Abstract
Objectives: By 2025, 90 percent of all care providers worldwide are expected to adopt cognitive AI help as evidence-driven care for their patients. Among all AI applications, clinical decision support systems (CDSS) are most likely to improve patient outcomes in the next 5–10 years. The objective of this paper is to analyze the business models of AI-based CDSS on the market to allow for generic statements on the design and state of the art of such business models. The study thereby aims at maximizing the utility of this technology by providing a basis for future business model considerations in this area.
Methods: Based on a comprehensive market analysis for AI-based solutions in the healthcare domain, we identify a sample of 36 commercially available CDSS and analyze their business models using the theoretical business model concept by Gassmann et al. [10].
Results: As a result, we identify generic attributes and alternate conditions of CDSS business models on the market in the respective key business model elements value proposition, value creation and value capture.
Conclusions: Based on the results, we develop a business model framework for AI-based CDSS that gives a first overview of the design of business models in this new technology field. Our findings contribute to closing a gap in the scientific literature and provide as a basis for future business model considerations.
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This work was supported as a Fraunhofer Lighthouse Project.
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Radić, M. et al. (2022). AI-Based Business Models in Healthcare: An Empirical Study of Clinical Decision Support Systems. In: Bach Tobji, M.A., Jallouli, R., Strat, V.A., Soares, A.M., Davidescu, A.A. (eds) Digital Economy. Emerging Technologies and Business Innovation. ICDEc 2022. Lecture Notes in Business Information Processing, vol 461. Springer, Cham. https://doi.org/10.1007/978-3-031-17037-9_5
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