Evidence map›Paper›PMID 28480474›Full record

ReviewYearbook of medical informatics2017

Secondary Use and Analysis of Big Data Collected for Patient Care.

F J Martin-Sanchez, V Aguiar-Pulido, G H Lopez-Campos, N Peek, L Sacchi

Abstract readReview
In one paragraph

Review in Yearbook of medical informatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 2 pooled it
–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

29 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. The reuse of genetic information in research and informed consent.European journal of human genetics : EJHG · 2023
    Article
  11. Article
  12. NIH Primary and Secondary Prevention Research in Humans: a Portfolio Analysis of Study Designs Used in 2012-2019.Prevention science : the official journal of the Society for Prevention Research · 2022
    Observational
  13. Observational
  14. A data driven learning approach for the assessment of data quality.BMC medical informatics and decision making · 2021
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. A method for interoperable knowledge-based data quality assessment.BMC medical informatics and decision making · 2021
    Article
  20. 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

5 authors.

F J Martin-Sanchez
V Aguiar-Pulido
G H Lopez-Campos
N Peek
L Sacchi

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Data MiningPatient CareBiomedical ResearchDatabases, FactualHumansTranslational Research, Biomedical

Identifiers

PMID28480474
PMCPMC6239231

What OpenQuestion holds

Textmetadata
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.