Performance

Medicare Spend per Beneficiary Measure & Data

Medicare Spend Per Beneficiary MSPB evaluates a hospitals efficiency (total spending for an episode of care) Assesses the cost to Medicare of services performed by hospitals and other healthcare providers during an episode An episode is defined as the period immediately prior to, during, and following a patient s hospital stay.

Why is MSPB Important MSPB is the only measure in the Efficiency Domain. Performance on this measure will account for one-quarter of FY 2016 VBP Score

Transparency 1 = Spending is ABOUT THE SAME as the national median >1 = Spending is MORE than the national median < 1 = Spending is LESS than the national median www.hospitalcompare.hhs.gov

Hospital Level Reports Patient Level Episode data - All Medicare Admissions - All post discharge utilization Risk Adjusted and Standardized Actual and Predicted Episode Payment amount

Spending by Claim Types 3 Days Prior Home Health Hospice Outpatient During Index Admission 30 Days After Hospital Discharge Inpatient Skilled Nursing Facility Durable Medical Carrier

MSPB: Key Take Aways Every Hospital has a MSPB measure Reports are available annually to hospitals Publicly Reported annually Included in Value Based Purchasing tying results to dollars Additional patient level reports are provided to hospitals for a deep dive

2011 & 2012 CCHS NSQIP Performance Surgical quality & outcomes n = 3672 Medicare pts 2011 & 2012 Medicare Spend per Beneficiary CMS reimbursement by episode n = 12,328 episodes Merged Dataset n = 1169 matched episodes Impact of Post-Operative Complications on Episode Cost

Sort by NSQIP-defined Complications No. of Complications per Episode (n=1169) No. of Cases 800 600 400 200 # of Complications / Episode Total 0 790 1 266 2 65 3 31 4 9 5 2 6 2 7 1 8 2 Grand Total 1169 0 0 1 2 3 4 5 6 7 8 No. of Complications

Complications & Payment No. of Complications Actual Minus Predicted Episode Pmt 0 -$2,400 1 $640 2 $9,700 3 $16,100 4 $29,660 Post-surgical complications are positively associated with increases in the difference between actual and predicted episode payment. *Note: episodes with 5 or more complications excluded due to insufficient no. of cases

Complications & Payment Post Operative Complication Episode Payment in Excess of Predicted p-value Bleeding with Transfusion (n=268) $3000 <0.0001 Post-operative DVT (n=23) $10000 0.0001 Post-Operative Sepsis (n=34) $12500 <0.0001 Deep Incisional SSI (n=15) $22000 <0.0001

How Complications Affect Episode Cost NO Post Surgical Complications YES Post Surgical Complications Discharge to: Home Inpatient 38% 62%

National Surgical Quality Improvement Program Clinical Registry CC Cost Accounting Data Cost of hospitalization Medicare Episode Payment Data Hospitalization + 30 days Impact of Quality on Financial Performance

Example: DRG 470 (n=306) Major Joint Replacement Hospital Margin Episode Performance 30% decrease NO YES Post-Operative Complications? NO YES Post-Operative Complications?

Our Approach PROS Every US hospital has MSPB data MSPB: predicted episode payment Standardized and risk-adjusted can compare CONS Sampling MSPB exclusions Low no. of matches Hospital cost data difficulty to access

NSQIP : MSPB Merge Summary 1. Data exist and are available for assessing value. 2. Complications correlate with unexpected costs. 3. The cost of harm also happens in post-acute spending, for which hospitals will be responsible. 4. Available datasets allow value comparison across institutions on a level playing field.