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

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

Readmissions

Many methodologies exist to identify and quantify readmissions 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

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.

3M™ PPR Methodology

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.

Observed PPR Rate

Expected PPR Rate

Observed to Expected Ratio

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

FFS Medicare Part A at the time of the index admission 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 Patients are identified by their principal diagnosis not DRG. CMS has released a set of ICD-9s that define each of the three disease areas. June 2010 release on hospital compare has additional changes, highlight later.

Incomplete Medicare enrollment data Under age 65 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 AMI – exclusions for planned readmissions: exclude readmissions with PCI or CABG that follow and index AMI admission, except those that are not consistent with planned (HF, AMI, unstable angina, arrhythmia, cardiac arrest, etc) AMI – same day discharges MD fixes Admissions that: (1) had a principal diagnosis code indicating psychiatric care (2) occurred within one day of an index discharge; and (3) had a discharge disposition of “65” (Discharged/ Transferred to a psychiatric hospital or psychiatric distinct unit of a hospital) Readmission with a principal diagnosis beginning with “V57” (rehab)

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. Only comorbidities that convey info about the patient at the time of index and 12 months prior and not complications that arise during the course of hospitalization are included. Models do not adjust for admit source/discharge disposition bc these factors are associated with the structure of the health care system not the patiebnts clinical risk factors. Do not adjust for SES bc association between ses and health outcomes can be due in pt to quality of health care. Risk adjusting for ses would imply that hospitals w/ more low SES pts are held to a different standard. HF:

Risk Standardized Readmission Rate (RSRR) 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. Analogous to the observed to expected ratio = but allows for a comparison of a particular hospital’s performance give its case-mix to an average hospital’s performance with the same case mix.

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

Live Tour Readmissions Diagnostic Tool

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

Medicare Value-Based Purchasing

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

General VBP Program Trends Continuously evolving program Program rules established well in advance Increasing program exposure Increasing weight towards Outcomes & Efficiency Measures

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

FFY 2015 VBP Program Overview First Year of Proportional Reweighting Impacts program eligibility

Tracking VBP Performance

PfP Data Collection and Reporting

Maintain Momentum Sample data collection / reporting tool Sample summary workbook

Vice President, DataGen Questions? Gloria Kupferman Vice President, DataGen gkupferm@hanys.org 518-431-7968