Reliability of the American Community Survey Estimates of Risk-Adjusted Readmission Rankings for Hospitals Before and After Peer Group Stratification

Nathaniel Bell,John M Brooks,Ana Lòpez-De Fede,Bo Cai

doi:10.1001/jamanetworkopen.2019.12727

Abstract

Since the transition to the American Community Survey, data uncertainty has complicated its use for policy making and research, despite the ongoing need to identify disparities in health care outcomes. The US Centers for Medicare & Medicaid Services' new, stratified payment adjustment method for its Hospital Readmissions Reduction Program may be able to reduce the reliance on data linkages to socioeconomic survey estimates. To determine whether there are differences in the reliability of socioeconomically risk-adjusted hospital readmission rates among hospitals that serve a disproportionate share of low-income populations after stratifying hospitals into peer group-based classification groups. This cross-sectional study uses data from the 2014 New York State Health Cost and Utilization Project State Inpatient Database for 96 278 hospital admissions for acute myocardial infarction, pneumonia, and congestive heart failure. The analysis included patients aged 18 years and older who were not transferred to another hospital, who were discharged alive, who did not leave the hospital against medical advice, and who were discharged before December 2014. The main outcomes were 30-day hospital readmissions after acute myocardial infarction, pneumonia, and congestive heart failure assessed using hierarchical logistic regression. The mean (SD) age of the patients was 69.6 (16.0) years for the safety-net hospitals and 74.9 (14.7) years for the non-safety-net hospitals; 9382 (48.8%) and 7003 (48.5%) patients, respectively, were female. For safety net designations, 20% (3 of 15) of all evaluations concealed and distorted differences in risk, with factors such as poverty failing to identify similar risk of acute myocardial infarction readmission until unreliable estimates were excluded from the analysis (OR, 1.23 [95% CI, 1.00-1.52], P = .02; vs OR, 1.17 [95% CI, 0.94-1.46], P = .15). By comparison, 2 of the 60 models (3%) for the peer group-based classification altered the association between socioeconomic status and readmission risk, concealing similarities in congestive heart failure readmission when adjusted using high school completion rates (OR, 1.27 [95% CI 1.02-1.58], P = .04; vs OR, 1.23 [95% CI, 0.98-1.53], P = .06) and distorting similarities in pneumonia readmissions when accounting for the proportion of lone-parent families (OR, 1.27 [95% CI, 0.98-1.66], P = .07; vs OR, 1.35 [95% CI, 1.02-1.80], P = .04) between the lowest and highest socioeconomic status hospitals in quartile 1. There was greater precision in socioeconomic adjusted readmission estimates when hospitals were stratified into the new payment adjustment criteria compared with safety net designations. A contributing factor for improved reliability of American Community Survey estimates under the new payment criteria was the merging of patients from low-income neighborhoods with greater homogeneity in survey estimates into groupings similar to those for higher-income patients, whose neighborhoods often exhibit greater estimate variability. Additional efforts are needed to explore the effect of measurement error on American Community Survey-adjusted readmissions using the new peer group-based classification methods.

Highlights

IntroductionAdhering to the Centers for Medicare & Medicaid Services (CMS) Hospital Readmissions Reduction Program (HRRP) performance and accountability metrics presents a profound and ongoing challenge for many safety-net hospitals (SNHs).[1,2,3] Because these hospitals care for a disproportionate number of socially and economically vulnerable patients, their readmission rates are often higher than those of non-SNHs, driven by challenges brought on by poverty, low health literacy, poor housing conditions, and a lack of social support and access to care.[4,5,6,7,8] These conditions often coincide with the primary reasons most patients cite as contributing to relapse and readmission.[9]
20% (3 of 15) of all evaluations concealed and distorted differences in risk, with factors such as poverty failing to identify similar risk of acute myocardial infarction readmission until unreliable estimates were excluded from the analysis (OR, 1.23 [95% CI, 1.00-1.52], P = .02; vs odds ratio (OR), 1.17 [95% CI, 0.94-1.46], P = .15)
2 of the 60 models (3%) for the peer group–based classification altered the association between socioeconomic status and readmission risk, concealing similarities in congestive heart failure readmission when adjusted using high school completion rates (OR, 1.27 [95% CI 1.02-1.58], P = .04; vs OR, 1.23 [95% CI, 0.98-1.53], P = .06) and distorting similarities in pneumonia readmissions when accounting for the proportion of lone-parent families (OR, 1.27 [95% CI, 0.98-1.66], P = .07; vs OR, 1.35 [95% CI, 1.02-1.80], P = .04) between the lowest and highest socioeconomic status hospitals in quartile 1

Summary

Introduction

Adhering to the Centers for Medicare & Medicaid Services (CMS) Hospital Readmissions Reduction Program (HRRP) performance and accountability metrics presents a profound and ongoing challenge for many safety-net hospitals (SNHs).[1,2,3] Because these hospitals care for a disproportionate number of socially and economically vulnerable patients, their readmission rates are often higher than those of non-SNHs, driven by challenges brought on by poverty, low health literacy, poor housing conditions, and a lack of social support and access to care.[4,5,6,7,8] These conditions often coincide with the primary reasons most patients cite as contributing to relapse and readmission.[9]. In an attempt to address this concern, CMS recently (fiscal year 2019) introduced a new peer group–based payment adjustment method into the HRRP to account for differences in readmission risk attributed to differences in patient socioeconomic case mix.[11] Because hospitals lack individuallevel data on patient socioeconomic case mix, CMS chose to classify institutions according to their proportion of fee-for-service Medicare and Medicare Advanced hospitalizations, for which the patient is eligible for both Medicare and Medicaid reimbursement. Initial evaluations of the new payment model suggest that a peer group–based method measured at the hospital level offers some reprieve to SNHs but does not eliminate the cost imbalances associated with the disproportionate burden these facilitates experience because they serve low-income populations.[12]

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