Evidence map›Paper›PMID 12925549›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA

Measuring the impact of diagnostic decision support on the quality of clinical decision making: development of a reliable and valid composite score.

Padmanabhan Ramnarayan, Ritika R Kapoor, Michael Coren, Vasantha Nanduri, Amanda L Tomlinson, Paul M Taylor, Jeremy C Wyatt, Joseph F Britto

Abstract readValidation Study
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Trial
  2. 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
  3. Article
  4. Article
  5. A review of measurement practice in studies of clinical decision support systems 1998-2017.Journal of the American Medical Informatics Association : JAMIA · 2019
    Review
  6. Article
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  12. Review
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  14. Beyond the threshold: real-time use of evidence in practice.BMC medical informatics and decision making · 2013
    Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Diagnostic decision support systems: how to determine the gold standard?Journal of the American Medical Informatics Association : JAMIA
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Padmanabhan RamnarayanDepartment of Paediatrics, St. Mary's Hospital, London, England.
Ritika R Kapoor
Michael Coren
Vasantha Nanduri
Amanda L Tomlinson
Paul M Taylor
Jeremy C Wyatt
Joseph F Britto

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveFew previous studies evaluating the benefits of diagnostic decision support systems have simultaneously measured changes in diagnostic quality and clinical management prompted by use of the system. This report describes a reliable and valid scoring technique to measure the quality of clinical decision plans in an acute medical setting, where diagnostic decision support tools might prove most useful.

designSets of differential diagnoses and clinical management plans generated by 71 clinicians for six simulated cases, before and after decision support from a Web-based pediatric differential diagnostic tool (ISABEL), were used. MEASUREMENTS: A composite quality score was calculated separately for each diagnostic and management plan by considering the appropriateness value of each component diagnostic or management suggestion, a weighted sum of individual suggestion ratings, relevance of the entire plan, and its comprehensiveness. The reliability and validity (face, concurrent, construct, and content) of these two final scores were examined.

resultsTwo hundred fifty-two diagnostic and 350 management suggestions were included in the interrater reliability analysis. There was good agreement between raters (intraclass correlation coefficient, 0.79 for diagnoses, and 0.72 for management). No counterintuitive scores were demonstrated on visual inspection of the sets. Content validity was verified by a consultation process with pediatricians. Both scores discriminated adequately between the plans of consultants and medical students and correlated well with clinicians' subjective opinions of overall plan quality (Spearman rho 0.65, p < 0.01). The diagnostic and management scores for each episode showed moderate correlation (r = 0.51).

conclusionThe scores described can be used as key outcome measures in a larger study to fully assess the value of diagnostic decision aids, such as the ISABEL system.

Indexed as

Diagnosis, Computer-AssistedDiagnosis, DifferentialPatient Care PlanningArtificial IntelligenceClinical MedicineDecision MakingDecision Support Systems, ClinicalDecision Support TechniquesEvaluation Studies as TopicHumansInternetOutcome Assessment, Health CarePediatricsQuality of Health CareReminder SystemsReproducibility of Results

Identifiers

PMID12925549
PMCPMC264434

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Registered trials

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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.