Evidence map›Paper›PMID 37171506›Full record

ArticleHealth economics review2023

Global trends in the scientific research of the health economics: a bibliometric analysis from 1975 to 2022.

Liliana Barbu

Abstract read
In one paragraph

Article in Health economics review, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. 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

1 author.

Liliana BarbuFaculty of Economic Sciences, Lucian Blaga University of Sibiu, 550024, Sibiu, Romania. liliana.barbu@ulbsibiu.ro.ORCID http://orcid.org/0000-0003-0641-7483

Funding

Universitatea "Lucian Blaga" din Sibiu LBUS-IRG-2022-08
6 · The paper itself

Abstract

backgroundHealth science is evolving extremely rapidly at worldwide level. There is a large volume of articles about health economics that are published each year. The main purpose of this research is to explore health economics in the world's scholarly literature based on a scient metric analysis to outline the evolution of research in the field.

methodThe Web of Science repository was used to get the data (1975-2022). The study explores 1620 documents from health economics. CiteSpace software was used to provide network visualisations. Four thousand ninety-six authors, 1723 institutions, 847 journals and 82 countries were involved in the sample. The current research contains a descriptive analysis, a co-authorship analysis, a co-citation analysis, and a co-occurrence analysis in health economics.

resultsDrummond M.F (author), the USA (country), University of London (institution) and Value Health (journal) are among the most important contributors to the health economics literature. Co-authorship analysis highlights that cooperation between authors, institutions and countries is weak. However, Drummond M.F. is the most collaborative author, the USA is the most collaborative country, and University of York is the most collaborative institution. The study offers an image about the most co-cited references (Arrow K.J., 1963), authors (Margolis H.) and journals (British Medical Journal). The current research hotspots in health economics are "behavioural economics" and "economic evaluation". The main findings should be interpreted in accordance with the selection strategy used in this paper.

conclusionAll in all, the paper maps the literature on health economics and may be used for future research.

Indexed as

Bibliometric analysisCiteSpaceHealth economicsScientometrics

Identifiers

PMID37171506
PMCPMC10176285

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.