Evidence map›Paper›PMID 33879255›Full record

ArticleBioelectronic medicine2021

How artificial intelligence can help us 'Choose Wisely'.

Nishila Mehta, Karen Born, Benjamin Fine

Abstract read
In one paragraph

Article in Bioelectronic medicine, 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. Using AI to Improve Individual and Population Health.International journal of public health · 2026
    Article
  2. 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

3 authors.

Nishila MehtaTemerty Faculty of Medicine, King's College Cir, Toronto, ON, M5S 1A8, Canada. nishila.mehta@mail.utoronto.ca.ORCID http://orcid.org/0000-0002-6804-5075
Karen BornUnity Health Toronto, 30 Bond Street, Toronto, Ontario, M5B 1W8, Canada.
Benjamin FineTemerty Faculty of Medicine, King's College Cir, Toronto, ON, M5S 1A8, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The overuse of low value medical tests and treatments drives costs and patient harm. Efforts to address overuse, such as Choosing Wisely campaigns, typically rely on passive implementation strategies- a form of low reliability system change. Embedding guidelines into clinical decision support (CDS) software is a higher leverage approach to provide ordering suggestions through an interface embedded within the clinical workflow. Growth in computing power is increasingly enabling artificial intelligence (AI) to augment such decision making tools. This article offers a roadmap of opportunities for AI-enabled CDS to reduce overuse, which are presented according to a patient's journey of care.

Indexed as

Artificial intelligenceClinical decision supportQuality improvementResource stewardship

Identifiers

PMID33879255
PMCPMC8057918

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.