Evidence map›Paper›PMID 39812666›Full record

ArticleDie Ophthalmologie2025

[Implementation and evaluation of a solution for automated documentation of the doctor-patient dialogue (ADAPI) in ophthalmology using the example of the IVI routine].

Clemens N Rudolph, Philip Wakili, Annekatrin Rickmann, Kai Januschowski, Patrick McCrae, Kilian Foth, Marco Petris, Annika Schilk, Stephan Kiefer, Kerstin Rohm and 6 more

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Article in Die Ophthalmologie, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

16 authors.

Clemens N RudolphAugenklinik Sulzbach, Knappschaftsklinikum Saar, An der Klinik 10, 66280, Sulzbach/Saar, Deutschland. Clemens.Rudolph@kksaar.de.ORCID http://orcid.org/0009-0001-3679-5074
Philip WakiliAugenklinik Sulzbach, Knappschaftsklinikum Saar, An der Klinik 10, 66280, Sulzbach/Saar, Deutschland.
Annekatrin RickmannAugenklinik Sulzbach, Knappschaftsklinikum Saar, An der Klinik 10, 66280, Sulzbach/Saar, Deutschland.
Kai JanuschowskiAugenklinik Sulzbach, Knappschaftsklinikum Saar, An der Klinik 10, 66280, Sulzbach/Saar, Deutschland.
Patrick McCraeLang.Tec, Hamburg, Deutschland.
Kilian FothLang.Tec, Hamburg, Deutschland.
Marco PetrisLang.Tec, Hamburg, Deutschland.
Annika SchilkLang.Tec, Hamburg, Deutschland.
Stephan KieferFraunhofer Institut für Biomedizinische Technik (IBMT), Sulzbach/Saar, Deutschland.
Kerstin RohmFraunhofer Institut für Biomedizinische Technik (IBMT), Sulzbach/Saar, Deutschland.
Suhail AhamedFraunhofer Institut für Biomedizinische Technik (IBMT), Sulzbach/Saar, Deutschland.
Gabriele WeilerFraunhofer Institut für Biomedizinische Technik (IBMT), Sulzbach/Saar, Deutschland.
Matthias StennesFraunhofer Institut für Digitale Medientechnologie (IDMT), Oldenburg, Deutschland.
André TrouvainAugenklinik Sulzbach, Knappschaftsklinikum Saar, An der Klinik 10, 66280, Sulzbach/Saar, Deutschland.
Peter SzurmanAugenklinik Sulzbach, Knappschaftsklinikum Saar, An der Klinik 10, 66280, Sulzbach/Saar, Deutschland.
Karl T BodenAugenklinik Sulzbach, Knappschaftsklinikum Saar, An der Klinik 10, 66280, Sulzbach/Saar, Deutschland.

Funding

Bundesministerium für Wirtschaft und Energie 16KN071926
6 · The paper itself

Abstract

backgroundThe increasing bureaucratic burden in everyday clinical practice impairs doctor-patient communication (DPC). Effective use of digital technologies, such as automated semantic speech recognition (ASR) with automated extraction of diagnostically relevant information can provide a solution.

objectiveThe aim was to determine the extent to which ASR in conjunction with semantic information extraction for automated documentation of the doctor-patient dialogue (ADAPI) can be integrated into everyday clinical practice using the IVI routine as an example and whether patient care can be improved through process optimization.

methodsIn a prospective monocentric study at the Sulzbach Eye Clinic, 50 patients were included in the period from 2020 to 2022. As part of a project funded by the "Zentrale Initiative des Mittelstandes" (ZIM), a demonstrator was developed with the consortium partners and integrated into the hospital information system (HIS). For qualitative and quantitative evaluation, a survey of patients was carried out using a questionnaire before and after implementation of the ADAPI module, supplemented by a determination of acceptance and possible time saving for users.

resultsThe ADAPI module was successfully integrated into the HIS. The documentation of the findings and connection of the subsequent processes could be automated. An improvement in the DPC was reported for 13/50 patients (26%). The majority 35/50 (70%) did not notice any subjective change. The average duration of the conversation in the area of conventional documentation was 4.46 min (1-10 min) and 3.9 min with ADAPI (1-10 min).

conclusionWith respect to the quality of the conversation within the DPC, no relevant differences could be shown with both types of documentation; however, larger case numbers and other areas of application still need to be evaluated. In the long term, the use of automated documentation solutions will sustainably improve the efficiency, completeness and consistency of clinical documentation.

Indexed as

DocumentationElectronic Health RecordsOphthalmologyPhysician-Patient RelationsSpeech Recognition SoftwareAgedAutomationFemaleHospital Information SystemsHumansMaleMiddle AgedProspective StudiesArtificial intelligenceAutomatic speech recognitionDigitalization of clinical documentationDigital technologyMedical documentation

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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.