Previously submitted to: JMIR Medical Informatics (no longer under consideration since Jun 20, 2024)
Date Submitted: Dec 28, 2023
Open Peer Review Period: Jan 15, 2024 - Mar 11, 2024
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An Omnichannel Mobile Companion for Personalized Healthcare: An Open Data Approach
ABSTRACT
Background:
In recent years, the concept of telemedicine and telehealth has been expanded a lot, and consequently, healthcare institutions are seeking innovative strategies to adopt these concepts in their services. The healthcare domain faces many challenges in terms of human resources allocation, systems integrations, and data interoperability. The adoption of an open-data approach in an omnichannel mobile companion can have a huge potential in how these strategies are designed. This research seeks to study the adoption of an open-data approach for an omnichannel mobile companion for personalized care services. Moreover, this paper will present a proof-of-concept and a demonstration regarding the design and implementation of an omnichannel mobile companion for personalized care services based on openEHR specifications for patient contact in ambulatory surgery.
Objective:
This research study aims to resolve some of the well-known identified gaps in the healthcare domain regarding personalized care services provided to patients (such as fragmented communication channels, lack of systems integration and interoperability, poor data access in real-time for timely decision-making, and overloaded health professionals) by leveraging the open-data approach in an omnichannel environment. Thus, this study aims to apply an innovative approach in this context to overcome the identified gaps and challenges in the healthcare domain.
Methods:
A case study and proof-of-concept method was applied in this research study, by designing a prototype of an omnichannel mobile companion for personalized care services. This will be materialized through a demonstration of a specific use case of the application of this approach.
Results:
Using an omnichannel mobile companion combined with the open-data approach allowed us to address and overcome the main gaps identified previously. Thus, this approach brings several gains to the healthcare domain and personalized care services such as an enhanced patient-centered approach, smooth and seamless access to health information, better systems and channels integration and data interoperability, more efficient data analytics and real-time insights, efficient resource allocation, and more. Moreover, these gains translate into better patient user experience with the care service provided to them.
Conclusions:
Despite the challenges encountered in carrying out this research study, it was possible to address and overcome the gaps identified. However, several issues persist, which require more attention in the field of personalized care services. The strategy proposed in this research study effectively overcame a substantial part of the challenges inherent to personalized care services but, additional challenges remain and deserve further consideration.
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