Paper Type
Complete
Paper Number
1812
Description
With increasing sophistication in wearable devices, Generative AI, and Quantum Computing, this paper reimagines the future of Precision Healthcare as a Service (PHCaaS). Specifically, how might we, for example, monitor patient wellness with wearable devices, AI interactions, and analytics on a trustworthy platform? As a first step, we establish and validate design rules using an emphatic, participatory approach called Soft Systems Modeling (SSM), prioritising patient-centricity. Drawing on prior research, we utilised Unified Modeling Language (UML) techniques to model and refine these rules, validated through a Delphi panel of potential PHC stakeholders. The procedural steps of SSM and UML methodologies utilised in the study are already detailed in prior work. This paper emphasises PHCaaS's link to patient-centricity, highlighting a commonly overlooked challenge for healthcare and technology providers. With the rise of generative AI and Large Language Models, ensuring data security, addressing bias, and building trust in PHCaaS become increasingly critical.
Recommended Citation
Zahid, Arnob; Wingreen, Stephen; Sharma, Ravi S.; and Inthiran, Anushia, "Digital Sustainable Healthcare: Field Validation of a Patient-centric Use-Case" (2024). PACIS 2024 Proceedings. 5.
https://aisel.aisnet.org/pacis2024/track11_healthit/track11_healthit/5
Digital Sustainable Healthcare: Field Validation of a Patient-centric Use-Case
With increasing sophistication in wearable devices, Generative AI, and Quantum Computing, this paper reimagines the future of Precision Healthcare as a Service (PHCaaS). Specifically, how might we, for example, monitor patient wellness with wearable devices, AI interactions, and analytics on a trustworthy platform? As a first step, we establish and validate design rules using an emphatic, participatory approach called Soft Systems Modeling (SSM), prioritising patient-centricity. Drawing on prior research, we utilised Unified Modeling Language (UML) techniques to model and refine these rules, validated through a Delphi panel of potential PHC stakeholders. The procedural steps of SSM and UML methodologies utilised in the study are already detailed in prior work. This paper emphasises PHCaaS's link to patient-centricity, highlighting a commonly overlooked challenge for healthcare and technology providers. With the rise of generative AI and Large Language Models, ensuring data security, addressing bias, and building trust in PHCaaS become increasingly critical.
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Comments
Healthcare