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Toward Actionable Knowledge: A Systematic Analysis of Mobile Patient Portal Use

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Delivering Superior Health and Wellness Management with IoT and Analytics

Part of the book series: Healthcare Delivery in the Information Age ((Healthcare Delivery Inform. Age))

Abstract

As the aging population grows, chronic illness increases, and our healthcare costs sharply increase, patient portals are positioned as a central component of patient engagement through the potential to change the physician-patient relationship and enable chronic disease self-management. A patient’s engagement in their healthcare contributes to improving health outcomes, and information technologies can support health engagement. In this chapter, we extend the existing literature by discovering design gaps for patient portals from a systematic analysis of negative users’ feedback from the actual use of patient portals. Specifically, we adopt a topic modeling approach, latent Dirichlet allocation (LDA) algorithm, to discover design gaps from online low rating user reviews of a common mobile patient portal, EPIC’s mychart. To validate the extracted gaps, we compared the results of LDA analysis with that of human analysis. Overall, the results revealed opportunities to improve collaboration and to enhance the design of portals intended for patient-centered care. Incorporating these changes may enable the technologies to have stronger position to influence health improvement and wellness.

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Notes

  1. 1.

    The Jaccard coefficient measures similarity between finite sample sets, and is defined as the size of the intersection divided by the size of the union of the sample sets.

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Correspondence to Cherie Noteboom .

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Noteboom, C., Abdel-Rahman (Al-Ramahi), M. (2020). Toward Actionable Knowledge: A Systematic Analysis of Mobile Patient Portal Use. In: Wickramasinghe, N., Bodendorf, F. (eds) Delivering Superior Health and Wellness Management with IoT and Analytics. Healthcare Delivery in the Information Age. Springer, Cham. https://doi.org/10.1007/978-3-030-17347-0_29

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  • DOI: https://doi.org/10.1007/978-3-030-17347-0_29

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