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Socio-Economic Impact Assessment and Business Models for Integrated eCare

Socio-Economic Impact Assessment and Business Models for Integrated eCare

Reinhard Hammerschmidt, Ingo Meyer
Copyright: © 2014 |Pages: 28
ISBN13: 9781466661387|ISBN10: 1466661380|EISBN13: 9781466661394
DOI: 10.4018/978-1-4666-6138-7.ch007
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MLA

Hammerschmidt, Reinhard, and Ingo Meyer. "Socio-Economic Impact Assessment and Business Models for Integrated eCare." Achieving Effective Integrated E-Care Beyond the Silos, edited by Ingo Meyer, et al., IGI Global, 2014, pp. 136-163. https://doi.org/10.4018/978-1-4666-6138-7.ch007

APA

Hammerschmidt, R. & Meyer, I. (2014). Socio-Economic Impact Assessment and Business Models for Integrated eCare. In I. Meyer, S. Müller, & L. Kubitschke (Eds.), Achieving Effective Integrated E-Care Beyond the Silos (pp. 136-163). IGI Global. https://doi.org/10.4018/978-1-4666-6138-7.ch007

Chicago

Hammerschmidt, Reinhard, and Ingo Meyer. "Socio-Economic Impact Assessment and Business Models for Integrated eCare." In Achieving Effective Integrated E-Care Beyond the Silos, edited by Ingo Meyer, Sonja Müller, and Lutz Kubitschke, 136-163. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-6138-7.ch007

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Abstract

Putting into place ICT-supported, integrated health and social care services means that a multitude of stakeholders are affected by changes to their working process and often to their economic performance. In this chapter, the authors describe their approach to assessing integrated eCare services to enable care integrators in making strategic decisions during development and early operation. The approach is founded on cost-benefit analysis. It stands out from other assessment frameworks in that it 1) allows identifying and addressing stakeholders that lose through the service and thus may become strong veto players, 2) allows monitoring of the actual and prospective service development over time, 3) includes non-financial factors that in many cases have a major impact on the behaviour of a stakeholder, and 4) provides probabilistic methods for achieving rigorous results from data of varying quality. Following an exemplary integration case developed from one of their pilot projects, the steps of the assessment process are described, including an exemplary interpretation of the analytic results and their application in practice. The chapter concludes with an outlook on future work.

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