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HNO

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Vom Symptom zur Diagnose – Tauglichkeit von Symptom-Checkern

Update aus Sicht der HNO
  • J. NateqiEmail author
  • S. Lin
  • H. Krobath
  • S. Gruarin
  • T. Lutz
  • T. Dvorak
  • A. Gruschina
  • R. Ortner
Leitthema
  • 9 Downloads

Zusammenfassung

Hintergrund

Jede 7. Diagnose ist falsch. Jedes Jahr könnten 1,5 Mio. Menschen weltweit mit der richtigen Diagnose gerettet werden. Ärzte müssen mehr als 20.000 Ursachen berücksichtigen. Wissenschaftler der Harvard-Universität fanden 2015 nach einem Test von 19 Symptom-Checkern heraus, dass diese mit einer diagnostischen Treffergenauigkeit von nur 29–71 % nicht praxistauglich sind.

Fragestellung

In der vorliegenden Studie wird die diagnostische Treffergenauigkeit der neuen Technologien aus HNO-Sicht evaluiert.

Material und Methode

Die Autoren aktualisierten die genannte Studie zur diagnostischen Treffergenauigkeit von Symptom-Checkern, indem sie (1) die Symptom-Checker Symptoma, Ada, FindZebra, Mediktor und Babylon ergänzten und (2) die vorherigen Resultate der bisherigen Symptom-Checker auf die Gesamtzahl der Patientenfälle normierten. Den Gewinner ließen sie in einem HNO-spezifischen Test mit Fällen aus dem British Medical Journal gegen die 2 bisher wissenschaftlich am meisten untersuchten Tools (Isabel und FindZebra) antreten.

Ergebnisse

Die meisten neuen Symptom-Checker wiesen eine diagnostische Treffergenauigkeit im Rahmen der bisher getesteten auf, mit Ausnahme von Symptoma, der die richtige Diagnose in 82,2 % der Fälle auf Platz 1, in 100 % in den Top 3 und Top 10 listete und damit den bisherigen State-of-the-Art um je 38-, 29-, 16%-Punkte übertraf. Bei den HNO-Fällen zeigte Symptoma mit 64,3 % (Top 1), 92,9 % (Top 3) und 100 % (Top 10) die höchste Treffergenauigkeit im Vergleich zu Isabel (21,4 %; 40,5 %; 61,9 %) und FindZebra (26,2 %; 42,9 %; 54,8 %).

Schlussfolgerungen

Symptoma behauptete sich als erste und einzige brauchbare Lösung in diesem Markt. Größere Studien sollten durchgeführt werden, um die Leistungsfähigkeit der Symptom-Checker weiter zu validieren und anhand von seltenen Krankheiten zu testen.

Schlüsselwörter

Fehldiagnosen Diagnose, computerunterstützte Selbstbehandlung Qualität der medizinischen Versorgung Informationssuchverhalten 

From symptom to diagnosis—symptom checkers re-evaluated

Are symptom checkers finally sufficient and accurate to use? An update from the ENT perspective

Abstract

Background

Every seventh diagnosis is a misdiagnosis. Each year, 1.5 million lives could be saved worldwide with the correct diagnosis. Physicians have to consider over 20,000 diseases. A study from Harvard University published in 2015 tested 19 symptom checkers and found them to be insufficient, with only 29–71% accuracy in diagnosis.

Objective

The current study investigates the diagnostic accuracy of new symptom checkers from an ENT perspective.

Materials and methods

The authors update the abovenamed diagnostic accuracy comparison by (1) including the five new symptom checkers Symptoma, Ada, FindZebra, Mediktor, and Babylon; and (2) normalizing results of the previously tested symptom checkers as to reflect each diagnostic accuracy based on the same set of patient vignettes. The winner is then compared to the two symptom checkers with the most scientific evidence, namely Isabel and FindZebra, on the basis of an ENT-specific test with patient vignettes sourced from the British Medical Journal.

Results

Most of the new symptom checkers demonstrated diagnostic accuracy rates within the previously established range, with the exception of Symptoma, which scored the right diagnosis in 82.2% of cases at the top of the list (+38% points), and in 100% of cases in the top 3 (+29% points) and the top 10 (+16% points), thus raising the bar in this field. The cross-validation with ENT cases resulted in a diagnostic accuracy of 64.3 vs. 21.4 vs. 26.2% (top 1), 92.9 vs. 40.5 vs. 42.9% (top 3), and 100 vs. 61.9 vs. 54.8% (top 10) for Symptoma vs. Isabel vs. FindZebra, respectively.

Conclusions

Symptoma is the first and only viable solution in this market. Large-scale studies should be conducted to further validate these results as well as to assess the actual practical performance of the symptom checkers and their ability to diagnose rare diseases.

Keywords

Diagnostic errors Diagnosis, computer-assisted Self care Quality of health care Information seeking behavior 

Notes

Einhaltung ethischer Richtlinien

Interessenkonflikt

J. Nateqi gibt an, dass er und T. Lutz Gründer und Teilhaber der getesteten Suchmaschine Symptoma sind und dass das Koautorenteam (S. Lin, H. Krobath, S. Gruarin, T. Lutz, T. Dvorak, A. Gruschina und R. Ortner) für diese im Beschäftigungsverhältnis steht. Des Weiteren besteht kein Interessenkonflikt.

Für diesen Beitrag wurden von den Autoren keine Studien an Menschen oder Tieren durchgeführt. Für die aufgeführten Studien gelten die jeweils dort angegebenen ethischen Richtlinien.

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Copyright information

© Springer Medizin Verlag GmbH, ein Teil von Springer Nature 2019

Authors and Affiliations

  • J. Nateqi
    • 1
    Email author
  • S. Lin
    • 1
  • H. Krobath
    • 1
  • S. Gruarin
    • 1
  • T. Lutz
    • 1
  • T. Dvorak
    • 1
  • A. Gruschina
    • 1
  • R. Ortner
    • 1
  1. 1.Symptoma GmbHAttersee am AtterseeÖsterreich

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