Dennstädt et al. BMC Med Inform Decis Mak (2021) 21:212 https://doi.org/10.1186/s12911-021-01568-w REVIEW Creation of clinical algorithms for decision-making in oncology: an example with dose prescription in radiation oncology Fabio Dennstädt 1* , Theresa Treffers 2,3 , Thomas Iseli 1 , Cédric Panje 1,4 and Paul Martin Putora 1,4 Abstract In oncology, decision-making in individual situations is often very complex. To deal with such complexity, people tend to reduce it by relying on their initial intuition. The downside of this intuitive, subjective way of decision-making is that it is prone to cognitive and emotional biases such as overestimating the quality of its judgements or being influenced by one’s current mood. Hence, clinical predictions based on intuition often turn out to be wrong and to be outperformed by statistical predictions. Structuring and objectivizing oncological decision-making may thus overcome some of these issues and have advantages such as avoidance of unwarranted clinical practice variance or error-prevention. Even for uncertain situations with limited medical evidence available or controversies about the best treatment option, structured decision-making approaches like clinical algorithms could outperform intuitive decision- making. However, the idea of such algorithms is not to prescribe the clinician which decision to make nor to abolish medical judgement, but to support physicians in making decisions in a systematic and structured manner. An exam- ple for a use-case scenario where such an approach may be feasible is the selection of treatment dose in radiation oncology. In this paper, we will describe how a clinical algorithm for selection of a fractionation scheme for palliative irradiation of bone metastases can be created. We explain which steps in the creation process of a clinical algorithm for supporting decision-making need to be performed and which challenges and limitations have to be considered. Keywords: Decision-making, Clinical algorithm, Decision strategy, Radiation oncology, Dose prescription, Bone metastases © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativeco mmons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Background Most of the work done by physicians in oncology relies to some level on decision-making. Tis includes defnition of indication, evaluation of the oncological situation and available treatment options, as well as reacting to treat- ment-related side efects and complications. In individual clinical situations evidence regarding which decision is best is often lacking. While guidelines often provide just a vague orientation, decision-making is mostly done in a more or less intuitive and open way, based on experi- ence, personal opinions and emotions [1, 2]. While being highly fexible, intuitive decision-making can be prob- lematic, as it tends to be inconsistent and is prone to biases [3]. While the growing oncological knowledge is becoming more and more complex, physicians are chal- lenged with difcult decisions in situations of big uncer- tainties. Due to that, support of clinical decision-making, e.g. via Clinical Decision Support Systems (CDSS), is a feld of emerging interest, particularly in oncology [4] and radiation oncology [5]. Structuring of decision- making, even in situations of uncertainties and lack- ing evidence, may hold great advantages, which can be explained by decision-making theory. Instead of making Open Access *Correspondence: fabio.dennstaedt@kssg.ch 1 Department of Radiation Oncology, Kantonsspital St. Gallen, Rorschacherstrasse 95, 9000 St. Gallen, Switzerland Full list of author information is available at the end of the article