Differential Impact of Hospital and Community Factors on Medicare Readmission Penalties

Monica S. Aswani, Meredith L. Kilgore, David J. Becker, David T. Redden, Bisakha Sen, Justin Blackburn

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Objective: To identify hospital/county characteristics and sources of regional heterogeneity associated with readmission penalties. Data Sources/Study Setting: Acute care hospitals under the Hospital Readmissions Reduction Program from fiscal years 2013 to 2018 were linked to data from the Annual Hospital Association, Centers for Medicare and Medicaid Services, Medicare claims, Hospital Compare, Nursing Home Compare, Area Resource File, Health Inequity Project, and Long-term Care Focus. The final sample contained 3,156 hospitals in 1,504 counties. Data Collection/Extraction Methods: Data sources were combined using Medicare hospital identifiers or Federal Information Processing Standard codes. Study Design: A two-level hierarchical model with correlated random effects, also known as the Mundlak correction, was employed with hospitals nested within counties. Principal Findings: Over a third of the variation in readmission penalties was attributed to the county level. Patient sociodemographics and the surrounding access to and quality of care were significantly associated with penalties. Hospital measures of Medicare volume, percentage dual-eligible and Black patients, and patient experience were correlated with unobserved area-level factors that also impact penalties. Conclusions: As the readmission risk adjustment does not include any community-level characteristics or geographic controls, the resulting endogeneity bias has the potential to disparately penalize certain hospitals.

Original languageEnglish (US)
JournalHealth Services Research
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Medicare
Information Storage and Retrieval
Risk Adjustment
County Hospitals
Centers for Medicare and Medicaid Services (U.S.)
Patient Readmission
Quality of Health Care
Health Resources
Long-Term Care
Nursing Homes
Automatic Data Processing

Keywords

  • Hospital Readmissions Reduction Program
  • Medicare

ASJC Scopus subject areas

  • Health Policy

Cite this

Differential Impact of Hospital and Community Factors on Medicare Readmission Penalties. / Aswani, Monica S.; Kilgore, Meredith L.; Becker, David J.; Redden, David T.; Sen, Bisakha; Blackburn, Justin.

In: Health Services Research, 01.01.2018.

Research output: Contribution to journalArticle

Aswani, Monica S. ; Kilgore, Meredith L. ; Becker, David J. ; Redden, David T. ; Sen, Bisakha ; Blackburn, Justin. / Differential Impact of Hospital and Community Factors on Medicare Readmission Penalties. In: Health Services Research. 2018.
@article{8f956c56f8434fe186069d9dccdf3b97,
title = "Differential Impact of Hospital and Community Factors on Medicare Readmission Penalties",
abstract = "Objective: To identify hospital/county characteristics and sources of regional heterogeneity associated with readmission penalties. Data Sources/Study Setting: Acute care hospitals under the Hospital Readmissions Reduction Program from fiscal years 2013 to 2018 were linked to data from the Annual Hospital Association, Centers for Medicare and Medicaid Services, Medicare claims, Hospital Compare, Nursing Home Compare, Area Resource File, Health Inequity Project, and Long-term Care Focus. The final sample contained 3,156 hospitals in 1,504 counties. Data Collection/Extraction Methods: Data sources were combined using Medicare hospital identifiers or Federal Information Processing Standard codes. Study Design: A two-level hierarchical model with correlated random effects, also known as the Mundlak correction, was employed with hospitals nested within counties. Principal Findings: Over a third of the variation in readmission penalties was attributed to the county level. Patient sociodemographics and the surrounding access to and quality of care were significantly associated with penalties. Hospital measures of Medicare volume, percentage dual-eligible and Black patients, and patient experience were correlated with unobserved area-level factors that also impact penalties. Conclusions: As the readmission risk adjustment does not include any community-level characteristics or geographic controls, the resulting endogeneity bias has the potential to disparately penalize certain hospitals.",
keywords = "Hospital Readmissions Reduction Program, Medicare",
author = "Aswani, {Monica S.} and Kilgore, {Meredith L.} and Becker, {David J.} and Redden, {David T.} and Bisakha Sen and Justin Blackburn",
year = "2018",
month = "1",
day = "1",
doi = "10.1111/1475-6773.13030",
language = "English (US)",
journal = "Health Services Research",
issn = "0017-9124",
publisher = "Wiley-Blackwell",

}

TY - JOUR

T1 - Differential Impact of Hospital and Community Factors on Medicare Readmission Penalties

AU - Aswani, Monica S.

AU - Kilgore, Meredith L.

AU - Becker, David J.

AU - Redden, David T.

AU - Sen, Bisakha

AU - Blackburn, Justin

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Objective: To identify hospital/county characteristics and sources of regional heterogeneity associated with readmission penalties. Data Sources/Study Setting: Acute care hospitals under the Hospital Readmissions Reduction Program from fiscal years 2013 to 2018 were linked to data from the Annual Hospital Association, Centers for Medicare and Medicaid Services, Medicare claims, Hospital Compare, Nursing Home Compare, Area Resource File, Health Inequity Project, and Long-term Care Focus. The final sample contained 3,156 hospitals in 1,504 counties. Data Collection/Extraction Methods: Data sources were combined using Medicare hospital identifiers or Federal Information Processing Standard codes. Study Design: A two-level hierarchical model with correlated random effects, also known as the Mundlak correction, was employed with hospitals nested within counties. Principal Findings: Over a third of the variation in readmission penalties was attributed to the county level. Patient sociodemographics and the surrounding access to and quality of care were significantly associated with penalties. Hospital measures of Medicare volume, percentage dual-eligible and Black patients, and patient experience were correlated with unobserved area-level factors that also impact penalties. Conclusions: As the readmission risk adjustment does not include any community-level characteristics or geographic controls, the resulting endogeneity bias has the potential to disparately penalize certain hospitals.

AB - Objective: To identify hospital/county characteristics and sources of regional heterogeneity associated with readmission penalties. Data Sources/Study Setting: Acute care hospitals under the Hospital Readmissions Reduction Program from fiscal years 2013 to 2018 were linked to data from the Annual Hospital Association, Centers for Medicare and Medicaid Services, Medicare claims, Hospital Compare, Nursing Home Compare, Area Resource File, Health Inequity Project, and Long-term Care Focus. The final sample contained 3,156 hospitals in 1,504 counties. Data Collection/Extraction Methods: Data sources were combined using Medicare hospital identifiers or Federal Information Processing Standard codes. Study Design: A two-level hierarchical model with correlated random effects, also known as the Mundlak correction, was employed with hospitals nested within counties. Principal Findings: Over a third of the variation in readmission penalties was attributed to the county level. Patient sociodemographics and the surrounding access to and quality of care were significantly associated with penalties. Hospital measures of Medicare volume, percentage dual-eligible and Black patients, and patient experience were correlated with unobserved area-level factors that also impact penalties. Conclusions: As the readmission risk adjustment does not include any community-level characteristics or geographic controls, the resulting endogeneity bias has the potential to disparately penalize certain hospitals.

KW - Hospital Readmissions Reduction Program

KW - Medicare

UR - http://www.scopus.com/inward/record.url?scp=85052790103&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85052790103&partnerID=8YFLogxK

U2 - 10.1111/1475-6773.13030

DO - 10.1111/1475-6773.13030

M3 - Article

C2 - 30151882

AN - SCOPUS:85052790103

JO - Health Services Research

JF - Health Services Research

SN - 0017-9124

ER -