• Julia Sellin, Jean Tori Pantel, Natalie Börsch, Rupert Conrad, and Martin Mücke.
• Institut für Digitale Allgemeinmedizin, Universitätsklinikum RWTH Aachen, Aachen, Deutschland. jsellin@ukaachen.de.
• Schmerz. 2024 Feb 1; 38 (1): 192719-27.

BackgroundRare diseases are often recognized late. Their diagnosis is particularly challenging due to the diversity, complexity and heterogeneity of clinical symptoms. Computer-aided diagnostic aids, often referred to as diagnostic decision support systems (DDSS), are promising tools for shortening the time to diagnosis. Despite initial positive evaluations, DDSS are not yet widely used, partly due to a lack of integration with existing clinical or practice information systems.ObjectiveThis article provides an insight into currently existing diagnostic support systems that function without access to electronic patient records and only require information that is easily obtainable.Materials And MethodsA systematic literature search identified eight articles on DDSS that can assist in the diagnosis of rare diseases with no need for access to electronic patient records or other information systems in practices and hospitals. The main advantages and disadvantages of the identified rare disease diagnostic support systems were extracted and summarized.ResultsSymptom checkers and DDSS based on portrait photos and pain drawings already exist. The degree of maturity of these applications varies.ConclusionDDSS currently still face a number of challenges, such as concerns about data protection and accuracy, and acceptance and awareness continue to be rather low. On the other hand, there is great potential for faster diagnosis, especially for rare diseases, which are easily overlooked due to their large number and the low awareness of them. The use of DDSS should therefore be carefully considered by doctors on a case-by-case basis.© 2023. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.

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