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Cloudy with a Chance of Readmissions Penalties Lynn Smith, Clinical Excellence Executive, Midas+ Solutions
Alycia R James, VP Care Performance Transformation Group, Midas+ Solutions
Objectives • Be able to describe the CMS readmission
reduction program penalty calculation • Be able to explain the analytics and insights
available to predict performance and target areas of opportunity for improvement
Readmissions! Readmissions!
Shifting From Volume to Value • Historically
readmissions were a revenue stream
• DRG-based payment caused intense focus on decreasing LOS with no provisions for readmissions
• “Frequent Flyers” common
• Hospitals struggle to make the shift – Not lack of intent/will – Like trying to turn a big ship quickly
• No longer responsible for JUST care within their four walls
• “Out of our control” no longer adequate
*Affordable Care Act (3/20/10) instigates MAJOR paradigm shift
*Section 3052 of Affordable Care Act established the Hospital Readmissions Reduction Program
Multiple TOP Priorities With Bottom-line Impact
• Value-Based Purchasing (VBP) • Hospital Readmissions Reduction Program
(HRRP) • Hospital Acquired Complications Reduction
Program (HACRP)
Payment Adjustment Hierarchy Payment reductions are made in a hierarchical order: 1. Value Based Purchasing 2. Hospital Readmissions
Reduction Program 3. Hospital Acquired
Complications Reduction Program
HOWEVER: • VBP and HRRP payment
adjustments are made independently of each other.
• Each applied to the base operating DRG payment amount.
• HAC adjustments are made after VBP and HRRP
Plethora of Published Data – 906,000 results on Google search
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Excessive Readmission Ratios Values > 1.0 = Financial Penalties
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Your Hospital ERR Other Hospitals
Hospital Readmission Reduction Program Penalties Forecasted to Impact More
Hospitals in Future
• Acute Myocardia Infarction
• Pneumonia
• Heart Failure
• Total Hip and Knee
• COPD
• CABG
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Excess Readmission Ratio’s > 1
in ANY one of the clinical cohorts
results in financial penalties
Excess Readmission Ratio = Predicted /Expected
A Primer on Predicted and Expected
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Predicted FY 2016
Excess Readmission Ratio = Predicted /Expected
=
Your patient’s risk factors for FY 2016 Part A & B Claims
(July 1, 2010 – June 30, 2014) x
Risk Coefficients
(July 1, 2011 – June 30, 2014)
+
Your hospital
provider Intercept
(July 1, 2011 - June 30, 2014)
Expected FY 2016 = +
Average hospital provider intercept for all Section(d) Hospitals in US
(July 1, 2011 – June 30, 2014)
Your patient’s risk factors for FY 2016 Part A & B Claims
(July 1, 2010 – June 30, 2014)
x
Risk Coefficients
(July 1, 2011-June 30, 2014)
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Midas+ Xerox
Hospital Readmission Penalty Forecaster
Hospital Readmission Penalty Forecaster Service explained
• Delivered via presentation with quarterly updates • Generated by Midas+ proprietary methodology • Executive-level analysis insights
– System-level rollups forecasts – Individual hospital view by cohort – Cohort detail – Cohort trend – Non-same hospital readmissions trend
• Cohort detail at patient-level files delivered
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How It Works • Utilizes advanced analytics, machine
learning technology, and clinical executive insight
• Informs you of your anticipated readmission penalties up to two years before your hospital-specific reports
• Help you focus improvement resources most effectively
Midas+ Predictive Analytics Creates a Proactive Response Strategy……
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Risk Factors Risk Coefficients
Midas+ Clients see their results
CMS Hospital Specific Reports
Adjusted Payments
Begin
July 2012 to June 2015
July 2011 to June 2015
October 2016 TODAY! August
2016
Midas+ Hospitals can
prioritize and intervene high risk populations to impact
financial penalties two years before they apply!
FY 17 Risk Factors and Risk Coefficients
calculated from Medicare Part A & B Claims July 1, 2011 – Dec 31, 2013
+ Midas+ Data Jan 1, 2014, to date
+ Midas+ Predictive Analytics
Understanding Your Tipping Point
• Which populations are at greatest risk?
• How many readmissions are too many?
