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DOI: 10.1055/a-1115-6980
Medizinische Spracherkennung im stationären und ambulanten Einsatz – Eine systematische Übersicht
Medical Speech Recognition in Inpatient and Outpatient Treatment – A Systematic ReviewZusammenfassung
Einleitung Die medizinische Dokumentation dient neben der Sicherung einer ordnungsgemäßen Behandlung auch der umfänglichen Aufklärung des Patienten. Gleichsam nimmt sie einen großen Anteil der Arbeitszeit von Gesundheitsprofessionen in Anspruch. Häufig ist die zeitnahe Fertigstellung der Dokumentation durch den zunehmenden Zeitdruck im klinischen Alltag zusätzlich erschwert. Um den Zeitaufwand für die medizinische Dokumentation zu reduzieren, werden auch im ärztlichen Dienst immer häufiger Spracherkennungstechnologien in Einsatz gebracht. Dennoch sind die Auswirkungen dieser medizinischen Spracherkennung auf Bearbeitungszeit und Qualität der Dokumentation zum aktuellen Zeitpunkt noch wenig erforscht. Die bestehende Literatur erfasst bis dato nicht in ausreichendem Maße alle Möglichkeiten des aktuellen technologischen Standes. Ziel dieser Übersichtsarbeit ist daher, den aktuellen Forschungsstand zu den Auswirkungen und Folgen des Einsatzes von digitaler Spracherkennung auf Arbeitsprozesse der Gesundheitsprofessionen zu analysieren. Dazu wurden alle seit dem Jahr 2000 veröffentlichten Studien der jeweiligen medizinischen Fachbereiche berücksichtigt.
Methode Die Autoren führten eine Literaturrecherche unter Verwendung der Datenbanken Medline via PubMed und Google Scholar durch. Die Datenbanken wurden nach den folgenden Stichwörtern durchsucht: „speech recognition“, „voice recognition“, „medical“ und „healthcare“. Unter der Annahme, dass sich erst die ab dem Jahr 2000 entwickelten Spracherkennungstechnologien bezüglich ihrer Genauigkeit für den medizinischen Bereich eignen, wurden Studien erst ab diesem Zeitpunkt in der vorliegenden Übersichtsarbeit berücksichtigt.
Ergebnisse Insgesamt lieferten die 29 für diese Analyse herangezogenen Studien sehr differente Ergebnisse. Im Vergleich zu alternativen Diktatserviceleistungen, konnte sich die Spracherkennungstechnologie als zeit- und kosteneffizienter erweisen. Im Vergleich zur Texteingabe zeigte sich die Spracherkennung in den betrachteten Studien jedoch nicht überlegen, was mehrheitlich an der geringeren beobachteten Genauigkeit der Spracherkennung lag.
Schlussfolgerung Der Einsatz von digitaler Spracherkennung im klinischen Betrieb bietet einige Vorteile bezüglich der reinen Dokumentationszeit. Die vorhandenen qualitativen Probleme in der genauen semantischen Umsetzung führen jedoch in den vorliegenden Studien noch nicht zu einer eindeutigen Evidenz der Vorteilhaftigkeit dieser Technologie. Aus diesem Grund besteht darüber hinaus Bedarf an weiteren Untersuchungen auf diesem Forschungsfeld.
Abstract
Introduction The medical documentation serves to ensure proper treatment and comprehensive information for the patient. At the same time, medical documentation takes up a large proportion of the working time of health professionals, and the increasing time pressure in everyday clinical life makes it more difficult to complete documentation promptly. With the aim of reducing the time required for medical documentation, speech recognition technologies are increasingly being used in the medical field. Nevertheless, the effect of medical speech recognition on the processing time and the quality of medical documentation appears to have been little researched to date and the existing literature does not capture the features of the current state of technology. The aim of this review is to analyse the current state of research on the effects of the use of digital speech recognition on the medical work processes, taking into account all since the year 2000 published studies of the medical disciplines.
Methods The literature search was carried out using the databases Medline via PubMed and Google Scholar. The databases were searched for keywords “speech recognition”, “voice recognition”, “medical” and “healthcare”. Under the assumption that the speech recognition technologies developed from the year 2000 onwards would be suitable for the medical-clinical field in terms of their accuracy, only the studies from 2000 or older were taken into account in this review.
Results In total, the 29 studies used for this analysis yielded very different results. Compared to the alternative “dictation service”, speech recognition technology proved to be more time and cost efficient. However, speech recognition was not superior to text input, mainly due to the lower observed accuracy of speech recognition.
Conclusion The use of speech recognition in clinical applications shows some advantages in terms of documentation time. However, the results of these studies do not yet provide clear evidence of the benefits of this technology. For this reason, there is still a need for further extensive investigations in this field of research.
Schlüsselwörter
Spracherkennung - medizinische Dokumentation - Digitalisierung - Spracheingabe - Systematische ÜbersichtsarbeitKey words
Speech recognition - Medical documentation - Digitalization - Voice typing - Systematic reviewPublication History
Article published online:
26 February 2020
© Georg Thieme Verlag KG
Stuttgart · New York
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