Evidence map›Paper›PMID 33675203›Full record

ArticleDiagnosis (Berlin, Germany)2021

Real-world virtual patient simulation to improve diagnostic performance through deliberate practice: a prospective quasi-experimental study.

Susrutha Kotwal, Mehdi Fanai, Wei Fu, Zheyu Wang, Anand K Bery, Rodney Omron, Nana Tevzadze, Daniel Gold, Brian T Garibaldi, Scott M Wright and 1 more

Registry-linked trialOpen access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Diagnosis (Berlin, Germany), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02483429 (Acute Video-oculography for Vertigo in Emergency Rooms for Rapid Triage), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.1field-weighted citation impact, top 15% 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.

NCT02483429 phase2completednot on this map

Acute Video-oculography for Vertigo in Emergency Rooms for Rapid Triage (AVERT)

TypeinterventionalSponsorJohns Hopkins UniversityRan2017 to 2023Enrolled130ConditionsVertigo, DizzinessArmsVRT Care
3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. A Symbolic AI Approach to Medical Training.Journal of medical systems · 2025
    Article
  5. Review
  6. 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

11 authors at 5 institutions in 2 countries.

Susrutha KotwalDepartment of Medicine, Division of Hospital Medicine, Johns Hopkins Bayview Medical Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Mehdi FanaiCenter for Diagnostic Excellence, Armstrong Institute for Patient Safety and Quality, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Wei FuDepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Zheyu WangCenter for Diagnostic Excellence, Armstrong Institute for Patient Safety and Quality, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Anand K BeryDepartment of Medicine, Division of Neurology, The Ottawa Hospital, Ottawa, Canada.
Rodney OmronCenter for Diagnostic Excellence, Armstrong Institute for Patient Safety and Quality, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Nana TevzadzeDepartment of Neurology, Division of Neuro-Visual & Vestibular Disorders, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Daniel GoldDepartment of Neurology, Division of Neuro-Visual & Vestibular Disorders, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Brian T GaribaldiCenter for Diagnostic Excellence, Armstrong Institute for Patient Safety and Quality, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Scott M WrightDepartment of Medicine, Division of Hospital Medicine, Johns Hopkins Bayview Medical Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
David E Newman-TokerCenter for Diagnostic Excellence, Armstrong Institute for Patient Safety and Quality, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Johns Hopkins University · USJohns Hopkins Bayview Medical Center · USJohns Hopkins Medicine · USNational Patient Safety Foundation · USOttawa Hospital · CA

Funding

Research Supplement to Promote Diversity in Health-Related Research U01DC013778-01A1U01DC013778 · NIDCD · JOHNS HOPKINS UNIVERSITY · PI NEWMAN-TOKER, DAVID · 2014 to 2018
$5.4M
NIDCD NIH HHS U01 DC013778
6 · The paper itself

Abstract

objectivesDiagnostic errors are pervasive in medicine and most often caused by clinical reasoning failures. Clinical presentations characterized by nonspecific symptoms with broad differential diagnoses (e.g., dizziness) are especially prone to such errors.

methodsWe hypothesized that novice clinicians could achieve proficiency diagnosing dizziness by training with virtual patients (VPs). This was a prospective, quasi-experimental, pretest-posttest study (2019) at a single academic medical center. Internal medicine interns (intervention group) were compared to second/third year residents (control group). A case library of VPs with dizziness was developed from a clinical trial (AVERT-NCT02483429). The approach (VIPER - Virtual Interactive Practice to build Expertise using Real cases) consisted of brief lectures combined with 9 h of supervised deliberate practice. Residents were provided dizziness-related reading and teaching modules. Both groups completed pretests and posttests.

resultsFor interns (n=22) vs. residents (n=18), pretest median diagnostic accuracy did not differ (33% [IQR 18-46] vs. 31% [IQR 13-50], p=0.61) between groups, while posttest accuracy did (50% [IQR 42-67] vs. 20% [IQR 17-33], p=0.001). Pretest median appropriate imaging did not differ (33% [IQR 17-38] vs. 31% [IQR 13-38], p=0.89) between groups, while posttest appropriateness did (65% [IQR 52-74] vs. 25% [IQR 17-36], p<0.001).

conclusionsJust 9 h of deliberate practice increased diagnostic skills (both accuracy and testing appropriateness) of medicine interns evaluating real-world dizziness '

Indexed as

Internship and ResidencyPatient SimulationClinical CompetenceHumansProspective Studiesdiagnostic errordizzinessmedical educationsimulation trainingstrokevirtual patient education

Identifiers

PMID33675203
PMCPMC9023126
OpenAlexW3134270660

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

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.