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Master Thesis

Apport du moteur de recherche Google pour le diagnostic de maladies rares en rhumatologie : une analyse descriptive

Abstract : Objective : The objective of this study was to evaluate the contribution of Google for the diagnosis of rare diseases in Rheumatology. Methods : Thirty cases of rare pathologies with osseous or articular expression were selected in the database of our hospital. Each medical record wassummarized in the form of clinical observation including the not interpreted examinations of imaging. Eight doctors rheumatologists not knowing these patients (five seniors and three interns at the end of course) were selected to participate in this study. After reading of each of the observations, it was proposed to each doctor to write one or several chains of keywords to be submitted to the search engine and to analyze the data supplied by the request. Several successive requests were authorized. At the end of the search, the doctors were invited to propose a diagnosis. An observant doctor (mute) followed the operation and noted the diagnosis selected (principal criterion), the number of keywords and chains of keywords used, the number of consulted websites and the time of Internet search (secondary criteria). Results : The average rate of exact diagnoses was 26/30 (86.7 % ± 5 %) with a minimum of 23/30 and a maximum of 28/30. All confused participants and all clinical cases, the use of 2.7 ± 1.1 keywords per request (1 at least and 6 at the most) and of 1.85 ± 1.3 chains of keywords (1 at least and 9 at the most), the consultation of 2.4 ± 1.9 websites (1 at least and 12 at the most) and a search time of 6.9 ± 4.9 minutes (2 at least and 20 at the most) were enough on average to propose a diagnosis. Conclusion : In front of complex or rare clinical cases, doctors have to conceive Internet and search engines like integral part of their strategy to reduce the times of diagnosis and improve the medical care of their patients.
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Master Thesis
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Contributor : Bu Carreire Université de Bordeaux <>
Submitted on : Wednesday, December 16, 2015 - 4:46:31 PM
Last modification on : Wednesday, August 23, 2017 - 4:30:54 PM
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  • HAL Id : dumas-01245091, version 1



Antoine Merlet. Apport du moteur de recherche Google pour le diagnostic de maladies rares en rhumatologie : une analyse descriptive. Médecine humaine et pathologie. 2015. ⟨dumas-01245091⟩



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