Literature DB >> 15617979

Do physicians value decision support? A look at the effect of decision support systems on physician opinion.

Stephan Dreiseitl1, Michael Binder.   

Abstract

OBJECTIVE: Clinical decision support systems are on the verge of becoming routine software tools in clinical settings. We investigate the question of how physicians react when faced with decision support suggestions that contradict their own diagnoses.
METHODOLOGY: We used a study design involving 52 volunteer dermatologists who each rated the malignancy of 25 lesion images on an ordinal scale and gave a dichotomous excise/no excise recommendation for each lesion image. After seeing the system's rating and excise suggestions, the physicians could revise their initial recommendations.
RESULTS: We observed that in 24% of the cases in which the physicians' diagnoses did not match those of the decision support system, the physicians changed their diagnoses. There was a slight but significant negative correlation between susceptibility to change and experience level of the physicians. Physicians were significantly less likely to follow the decision system's recommendations when they were confident of their initial diagnoses. No differences between the physicians' inclinations to following excise versus no excise recommendations could be observed.
CONCLUSION: These results indicate that physicians are quite susceptible to accepting the recommendations of decision support systems, and that quality assurance and validation of such systems is therefore of paramount importance.

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Mesh:

Year:  2005        PMID: 15617979     DOI: 10.1016/j.artmed.2004.07.007

Source DB:  PubMed          Journal:  Artif Intell Med        ISSN: 0933-3657            Impact factor:   5.326


  13 in total

1.  Applying a decision support system in clinical practice: results from melanoma diagnosis.

Authors:  Stephan Dreiseitl; Michael Binder; Staal Vinterbo; Harald Kittler
Journal:  AMIA Annu Symp Proc       Date:  2007-10-11

Review 2.  Automation bias: a systematic review of frequency, effect mediators, and mitigators.

Authors:  Kate Goddard; Abdul Roudsari; Jeremy C Wyatt
Journal:  J Am Med Inform Assoc       Date:  2011-06-16       Impact factor: 4.497

3.  [Image-based computer diagnosis of melanoma].

Authors:  V Dick; P Tschandl; C Sinz; A Blum; H Kittler
Journal:  Hautarzt       Date:  2018-07       Impact factor: 0.751

4.  VIKOR method with enhanced accuracy for multiple criteria decision making in healthcare management.

Authors:  Qiang-Lin Zeng; Dan-Dan Li; Yi-Bin Yang
Journal:  J Med Syst       Date:  2013-02-03       Impact factor: 4.460

5.  Are residents' decisions influenced more by a decision aid or a specialist's opinion? A randomized controlled trial.

Authors:  Mitchell A Medow; Hal R Arkes; Victoria A Shaffer
Journal:  J Gen Intern Med       Date:  2010-01-30       Impact factor: 5.128

6.  Predicting treatment outcome in depression: an introduction into current concepts and challenges.

Authors:  Nicolas Rost; Elisabeth B Binder; Tanja M Brückl
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2022-05-19       Impact factor: 5.270

7.  The Artificial Intelligence Doctor: Considerations for the Clinical Implementation of Ethical AI.

Authors:  Julius M Kernbach; Karlijn Hakvoort; Jonas Ort; Hans Clusmann; Georg Neuloh; Daniel Delev
Journal:  Acta Neurochir Suppl       Date:  2022

Review 8.  Societal Issues Concerning the Application of Artificial Intelligence in Medicine.

Authors:  Alfredo Vellido
Journal:  Kidney Dis (Basel)       Date:  2018-09-03

9.  Computer-assisted diagnosis techniques (dermoscopy and spectroscopy-based) for diagnosing skin cancer in adults.

Authors:  Lavinia Ferrante di Ruffano; Yemisi Takwoingi; Jacqueline Dinnes; Naomi Chuchu; Susan E Bayliss; Clare Davenport; Rubeta N Matin; Kathie Godfrey; Colette O'Sullivan; Abha Gulati; Sue Ann Chan; Alana Durack; Susan O'Connell; Matthew D Gardiner; Jeffrey Bamber; Jonathan J Deeks; Hywel C Williams
Journal:  Cochrane Database Syst Rev       Date:  2018-12-04

10.  Computer-Aided Decision Support for Melanoma Detection Applied on Melanocytic and Nonmelanocytic Skin Lesions: A Comparison of Two Systems Based on Automatic Analysis of Dermoscopic Images.

Authors:  Kajsa Møllersen; Herbert Kirchesch; Maciel Zortea; Thomas R Schopf; Kristian Hindberg; Fred Godtliebsen
Journal:  Biomed Res Int       Date:  2015-11-26       Impact factor: 3.411

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