Evidence map›Paper›PMID 31984494›Full record

ArticleHealth services research2020

Is mortality readmissions bias a concern for readmission rates under the Hospital Readmissions Reduction Program?

Irene Papanicolas, E John Orav, Ashish K Jha

Abstract read
In one paragraph

Article in Health services research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Hospital readmission disparity measure for evaluating hospital performance and penalties.Archives of public health = Archives belges de sante publique · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Irene PapanicolasDepartment of Health Policy, London School of Economics and Political Science, London, UK.ORCID 0000-0002-8000-3185
E John OravDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachussets.
Ashish K JhaDepartment of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, Massachussets.ORCID 0000-0002-6602-6444

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo determine whether the exclusion of patients who die from adjusted 30-day readmission rates influences readmission rate measures and penalties under the Hospital Readmission Reduction Program (HRRP). DATA SOURCES/STUDY

setting100% Medicare fee-for-service claims over the period July 1, 2012, until June 30, 2015. STUDY

designWe examine the 30-day readmission risk across the three conditions targeted by the HRRP: acute myocardial infarction (AMI), congestive heart failure (CHF), and pneumonia. Using logistic regression, we estimate the readmission risk for three samples of patients: those who survived the 30-day period after their index admission, those who died over the 30-day period, and all patients who were admitted to see how they differ. DATA COLLECTION/EXTRACTION

methodsWe identified and extracted data for Medicare fee-for-service beneficiaries admitted with primary diagnoses of AMI (N = 497 931), CHF (N = 1 047 552), and pneumonia (N = 850 552).

resultsThe estimated hospital readmission rates for the survived and nonsurvived patients differed by 5%-8%, on average. Incorporating these estimates into overall readmission risk for all admitted patients changes the likely penalty status for 9% of hospitals. However, this change is randomly distributed across hospitals and is not concentrated amongst any one type of hospital.

conclusionsNot accounting for variations in mortality may result in inappropriate penalties for some hospitals. However, the effect of this bias is low due to low mortality rates amongst incentivized conditions and appears to be randomly distributed across hospital types.

Indexed as

BiasMortalityAgedAged, 80 and overFemaleHeart FailureHumansMaleMedicareMyocardial InfarctionPatient ReadmissionPneumoniaReimbursement, IncentiveUnited Stateshospitalsmortalitypay-for-performancequalityreadmissions

Identifiers

PMID31984494
PMCPMC7080391

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.