Resumen
Inappropriate pathology test orders are an economic burden on laboratories and compromise patient safety. We pursue a laboratory utilization management strategy that involves raising awareness amongst physicians regarding their test ordering behaviour. We are employing an AI-driven approach for laboratory utilization management, whereby we apply both machine learning and semantic reasoning methods to analyze pathology laboratory data. We are analyzing over 6-years of primary care physician’s pathology test order ‘big’ data. Our analysis generates physician order profiles, based on their case-mix and orders-sets, to inform physicians about their laboratory utilization. We developed an AI-driven platform—i.e. Pathology Laboratory Utilization Scorecards (PLUS) that offers an interactive means for physicians to self-examine their test ordering pattern. PLUS aims to optimize the utilization of the Central Zone pathology laboratory of the Nova Scotia Health Authority.
Idioma original | English |
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Título de la publicación alojada | Artificial Intelligence in Medicine - 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Proceedings |
Editores | David Riaño, Szymon Wilk, Annette ten Teije |
Editorial | Springer Verlag |
Páginas | 241-251 |
Número de páginas | 11 |
ISBN (versión impresa) | 9783030216412 |
DOI | |
Estado | Published - 2019 |
Evento | 17th Conference on Artificial Intelligence in Medicine, AIME 2019 - Poznan, Poland Duración: jun. 26 2019 → jun. 29 2019 |
Serie de la publicación
Nombre | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volumen | 11526 LNAI |
ISSN (versión impresa) | 0302-9743 |
ISSN (versión digital) | 1611-3349 |
Conference
Conference | 17th Conference on Artificial Intelligence in Medicine, AIME 2019 |
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País/Territorio | Poland |
Ciudad | Poznan |
Período | 6/26/19 → 6/29/19 |
Nota bibliográfica
Funding Information:We thank the NSHA Central Zone pathology lab for supporting the project, and Nova Scotia Health Research Foundation for giving the catalyst grant.
Funding Information:
Acknowledgements. We thank the NSHA Central Zone pathology lab for supporting the project, and Nova Scotia Health Research Foundation for giving the catalyst grant.
Publisher Copyright:
© Springer Nature Switzerland AG 2019.
ASJC Scopus Subject Areas
- Theoretical Computer Science
- General Computer Science