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Title: Delivering Health Intelligence For Healthcare Services
Authors: Murray, Michael
Macedo, Mário
Glynn, Carole
Keywords: Artificial intelligence
Clinical decision support systems
Issue Date: Nov-2019
Citation: Murray, M.; Macedo, M. & Glynn, C.(2019). Delivering Health Intelligence For Healthcare Services. 2019 First International Conference on Digital Data Processing (DDP)
Abstract: The systems barrier for clinical information interoperability and standards has now evolved from a technology barrier to a semantic barrier. The processes to gather clinical data and to build clinical information and knowledge cannot be fully implemented, owing to semantic dissonances and limited data normalization. According to [1], “Just over a half of entered codes were appropriate for a given scenario and about a quarter were omitted.” This is a significant data and financial gap for healthcare provision. Huge amount of addition to the financial cost, lack of data integration and loss of information affects the ability to maintain standards in clinical care delivery and patient outcomes. This paper proposes that the solution to these issues is an augmented network of clinical note taking, where coding is automatically generated by an AI system as clinicians write their clinical notes. The system (AI-KEN) offers enhanced web support that is integrated to local clinical systems, whereby clinical notes are prompted by suggested predictive text options in real time. The anticipated benefits include reducing financial loss for acute services, support for clinical standard maintenance and enhanced advancements for clinical practice and research in real time.
Appears in Collections:CTIC/GSC - Comunicações a Conferências

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