Background: The purpose of this study is to assess the Business-to-Consumer (B2C) model for telemonitoring patients with Chronic Heart Failure (CHF) by analysing the value it creates, both for organizations or ventures that provide telemonitoring services based on it, and for society. Methods: The business model assessment was based on the following categories: caveats, venture type, six-factor alignment, strategic market assessment, financial viability, valuation analysis, sustainability, societal impact, and technology assessment. The venture valuation was performed for three jurisdictions (countries) - Singapore, the Netherlands and the United States - in order to show the opportunities in a small, medium-sized, and large country (i.e. population). Results: The business model assessment revealed that B2C telemonitoring is viable and profitable in the Innovating in Healthcare Framework. Analysis of the ecosystem revealed an average-to-excellent fit with the six factors. The structure and financing fit was average, public policy and technology alignment was good, while consumer alignment and accountability fit was deemed excellent. The financial prognosis revealed that the venture is viable and profitable in Singapore and the Netherlands but not in the United States due to relatively high salary inputs. Conclusions: The B2C model in telemonitoring CHF potentially creates value for patients, shareholders of the service provider, and society. However, the validity of the results could be improved, for instance by using a peer-reviewed framework, a systematic literature search, case-based cost/efficiency inputs, and varied scenario inputs.

Additional Metadata
Keywords B2C, Business model, CHF, Financial analysis, Telemonitoring
Persistent URL,
Journal B M C Medical Informatics and Decision Making
Grustam, A.S, Vrijhoef, H.J.M. (Hubertus J. M.), Koymans, R, Hukal, P. (Philipp), & Severens, J.L. (2017). Assessment of a Business-to-Consumer (B2C) model for Telemonitoring patients with Chronic Heart Failure (CHF). B M C Medical Informatics and Decision Making, 17(1). doi:10.1186/s12911-017-0541-2