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Readmission Penalty Forecaster Uses Medicare Part A & B Claims Data • Includes risk Factors and risk coefficients
Also includes Midas+ data from January 2014 through latest harvested quarter
RPF measures available to Readmission Penalty Forecaster clients only; delivered as a service including quarterly presentations and executive level insights
Unique Features
• Combines CMS Claims data with YOUR data (DV quarterly harvest) to identify patient level
• Provides visibility and predictive adjustment for “Non-Same” readmissions
• Defines how many readmissions are EXCESS causing penalties
• Calculates Expected Probability of Readmission to each INDEX case
16% 7%
33% 29%
Process • Contract Signed
• Financial Line Item data received
• Your Hospital Model developed/Data Generated by Advanced Analytics
• Data to Care Performance Transformation – Insights
• Presentation of YOUR results via web ex • Follow up with delivery of patient level (by cohort)
files
FY 18 Predictions available – Newest CMS data anticipated in August, 2-4 weeks to forecast
Financial Info Needed for Forecaster • Medicare Fee-for-Service In-Patient Volume
• FFS Part A inpatient Medicare claims as principal payer • May include Medicare Part A FFS as secondary is secondary paid • May include Medicare Part A FFS enrolled in state-buy-in program • Must NOT include Medicare Advantage or HMO
• CASE MIX for Medicare Fee for Service inpatient volume • Relative weights for DRGS that have been adjusted for transfer • Only Medicare populations previously defined
• TOTAL REVENUE for Medicare FFS Inpatient volume • By fiscal year 2012, 2013, 2014
• BASE Operating DRG VALUE for 3 years • DRG Weights x [(labor share x wage index)+(non-labor share x cost of living
adjustment)]+New technology if applicable • DO NOT include adjustments for graduate medical education, disproportionate
share, high-cost outliers or Value-Based Purchasing • Does NOT include adjustments or add-on payments for Medicaid payments to
Disproportionate Share Hospitals (DSH)
System-level Forecast
Individual Hospital View
Cohort Detail
Cohort Trend
Patient-level Files
SAME but Different DataVision Readmission Penalty Forecaster
DATA Hospital’s ADT/DAB All Patients with Medicare as payer
Primary: CMS Claims Secondary: Hospital’s Midas+ data CMS Claims – Medicare as principal/secondary
FACILITY Readmissions ONLY to same facility
Readmissions to same facility with adjustment for “non-same” Identification of “non-same” via Claims data
PRIMARY FOCUS
Patient care management at your facility
Predicting excess readmissions & associated penalties at the cohort & system level
Good Enough Today May Not Be Good Enough Tomorrow
“Even if you’re on the right track, you’ll get run over if you just sit there.”
Will Rogers
I’ve Got the Data – Now What?
• Financial planning (budget) – Reality (What is fluid/what is static?)
• Performance Improvement – Focus on “teaching” cases – Root Causation
• Expected Probability • Readmission to “Non-Same” hospitals • Discharge Disposition
Midas+ Findings • Much variation in Expected Probability of
Readmission by Cohort – Highest doesn’t always translate to most readmissions
• CABG and TH/TK typically highest cost/case
• Being discharged to a SNF or home with Home Health no guarantee
Importance of Documentation • Accurate & complete
documentation of patient’s clinical condition is of utmost importance
• “Not uncommonly, a measured risk-adjusted readmission rate is artificially high either because the conditions defining the cohort and/or the comorbidities defining the severity of the expected readmission rate were not documented by the provider or were not coded by the facility as to be reported, or both…” – https://www.nationalreadmissionp
revention.com/documents/snf-penalties-announced.pdf
LOST in TRANSLATION?
Client Findings - Forecaster
• “Non-same” readmit trends
• The amount of excess readmissions only has to be 1 (in 1 cohort) to initiate penalty
• Post acute care providers importance
• The “EXPECTED” is consistently lower for FY 17 than FY 16 (window tightening) – Above average in FY 16 is not a guarantee for
FY 17 … moving target
Quick Wins • Systems
– Communicate, communicate, communicate – “Non-same” readmissions
• What cohort is “almost” there? Minor issues
• Trends of decreasing Relative Weight/increasing provider intercepts – What Changed? Who Changed?
Long-range Improvement Strategies • Systems
– Transparency – ID Best Practices • Community Collaboration with Post Acute
Care providers • Cohorts with major opportunity
– Process evaluation / root causation – Care Transitions
• Talk to your patients
• There is no “one size fits all” to reduce readmissions
• Hospitals must deploy and support multiple strategies
• IMPORTANT – consistently monitor results • Reliable data is CRITICAL • The time for action is NOW – don’t delay
Summary
Guidance in the Storm • Readmission Penalty Forecaster • Midas+ Care Performance
– Additional Hands on Deck – Impartial Root Causation – Best Practices – Collaboration – DV Data
• Process Control
Thanks for attending. Are there any questions?
Lynn Smith, Clinical Excellence Executive, Midas+ Solutions
Alycia R James, VP Care Performance Transformation Group, Midas+ Solutions