From Cues to Nudge

A Knowledge-Based Framework for Surveillance of Healthcare-Associated Infections

Arash Shaban-Nejad, Hiroshi Mamiya, Alexandre Riazanov, Alan J. Forster, Christopher J.O. Baker, Robyn Tamblyn, David L. Buckeridge

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

We propose an integrated semantic web framework consisting of formal ontologies, web services, a reasoner and a rule engine that together recommend appropriate level of patient-care based on the defined semantic rules and guidelines. The classification of healthcare-associated infections within the HAIKU (Hospital Acquired Infections – Knowledge in Use) framework enables hospitals to consistently follow the standards along with their routine clinical practice and diagnosis coding to improve quality of care and patient safety. The HAI ontology (HAIO) groups over thousands of codes into a consistent hierarchy of concepts, along with relationships and axioms to capture knowledge on hospital-associated infections and complications with focus on the big four types, surgical site infections (SSIs), catheter-associated urinary tract infection (CAUTI); hospital-acquired pneumonia, and blood stream infection. By employing statistical inferencing in our study we use a set of heuristics to define the rule axioms to improve the SSI case detection. We also demonstrate how the occurrence of an SSI is identified using semantic e-triggers. The e-triggers will be used to improve our risk assessment of post-operative surgical site infections (SSIs) for patients undergoing certain type of surgeries (e.g., coronary artery bypass graft surgery (CABG)).

Original languageEnglish (US)
Article number23
Pages (from-to)1-12
Number of pages12
JournalJournal of Medical Systems
Volume40
Issue number1
DOIs
StatePublished - Jan 1 2016

Fingerprint

Surgical Wound Infection
Cross Infection
Cues
Semantics
Surgery
Ontology
Catheter-Related Infections
Quality of Health Care
Catheters
Patient Safety
Semantic Web
Grafts
Urinary Tract Infections
Coronary Artery Bypass
Risk assessment
Web services
Pneumonia
Patient Care
Blood
Guidelines

All Science Journal Classification (ASJC) codes

  • Medicine (miscellaneous)
  • Information Systems
  • Health Informatics
  • Health Information Management

Cite this

Shaban-Nejad, A., Mamiya, H., Riazanov, A., Forster, A. J., Baker, C. J. O., Tamblyn, R., & Buckeridge, D. L. (2016). From Cues to Nudge: A Knowledge-Based Framework for Surveillance of Healthcare-Associated Infections. Journal of Medical Systems, 40(1), 1-12. [23]. https://doi.org/10.1007/s10916-015-0364-6

From Cues to Nudge : A Knowledge-Based Framework for Surveillance of Healthcare-Associated Infections. / Shaban-Nejad, Arash; Mamiya, Hiroshi; Riazanov, Alexandre; Forster, Alan J.; Baker, Christopher J.O.; Tamblyn, Robyn; Buckeridge, David L.

In: Journal of Medical Systems, Vol. 40, No. 1, 23, 01.01.2016, p. 1-12.

Research output: Contribution to journalArticle

Shaban-Nejad, Arash ; Mamiya, Hiroshi ; Riazanov, Alexandre ; Forster, Alan J. ; Baker, Christopher J.O. ; Tamblyn, Robyn ; Buckeridge, David L. / From Cues to Nudge : A Knowledge-Based Framework for Surveillance of Healthcare-Associated Infections. In: Journal of Medical Systems. 2016 ; Vol. 40, No. 1. pp. 1-12.
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