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Proceedings 2017, 1(3), 170; doi:10.3390/IS4SI-2017-04014

Predicting Pregnancy Complications in Low Resource Contexts

Department of Applied IT, University of Gothenburg, Forskningsgangen 6, 41796 Gothenburg, Sweden
Presented at the IS4SI 2017 Summit DIGITALISATION FOR A SUSTAINABLE SOCIETY, Gothenburg, Sweden, 12–16 June 2017.
Published: 9 June 2017
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The United Nations listed maternal mortality as a major problem especially in developing countries. Predictive models that predict pregnancy complications have been suggested as an intervention to reduce maternal mortality but at the moment, many are not used in clinical practice. This study proposes a service-dominant perspective as an alternative use of predictive models to create value for maternal healthcare. I anticipate that through the use of the service innovation framework and social capital theory, I can study how health practitioners and pregnant women can be empowered with skills and knowledge to predict pregnancy complications and trigger collaborative value creation.
Keywords: service-dominant logic; maternal healthcare; predictive models; pregnancy complications service-dominant logic; maternal healthcare; predictive models; pregnancy complications
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Nyende, H. Predicting Pregnancy Complications in Low Resource Contexts. Proceedings 2017, 1, 170.

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