PfP Quality Metrics: Readmissions, Value-Based Purchasing and Beyond

Transcription

1 PfP Quality Metrics: Readmissions, Value-Based Purchasing and Beyond Presented to ASHNHA Alaska Partnership for Patients Advisory Group February 4, 2015 Gloria Kupferman

2 Readmissions Calculation methods Agenda 3M compared to Medicare (CMS) Sample reporting tool Medicare Value-Based Purchasing Maintaining PfP momentum with data collection and reporting

3 Readmissions

4 What is a Readmission? A readmission is a return hospitalization to an acute care hospital that follows a prior admission from an acute care hospital within the specified readmission time interval The time interval can vary depending upon the purpose of the review Many methodologies exist to identify and quantify readmissions

5 Methodologies 3M Potentially Preventable Readmissions Some States Medicaid Penalties CMS Hospital Readmissions Reduction Program Hospital-Level 30-Day Risk-Standardized Readmission Measures for specific conditions AMI, HF, PNEU, COPD, THA/TKA, CABG Readmissions in the BPCI and ACO Initiatives Others developed by QIOs, health departments, etc.

6 3M PPR Methodology

7 3M PPR Methodology Index admissions and readmissions for conditions that are not considered preventable are globally excluded e.g. major or metastatic malignancies, multiple trauma and burns, etc. Some admissions are considered non-events and are considered at risk admissions e.g. same day transfer to an acute care hospital for non-acute care, etc.

8 Observed PPR Rate

9 Expected PPR Rate

10 Observed to Expected Ratio

11 Overview of the Current CMS Methodology All-cause readmissions Current focus areas Heart Failure (HF) patients Heart Attack (AMI) patients Pneumonia (PN) patients Chronic Obstructive Pulmonary Disease (COPD) Total hip and knee replacements (THA/TKA) CABG in FFY 2017 What hospitals are included? All acute care PPS hospitals CAHs are exempt Hospital must have 25 discharges within a disease category over the 3 year reporting period

12 Inclusions Medicare Fee-for-Service patients, at least 65 years of age, with a principal diagnosis of AMI, HF, or PN 12 full months of enrollment in parts A and B FFS prior to the index admission FFS Medicare Part A at the time of the index admission One full month of enrollment in Parts A and B FFS post discharge

13 Exclusions Incomplete Medicare enrollment data Under age 65 Length of stay greater than one year Discharged against medical advice In hospital deaths Transfers out Same day readmissions for the same condition to the same hospital Disease category specific exclusions Some recognition of planned readmissions

14 Risk Adjustment Methodology Developed by a team of clinical and statistical experts from Yale and Harvard universities Each disease category has an individual risk adjustment model Adjust for variables that are clinically relevant and have strong relationships with the outcome Demographics, disease severity indicators, indicators of frailty Example for HF: age, sex, history of CABG, cancer, diabetes, asthma, COPD, pneumonia, renal failure, etc.

15 Risk Standardized Readmission Rate (RSRR) RSRR= Predicted Rate National Expected Rate Unadjusted Rate Predicted Rate (similar to observed rate) the number of readmissions within 30 days predicted on the basis of the hospital's performance with its observed case mix Expected Rate the number of readmissions expected on the basis of the nation s performance (US average hospital performance) with that hospital s case mix.

16 Predicted to Expected Ratio P/E less than 1 = Lower than expected readmission rate Better quality, no penalty P/E greater than 1= Higher than expected readmission rate Lower quality, subject to penalty

17 Live Tour Readmissions Diagnostic Tool 17

18 Takeaways You can t evaluate and address issues without data You need an analytic tool that can identify and track readmissions Let the CMO, Dept. Chairs, Nurse Leads... Play with it Formally analyze Provide feedback Share with MD/RN and other key clinicians Use for focus groups... What goes well and where are the opportunities

19 Medicare Value-Based Purchasing

20 Value-Based Purchasing Overview Mandated by the ACA The only Medicare quality program that actually rewards good performance Funded by Medicare payment carve-outs Complex scoring methodology looks at quality metrics in several domains Scores reflect performance compared to national standards and individual improvement Domains, metrics and standards change annually

21 General VBP Program Trends Continuously evolving program Program rules established well in advance Increasing program exposure Increasing weight towards Outcomes & Efficiency Measures Domain Weight 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 30% 25% 20% 25% 70% 45% 30% 20% 30% 30% 10% 25% 40% 25% 25% 5% 20% 25% Program Contribution Amount 2.00% 1.75% 1.50% 1.25% 1.00% 0.75% 0.50% 0.25% 0.00%

