Evidence map›Paper›PMID 24845773›Full record

ArticleHealth services research2014

Long-term impact of medicare payment reductions on patient outcomes.

Vivian Y Wu, Yu-Chu Shen

Abstract readComparative Study
In one paragraph

Article in Health services research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

12 citing papers in PubMed.

  1. Trial
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  4. Hospital Allocation and Racial Disparities in Health Care.The review of economics and statistics · 2024
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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

2 authors.

Vivian Y WuSol Price School of Public Policy, University of Southern California, Los Angeles, CA.
Yu-Chu Shen

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo examine the long-term impact of Medicare payment reductions on patient outcomes for Medicare acute myocardial infarction (AMI) patients. DATA SOURCES: Analysis of secondary data compiled from 100 percent Medicare Provider Analysis and Review between 1995 and 2005, Medicare hospital cost reports, Inpatient Prospective Payment System Payment Impact Files, American Hospital Association annual surveys, InterStudy, Area Resource Files, and County Business Patterns. STUDY

designWe used a natural experiment-the Balanced Budget Act (BBA) of 1997-as an instrument to predict cumulative Medicare revenue loss due solely to the BBA, and basing on the predicted loss categorized hospitals into small, moderate, or large payment-cut groups and followed Medicare AMI patient outcomes in these hospitals over an 11-year panel between 1995 and 2005. PRINCIPAL

findingsWe found that while Medicare AMI mortality trends remained similar across hospitals between pre-BBA and initial-BBA periods, hospitals facing large payment cuts saw smaller improvement in mortality rates relative to that of hospitals facing small cuts in the post-BBA period. Part of the relatively higher AMI mortalities among large-cut hospitals might be related to reductions in staffing levels and operating costs, and a small part might be due to patient selection.

conclusionsWe found evidence that hospitals facing large Medicare payment cuts as a result of BBA of 1997 were associated with deteriorating patient outcomes in the long run. Medicare payment reductions may have an unintended consequence of widening the gap in quality across hospitals.

Indexed as

Cost ControlHospital CostsHospital MortalityHumansMedicareMyocardial InfarctionProspective Payment SystemProspective StudiesQuality of Health CareTreatment OutcomeUnited StatesBBAhospitalMedicaremortalitypayment reduction

Identifiers

PMID24845773
PMCPMC4213051

What OpenQuestion holds

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Registered trials

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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.