Creation of clinical algorithms for decision-making in oncology: an example with dose prescription in radiation oncology

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 o...

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Bibliographic Details
Published in:BMC medical informatics and decision making 2021-07, Vol.21 (1), p.1-212, Article 212
Main Authors: Dennstädt, Fabio, Treffers, Theresa, Iseli, Thomas, Panje, Cédric, Putora, Paul Martin
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Artificial intelligence
Bone metastases
Cancer therapies
Clinical algorithm
Clinical decision making
Cognitive ability
Complexity
Decision making
Decision strategy
Dose prescription
Drug dosages
Emotions
Evidence-based medicine
Fractionation
Health aspects
Health services
Information processing
Innovations
Irradiation
Medicine
Metastases
Metastasis
Mood
Oncology
Physicians
Prescriptions
Radiation
Radiation dosage
Radiation oncology
Review
Software
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Summary: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 example 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.
ISSN:1472-6947
1472-6947
DOI:10.1186/s12911-021-01568-w