Evidence map›Paper›PMID 17711936›Full record

ArticleEmergency medicine journal : EMJ2007

Validation of a diagnostic reminder system in emergency medicine: a multi-centre study.

Padmanabhan Ramnarayan, Natalie Cronje, Ruth Brown, Rupert Negus, Bill Coode, Philip Moss, Taj Hassan, Wayne Hamer, Joseph Britto

Abstract readMulticenter StudyValidation Study
In one paragraph

Article in Emergency medicine journal : EMJ, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 pooled it
1.6field-weighted citation impact, top 14% 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.

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

21 citing papers in PubMed, 2 syntheses or guidelines pooled it, 51 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Early diagnostic suggestions improve accuracy of GPs: a randomised controlled trial using computer-simulated patients.The British journal of general practice : the journal of the Royal College of General Practitioners · 2015
    Trial
  6. Article
  7. Article
  8. Article
  9. Observational
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. 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

9 authors at 5 institutions in 1 country.

Padmanabhan RamnarayanChildren's Acute Transport Service, London WC1R 4LL, UK. ram@isabelhealthcare.com
Natalie Cronje
Ruth Brown
Rupert Negus
Bill Coode
Philip Moss
Taj Hassan
Wayne Hamer
Joseph Britto
Leeds General Infirmary · GBNewham University Hospital · GBSt Mary's Hospital · GBInforma Healthcare · GBTransport for London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiagnostic error is a significant problem in emergency medicine, where initial clinical assessment and decision making is often based on incomplete clinical information. Traditional computerised diagnostic systems have been of limited use in the acute setting, mainly due to the need for lengthy system consultation. We evaluated a novel web-based reminder system, which provides rapid diagnostic advice to users based on free text search terms.

methodsClinical data collected from patients presenting to three emergency departments with acute medical problems were entered into the diagnostic system. The displayed results were assessed against the final discharge diagnoses for patients who were admitted to hospital (diagnostic accuracy) and against a set of "appropriate" diagnoses for each case provided by an expert panel (potential utility).

resultsData were collected from 594 patients (53.4% of screened attendances). Mean age was 49.4 years (95% CI 47.7 to 51.1) and the majority had significant past illnesses. Most were assessed first by junior doctors (70%) and 266/594 (44.6%) were admitted to hospital. Overall, the diagnostic system displayed the final discharge diagnosis in 95% of inpatients and 90% of "must-not-miss" diagnoses suggested by the expert panel. The discharge diagnosis appeared within the first 10 suggestions in 78% of cases.

conclusionsThe Isabel diagnostic aid has been shown to be of potential use in reminding junior doctors of key diagnoses in the emergency department. The effects of its widespread use on decision making and diagnostic error can be clarified by evaluating its impact on routine clinical decision making.

Indexed as

Decision Support Systems, ClinicalReminder SystemsAnalysis of VarianceChi-Square DistributionDiagnosis, Computer-AssistedDiagnosis, DifferentialDiagnostic ErrorsEmergency Service, HospitalFemaleHumansLondonMaleMiddle AgedProspective StudiesUser-Computer Interface

Identifiers

PMID17711936
PMCPMC2464650
OpenAlexW2149078465

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.