Do Hospital Penalties Affect Health Disparities? The Impact of HRRP - PowerPoint PPT Presentation

June 2017 Do Hospital Penalties Affect Health Disparities? The Impact of HRRP on Black Patients and the Hospitals that Serve Them Jose F. Figueroa, MD, MPH Associate Physician, Brigham & Women’s Hospital Instructor of Medicine, Harvard Medical School @joefigs2 Co-authors: Ashish K. Jha, MD, MPH Arnold Epstein, MD, MPH, Jie Zheng, PhD, John Orav, PhD No personal conflict of interests to disclose

Background: Hospital Readmissions  Hospital Readmissions are common, costly, and potentially preventable  Over 1 in 5 Medicare pts readmitted (pre-ACA)  ~24% to 76% potentially preventable  Cost: $17 to $24 billion  Black patients have a 20% higher rate of readmissions than Whites  Care for blacks is highly concentrated (“minority - serving” hospitals)  Top 10% MSHs: ~ 50% of blacks  Top 25% MSHs: ~ 90% of blacks  Historically, MSHs have higher readmission rates for all patients Joynt et al., JAMA, 2011; MedPAC Report, 2007; Jha et al, Health Affairs 2011, Jha et al, JAMA IM, 2007

Hospital Readmissions Reduction Program  Medicare Hospital Penalty Program  Penalty for higher-than-expected readmission rates  Targeted Conditions  FY 2013: AMI, heart failure, pneumonia  FY 2015: COPD, THR/TKR  FY 2017: CABG  Penalty Size  FY 2013: 1%  FY 2015 to present: 3%

Readmission rates are decreasing over time Zuckerman et al, NEJM, 2016

Can hospital penalties worsen health disparities?  MSHs report more barriers yet less likely to use readmission reduction strategies  MSHs are much more likely to be penalized  Increase in financial penalties may limit MSHs ability to invest in quality improvement efforts  Important to understand impact of hospital penalties on minority populations and hospitals that serve them Joynt KJ, et al., JAMA, 2011; Joynt KJ, et al., AJMC, 2016, Figueroa JF, et al., Med Care 2017.

Research questions  Q1. How did the HRRP affect readmission rates of black patients relative to white patients?  Q2. Did the HRRP affect the disparity gap between MSHs vs. non-MSHs?  Q3. If so, did the risk of MSHs receiving a hospital penalty change over time?

Methods  Data:  2007 to 2014 Medicare 100% inpatient file  Hospital characteristics: AHA survey  Penalty data: CMS Hospital Compare  Exclusions:  Hospitals not in 8yrs of period  Critical access hospitals & MD Hospitals  Specialty hospitals (children’s, VA hospitals)  Definition: “Minority - serving” hospital  Top 10% of hospitals with the highest proportion of black Medicare admissions

Statistical Methods  Analysis: Linear spline regression model  Time 1: Pre-ACA/HRRP Q1 2007 to Q1 2010  Time 2: HRRP implementation Q2 2010 to Q2 2012  Time 3: Penalty phase Q3 2012 to Q4 2014  Outcome: 30-day readmission rates (composite AMI, CHF, PN)  Primary Predictors:  Q1: Race (White vs. Black)  Q2: Hospital status (MSH vs. non-MSH)  Covariates:  Age, sex, dual status, comorbidities  Hospital fixed effects

Results

Patient Characteristics of Blacks vs. Whites Patient Characteristics Blacks Whites (2007) (n=83,003) (765,416) Age (mean) 77.1 79.6 Gender Female 59.8% 53.5% Comorbidities Hypertension 63.2% 53.2% Diabetes 31.3% 22.4% COPD 33.2% 39.7% Renal Failure 35.7% 22.1% Obesity 4.7% 2.9% Note: Pattern of patient characteristics was similar across all years in study period (2007 to 2014)

Hospital Characteristics MSH Non-MSH Hospital Characteristics (n=290) (n=2,650) Hospital Size Small 22.5% 29.2% Medium 52.6% 56.5% Large 24.9% 14.3% Teaching Status Major Teaching 21.5% 6.4% Minor Teaching 29.4% 27.9% Non-Teaching 49.1% 65.7% Hospital Region Northeast 13.8% 16.3% Midwest 19.4% 23.5% South 61.2% 39.9% West 5.5% 20.3%

