Evidence map›Paper›PMID 39222248›Full record

ReviewHealth economics review2024

Kidney transplant cases in US: study of determinants of variance in hospital charges and inpatient care.

Aigbe Akhigbe, Ravi Chinta

Abstract readReview
In one paragraph

Review in Health economics review, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Aigbe AkhigbeThe Peter J. Tobin College of Business, St. John's University, 8000 Utopia Parkway, 11439, Queens, NY, USA. akhigbea@stjohns.edu.
Ravi ChintaSchool of Business and Public Administration, University of District of Columbia, Washington DC, 20008, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We investigate the factors that influence the variance in hospital charges and inpatient care for kidney transplant cases in the US. Using the AHRQ's (Agency for Healthcare Research and Quality) HCUP's (Hospital Cost and Utilization Project) NIS (National Inpatient Sample) database, we find that variance in hospital charges and inpatient care is driven by patient demographics and hospital variables. We find that variance in hospital charges and inpatient care is determined by patient-specific factors including age, gender, race, and income, and hospital factors such as size, type, and location. Our results provide a deeper understanding of the non-clinical factors that impact hospital charges and inpatient care for kidney transplant patients.

Indexed as

Hospital characteristicsHospital chargesInpatient careKidney transplantsPatient demographics

Identifiers

PMID39222248
PMCPMC11370305

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.