Real-Time Automated Hazard Detection Framework for Health Information Technology Systems. Issue 3 (2nd September 2019)
- Record Type:
- Journal Article
- Title:
- Real-Time Automated Hazard Detection Framework for Health Information Technology Systems. Issue 3 (2nd September 2019)
- Main Title:
- Real-Time Automated Hazard Detection Framework for Health Information Technology Systems
- Authors:
- Omitaomu, Olufemi A.
Ozmen, Ozgur
Olama, Mohammed M.
Pullum, Laura L.
Kuruganti, Teja
Nutaro, James
Klasky, Hilda B.
Zandi, Helia
Advani, Aneel
Laurio, Angela L.
Ward, Merry
Scott, Jeanie
Nebeker, Jonathan R. - Abstract:
- ABSTRACT: An increase in the reliability of Health Information Technology (HIT) will facilitate institutional trust and credibility of the systems. In this paper, we present an end-to-end framework for improving the reliability and performance of HIT systems. Specifically, we describe the system model, present some of the methods that drive the model, and discuss an initial implementation of two of the proposed methods using data from the Veterans Affairs HIT and Corporate Data Warehouse systems. The contributions of this paper, thus, include (1) the design of a system model for monitoring and detecting hazards in HIT systems, (2) a data-driven approach for analysing the health care data warehouse, (3) analytical methods for characterising and analysing failures in HIT systems, and (4) a tool architecture for generating and reporting hazards in HIT systems. Our goal is to work towards an automated system that will help identify opportunities for improvements in HIT systems.
- Is Part Of:
- Health systems. Volume 8:Issue 3(2019)
- Journal:
- Health systems
- Issue:
- Volume 8:Issue 3(2019)
- Issue Display:
- Volume 8, Issue 3 (2019)
- Year:
- 2019
- Volume:
- 8
- Issue:
- 3
- Issue Sort Value:
- 2019-0008-0003-0000
- Page Start:
- 190
- Page End:
- 202
- Publication Date:
- 2019-09-02
- Subjects:
- Health information technology -- hazard detection -- statistical process control -- Markov chain -- transaction process model -- corporate data warehouse
610.285 - Journal URLs:
- http://link.springer.com/ ↗
http://www.theorsociety.com/Pages/Publications/HS.aspx ↗ - DOI:
- 10.1080/20476965.2019.1599701 ↗
- Languages:
- English
- ISSNs:
- 2047-6965
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12282.xml