Trends in 30d readmission rates in Blacks v Whites Time 2: Time 3: Time 1: Pre-ACA Implementation Penalty Phase 30% White Blacks: slope, 0.06% per quarter 23.9% 24.5% 25% Black 30d composite readmission rate slope, -0.45% slope, -0.11% 20.3% 22.3% Whites: slope, 0.02% per quarter 20% (AMI, CHF, PN) 19.3% 22.5% 18.4% slope, -0.36% 19.3% slope, -0.10% 15% 10% Difference-in-differences in Trends Difference-in-differences in Trends slope, -0.13% per quarter slope, 0.08% per quarter (p<0.001) (p=0.10) 5% (more reduction in Blacks) 0% 2007 2008 2009 2010 2011 2012 2013 2014

Trends in readmission rates in MSHs vs. non-MSHs Time 1: Time 2: Time 3: Pre-ACA Implementation Penalty Phase 30% MSH MSHs: slope, 0.04% per quarter slope, -0.44% 25% 30d composite readmission rate non-MSH slope, -0.12% (AMI, CHF, PN) 20% Non-MSHs: slope, 0.02% per quarter slope, -0.36% slope, -0.10% 15% 10% Difference-in-differences in Trends Difference-in-differences in Trends slope, -0.10% per quarter slope, 0.06% per quarter (p=0.009) (p=0.18) 5% (more reduction in MSHs) 0% 2007 2008 2009 2010 2011 2012 2013 2014

Did the risk of receiving a readmissions penalty from HRRP change over time for MSHs? Odds Ratio of % MSHs MSH Receiving Penalty* Fiscal Year P-value Penalized (95% CI) (n=290) [non-MSH ref group] 1.5 84.8% 2013 <0.001 (1.3 to 1.8) 1.7 87.3% 2014 <0.001 (1.4 to 2.0) 1.3 90.5% 2015 0.016 (1.1 to 1.6) 1.3 90.5% 2016 0.016 (1.1 to 1.6) 1.4 91.2% 2017 <0.001 (1.2 to 1.7) *Multivariate logistic regression model, adjusting for hospital characteristics

Limitations  Observational study so cannot draw causal inferences between HRRP and changes in readmission rates  Administrative claims data are limited (lack of clinical data)

Discussion/Conclusion  The readmission gap between blacks and whites narrowed after the announcement of HRRP  Penalties did not lead to further reductions in disparity gap  Similarly, MSHs narrowed readmission gap relative to non-MSHs during HRRP implementation period only  Concerns remain since MSHs continue to be more likely penalized than non-MSHs despite experiencing more improvement

Policy Implications  Policymakers should consider changes to HRRP program to reward improvement and not just achievement  21 st century act: Congress mandated HHS to account for social risk factors  Adjustment for dual status

ACKNOWLEDGMENTS • Ashish K. Jha, MD, MPH • Arnold Epstein, MD, MPH • John Orav, PhD • Jie Zheng, PhD • 42 Church St Team at HGHI QUESTIONS? THANK YOU JOSE F. FIGUEROA, MD, MPH jfigueroa@hsph.harvard.edu @joefigs2

Extra Slides/Notes

Formulas to Calculate the Readmission Adjustment Factor Excess readmission ratio = risk-adjusted predicted readmissions/risk-adjusted expected readmissions Aggregate payments for excess readmissions = [sum of base operating DRG payments for AMI x (excess readmission ratio for AMI-1)] + [sum of base operating DRG payments for HF x (excess readmission ratio for HF-1)] + [sum of base operating DRG payments for PN x (excess readmission ratio for PN-1)] + [sum of base operating DRG payments for COPD x (excess readmission ratio for COPD-1)] + [sum of base operating payments for THA/TKA x (excess readmission ratio for THA/TKA -1)] *Note, if a hospital’s excess readmission ratio for a condition is less than/equal to 1, then there are no aggregate payments for excess readmissions for that condition included in this calculation. Aggregate payments for all discharges = sum of base operating DRG payments for all discharges Ratio = 1 - (Aggregate payments for excess readmissions/ Aggregate payments for all discharges) Readmissions Adjustment Factor = the higher of the Ratio or 0.97 (3% reduction). (For FY 2013, the higher of the Ratio or 0.99% (1% reduction), and for FY 2014, the higher of the Ratio or 0.98% (2% reduction).)

Formulas to Compute the Readmission Payment Adjustment Amount Wage-adjusted DRG operating amount * = DRG weight x [(labor share x wage index) + (non-labor share x cola, if applicable)] * Note, If the case is subject to the transfer policy, then this amount includes an applicable payment adjustment for transfers under § 412.4(f). Base Operating DRG Payment Amount = Wage-adjusted DRG operating amount + new technology payment, if applicable. Readmissions Payment Adjustment Amount = [Base operating DRG payment amount x readmissions adjustment factor] - base operating DRG payment amount. * The readmissions adjustment factor is always less than 1.0000, therefore, the readmissions payment adjustment amount will always be a negative amount (i.e., a payment reduction).