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Original Investigation | Health Care Reform

Patient Characteristics and Differences in Hospital Readmission Rates

Michael L. Barnett, MD1,2; John Hsu, MD, MBA, MSCE1,3; J. Michael McWilliams, MD, PhD1,2
[+] Author Affiliations
1Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
2Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
3Mongan Institute for Health Care Policy, Massachusetts General Hospital, Boston
JAMA Intern Med. 2015;175(11):1803-1812. doi:10.1001/jamainternmed.2015.4660.
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Published online

Importance  Medicare penalizes hospitals with higher than expected readmission rates by up to 3% of annual inpatient payments. Expected rates are adjusted only for patients’ age, sex, discharge diagnosis, and recent diagnoses.

Objective  To assess the extent to which a comprehensive set of patient characteristics accounts for differences in hospital readmission rates.

Design, Setting, and Participants  Using survey data from the nationally representative Health and Retirement Study (HRS) and linked Medicare claims for HRS participants enrolled in Medicare who were hospitalized from 2009 to 2012 (n = 8067 admissions), we assessed 29 patient characteristics from survey data and claims as potential predictors of 30-day readmission when added to standard Medicare adjustments of hospital readmission rates. We then compared the distribution of these characteristics between participants admitted to hospitals with higher vs lower hospital-wide readmission rates reported by Medicare. Finally, we estimated differences in the probability of readmission between these groups of participants before vs after adjusting for the additional patient characteristics.

Main Outcomes and Measures  All-cause readmission within 30 days of discharge.

Results  Of the additional 29 patient characteristics assessed, 22 significantly predicted readmission beyond standard adjustments, and 17 of these were distributed differently between hospitals in the highest vs lowest quintiles of publicly reported hospital-wide readmission rates (P ≤ .04 for all comparisons). Almost all of these differences (16 of 17) indicated that participants admitted to hospitals in the highest quintile of readmission rates were more likely to have characteristics that were associated with a higher probability of readmission. The difference in the probability of readmission between participants admitted to hospitals in the highest vs lowest quintile of hospital-wide readmission rates was reduced by 48% from 4.41 percentage points with standard adjustments used by Medicare to 2.29 percentage points after adjustment for all patient characteristics assessed (reduction in difference: −2.12; 95% CI, −3.33 to −0.67; P = .003).

Conclusions and Relevance  Patient characteristics not included in Medicare’s current risk-adjustment methods explained much of the difference in readmission risk between patients admitted to hospitals with higher vs lower readmission rates. Hospitals with high readmission rates may be penalized to a large extent based on the patients they serve.






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