22 FFY 2015 VBP Program Overview 1.5% program contribution Outcomes domain measure expansion PSI-90 Safety Indicator Composite CLABSI Standardized Infection Ratio New Efficiency Domain SPP_1 (Medicare Spending Per Beneficiary) Overlap with FFY 2015 HAC Reduction Program PSI-90 Composite CLABSI 30% 20% Process Domain Patient Experience Domain 30% 20% Patient Outcomes Domain Efficiency Domain

23 FFY 2015 VBP Program Overview First Year of Proportional Reweighting Impacts program eligibility Process Domain Unweighted Domain Score Original Domain Weight Proportionally Reweighted Domain Weight * 63.33% 20.00% 28.57% 29% Process Domain Patient Experience Domain Patient Experience Domain Patient Outcomes Domain 96.00% 30.00% 42.86% Not Eligible 30.00% Not Elgible 43% 29% Patient Outcomes Domain Efficiency Domain 90.00% 20.00% 28.57% Efficiency Domain Hospital Counts Scored on 2 Domains % Scored on 3 Domains % Scored on 4 Domains % Total Number of Insiders* % *Based on 4Q2013 DataGen Estimate

24 Tracking VBP Performance Measure and Domain Score Comparison FFY 2013 Program ACTUAL Performance Hospital FFY 2014 Program ACTUAL Performance Hospital FFY 2015 Program ESTIMATED Performance VBP Measure Score VBP Measure Score Hospital Performance VBP Measure Score Performance Performance Program Eligibility Eligible Eligible Projected to be Eligible AMI-7a N/A N/A N/A N/A N/A N/A AMI-8a N/A N/A 100.0% % 6 HF % % % 6 PN-3b 100.0% % % 10 PN % % % 10 SCIP-Inf % % % 10 Process of Care SCIP-Inf % % % 10 SCIP-Inf % % % 10 SCIP-Inf-4 N/A N/A N/A N/A N/A N/A SCIP-Inf-9 Measure Not Evaluated for VBP % % 6 SCIP-Card % % % 5 SCIP-VTE % % 10 Measure Not Evaluated for VBP 2015 SCIP-VTE % % % 10 Unweighted Domain Score 85.6% 93.6% 83.0% Patient Experience of Care Communication with Nurses % 1 Communication with Doctors % 0 Responsiveness of Hospital Staff % 0 Pain Management % 0 Not Provided By Not Provided By Communication about Medicines CMS 6 CMS % 3 Cleanliness and Quietness of Hospital Environment % 3 Discharge Information % 7 Overall Rating of Hospital % 2 HCAHPS Consistency Score Not Applicable 19 Unweighted Domain Score 51.0% 35.0% 35.0% Patient Outcomes MORT-30-AMI 85.0% 2 N/A N/A MORT-30-HF 85.8% % 0 Domain Not Evaluated MORT-30-PN for VBP % % 0 PSI Measure Not Evaluated for VBP 2014 HAI_1 N/A N/A Unweighted Domain Score 30.0% 0.0% Efficiency SPP_1 Domain Not Evaluated for VBP 2013 Domain Not Evaluated for VBP Unweighted Domain Score 100.0% Reweighting factor 1 TPS and Payment Impact Comparison FFY 2013 ACTUAL Program Performance Unweighted Domain X Domain Weight = FFY 2014 ACTUAL Program Performance Unweighted Domain X Domain Weight = FFY 2015 ESTIMATED Program Performance Unweighted Domain Score Process of Care Domain 85.6% X 70.0% = 59.9% 93.6% X 45.0% = 42.1% 83.0% X 20.0% = Patient Experience of Care Domain 51.0% X 30.0% = 15.3% 35.0% X 30.0% = 10.5% 35.0% X 30.0% = Patient Outcomes Domain 30.0% X 25.0% = 7.5% 0.0% X 30.0% = Not Applicable Efficiency Domain Not Applicable 100.0% X 20.0% = Weighted Score Weighted Score X Domain Weight = Weighted Score 16.6% 10.5% 0.0% 20.0% Total Performance Score (TPS) 75.2% 60.1% 47.1%

25 PfP Data Collection and Reporting

26 Maintain Momentum Sample data collection / reporting tool Sample summary workbook

27 Questions? Gloria Kupferman Vice President, DataGen