Evidence map›Paper›PMID 32627391›Full record

ArticleClinical obesity2020

In-patient obesity diagnosis, use of surgical treatment and associated costs by payer type in the United States: Analysis of the National Inpatient Sample, 2011 through 2014.

Janani Rajbhandari-Thapa, Justin B Ingels, Sae R Chung, Kiran Thapa, Zhuo Chen, Donglan Zhang

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Clinical obesity, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 31% of its field
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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

6 authors at 1 institution in 1 country.

Janani Rajbhandari-ThapaDepartment of Health Policy and Management, College of Public Health, University of Georgia, Athens, Georgia, USA.ORCID https://orcid.org/0000-0002-0468-0387
Justin B IngelsDepartment of Health Policy and Management, College of Public Health, University of Georgia, Athens, Georgia, USA.
Sae R ChungDepartment of Financial Planning, Housing and Consumer Economics, College of Family and Consumer Sciences, University of Georgia, Athens, Georgia, USA.
Kiran ThapaDepartment of Health Policy and Management, College of Public Health, University of Georgia, Athens, Georgia, USA.
Zhuo ChenDepartment of Health Policy and Management, College of Public Health, University of Georgia, Athens, Georgia, USA.
Donglan ZhangDepartment of Health Policy and Management, College of Public Health, University of Georgia, Athens, Georgia, USA.
University of Georgia · US

Funding

Using machine learning and causal inference approaches to investigate disparities in Alzheimer’s disease and related dementias outcomesR01MD013886 · NIMHD · UNIVERSITY OF GEORGIA · PI ZHANG, DONGLAN · 2019 to 2022
$2.4M
National Institute for Minority Health and Health Disparity R01MD013886NIMHD NIH HHS R01 MD013886University of Georgia Presidential Interdisciplinary Seed Grant
6 · The paper itself

Abstract

This study aims to examine the trend in the diagnosis of obesity and the use of surgical treatment in in-patient settings as well as per person and national costs associated with the surgical treatment of obesity. We conducted cross-sectional and trend analyses of in-patient obesity diagnosis and surgical treatment for obesity using data from the National Inpatient Sample (2011-2014) of adult patients in the United States aged 18 years and older. We studied the rate of in-patient obesity diagnosis among hospitalized patients, the rate of bariatric surgery among patients diagnosed with obesity in the hospital, and the costs associated with surgical treatment. Trend analyses showed a statistically significant increase in the proportion of (a) hospitalized patients diagnosed with obesity, and (b) bariatric surgery among those diagnosed with obesity and among different socio-demographic and insurance groups. Despite the increase in the national in-patient cost, the average in-patient cost per hospitalization associated with bariatric surgery decreased from 2012 to 2014. With the increase in the rate of diagnosed obesity and bariatric surgery among hospitalized patients and the decrease in the average in-patient cost, future research should address the short- and long-term cost-effectiveness of bariatric surgery on chronic diseases.

Indexed as

AdolescentAdultBariatric SurgeryCost of IllnessCross-Sectional StudiesFemaleHealth Care CostsHospitalizationHumansInpatientsMaleMiddle AgedObesityUnited Statesbariatric surgerycostin-patient obesity diagnosistrend analysis

Identifiers

PMID32627391
PMCPMC8627372
OpenAlexW3038359447

What OpenQuestion holds

Textmetadata
LicenceTDM
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.