Evidence map›Paper›PMID 33676513›Full record

ReviewBMC medical informatics and decision making2021

The concept of justifiable healthcare and how big data can help us to achieve it.

Wim van Biesen, Catherine Van Der Straeten, Sigrid Sterckx, Johan Steen, Lisa Diependaele, Johan Decruyenaere

Abstract readReview
In one paragraph

Review in BMC medical informatics and decision making, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Ethical considerations on the use of big data and artificial intelligence in kidney research from the ERA ethics committee.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2025
    Review
  2. 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

6 authors.

Wim van BiesenRenal Division, 0K12 IA, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Gent, Belgium. wim.vanbiesen@ugent.be.ORCID 0000-0002-4782-5224
Catherine Van Der StraetenHealth, Innovation and Research Institute, Ghent University Hospital, Ghent, Belgium.
Sigrid SterckxConsortium for Justifiable Healthcare, Ghent University Hospital, Ghent, Belgium.
Johan SteenRenal Division, 0K12 IA, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Gent, Belgium.
Lisa DiependaeleConsortium for Justifiable Healthcare, Ghent University Hospital, Ghent, Belgium.
Johan DecruyenaereConsortium for Justifiable Healthcare, Ghent University Hospital, Ghent, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the last decades, the face of health care has changed dramatically, with big improvements in what is technically feasible. However, there are indicators that the current approach to evaluating evidence in health care is not holistic and hence in the long run, health care will not be sustainable. New conceptual and normative frameworks for the evaluation of health care need to be developed and investigated. The current paper presents a novel framework of justifiable health care and explores how the use of artificial intelligence and big data can contribute to achieving the goals of this framework.

Indexed as

Artificial IntelligenceBig DataDelivery of Health CareHealth FacilitiesHumans

Identifiers

PMID33676513
PMCPMC7937275

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.