Evidence map›Paper›PMID 39735827›Full record

ArticlePerspectives on medical education2024

Proximity to Practice: The Role of Technology in the Next Era of Assessment.

Andrew E Krumm, Hollis Lai, Kayla Marcotte, Tavinder K Ark, Victoria Yaneva, Saad Chahine

Abstract read
In one paragraph

Article in Perspectives on medical education, 2024. 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. Article
  2. Introducing the Next Era in Assessment.Perspectives on medical education · 2025
    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

6 authors.

Andrew E KrummLearning Health Sciences, Surgery, and Information, Medical School and School of Information, University of Michigan, Ann Arbor, Michigan, United States.ORCID 0000-0001-9714-1632
Hollis LaiFaculty of Medicine and Dentistry, University of Alberta, Canada.ORCID 0000-0002-5531-6622
Kayla MarcotteDepartment of Learning Health Sciences, University of Michigan, Ann Arbor, Michigan, United States.ORCID 0000-0001-8773-213X
Tavinder K ArkData Science Institute and Center for Advancing Population Science, Medical Colleges of Wisconsin, United States.ORCID 0009-0006-2799-1416
Victoria YanevaNBME, Philadelphia, United States.ORCID 0000-0002-0285-4654
Saad ChahineFaculty of Education, Queen's University, Canada.ORCID 0000-0003-0488-773X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integration of technology into health professions assessment has created multiple possibilities. In this paper, we focus on the challenges and opportunities of integrating technologies that are used during clinical activities or that are completed by raters after a clinical encounter. In focusing on technologies that are more proximal to practice, we identify tradeoffs with different data collection approaches. To maximize the benefits of integrating technology in workplace-based assessment, we describe the importance of using preexisting frameworks from the fields of assessment design, implementation research, and clinical artificial intelligence governance.

Indexed as

Artificial IntelligenceHumans

Identifiers

PMID39735827
PMCPMC11673589

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.