Evidence map›Paper›PMID 36767849›Full record

ReviewInternational journal of environmental research and public health2023

Literature Review on Health Emigration in Rare Diseases-A Machine Learning Perspective.

Małgorzata Skweres-Kuchta, Iwona Czerska, Elżbieta Szaruga

Open access · goldAbstract readReview
In one paragraph

Review in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.9field-weighted citation impact, top 21% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 2 institutions in 1 country.

Małgorzata Skweres-KuchtaDepartment of Organization and Management, Institute of Management, University of Szczecin, Cukrowa 8 Street, 71-004 Szczecin, Poland.ORCID 0000-0002-0540-5416
Iwona CzerskaDepartment of Marketing Research, Faculty of Management, Wroclaw University of Economics and Business, 118/120 Komandorska Str, 53-345 Wroclaw, Poland.ORCID 0000-0002-9680-6695
Elżbieta SzarugaDepartment of Transport Management, Institute of Management, University of Szczecin, Cukrowa 8 Street, 71-004 Szczecin, Poland.ORCID 0000-0001-6205-1311
University of Szczecin · PLWroclaw University of Economics and Business · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The article deals with one of the effects of health inequalities and gaps in access to treatments for rare diseases, namely health-driven emigration. The purpose of the paper is to systematize knowledge about the phenomenon of health emigration observed among families affected by rare diseases, for which reimbursed treatment is available, but only in selected countries. The topic proved to be niche; the issue of "health emigration in rare diseases" is an area for exploration. Therefore, the further analysis used text mining and machine learning methods based on a database selected based on keywords related to this issue. The results made it possible to systematize the guesses made by researchers in management and economic fields, to identify the most common keywords and thematic clusters around the perspective of the patient, drug manufacturer and treatment reimbursement decision-maker, and the perspective integrating all the others. Since the topic of health emigration was not directly addressed in the selected sources, the authors attempted to define the related concepts and discussed the importance of this phenomenon in managing the support system in rare diseases. Thus, they indicated directions for further research in this area.

Indexed as

Orphan Drug ProductionRare DiseasesEmigration and ImmigrationHealth InequitiesHumansMachine Learningaccess gapdiscrimination in access to therapyhealth emigrationorphan drugrare disease

Identifiers

PMID36767849
PMCPMC9915846
OpenAlexW4318587280

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.