Evidence map›Paper›PMID 34479398›Full record

ReviewYearbook of medical informatics2021

Public Health and Epidemiology Informatics: Recent Research Trends.

Gayo Diallo, Georgeta Bordea, Section Editors for the IMIA Yearbook Section on Public Health and Epidemiology Informatics

Open access · hybridAbstract readReview
In one paragraph

Review in Yearbook of medical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

7 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Review
  3. Global respiratory health priorities at the beginning of the 21st century.European respiratory review : an official journal of the European Respiratory Society · 2024
    Review
  4. Article
  5. Novelty in Public Health and Epidemiology Informatics.Yearbook of medical informatics · 2022
    Article
  6. Review
  7. Managing Pandemics with Health Informatics.Yearbook of medical informatics · 2021
    Review
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.

Gayo DialloINRIA SISTM, Team ERIAS - INSERM Bordeaux Population Health Research Center, Univ. Bordeaux, Bordeaux, France.
Georgeta BordeaINRIA SISTM, Team ERIAS - INSERM Bordeaux Population Health Research Center, Univ. Bordeaux, Bordeaux, France.
Section Editors for the IMIA Yearbook Section on Public Health and Epidemiology Informatics
Inserm · FRLaboratoire Bordelais de Recherche en Informatique · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo introduce and analyse current trends in Public Health and Epidemiology Informatics.

methodsPubMed search of 2020 literature on public health and epidemiology informatics was conducted and all retrieved references were reviewed by the two section editors. Then, 15 candidate best papers were selected among the 920 references. These papers were then peer-reviewed by the two section editors, two chief editors, and external reviewers, including at least two senior faculty, to allow the Editorial Committee of the 2021 International Medical Informatics Association (IMIA) Yearbook to make an informed decision regarding the selection of the best papers.

resultsAmong the 920 references retrieved from PubMed, four were suggested as best papers and the first three were finally selected. The fourth paper was excluded because of reproducibility issues. The first best paper is a very public health focused paper with health informatics and biostatistics methods applied to stratify patients within a cohort in order to identify those at risk of suicide; the second paper describes the use of a randomized design to test the likely impact of fear-based messages, with and without empowering self-management elements, on patient consultations or antibiotic requests for influenza-like illnesses. The third selected paper evaluates the perception among communities of routine use of Whole Genome Sequencing and Big Data technologies to capture more detailed and specific personal information.

conclusionsThe findings from the three studies suggest that using Public Health and Epidemiology Informatics methods could leverage, when combined with Deep Learning, early interventions and appropriate treatments to mitigate suicide risk. Further, they also demonstrate that well informing and empowering patients could help them to be involved more in their care process.

Indexed as

Anti-Bacterial AgentsDeep LearningElectronic Health RecordsEpidemiologyMedical InformaticsPopulation SurveillancePrimary Health CarePublic Health InformaticsSuicide, AttemptedAnti-Bacterial Agents

Identifiers

PMID34479398
PMCPMC8416213
OpenAlexW3196835883

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.