WMSS: A Web-Based Multitiered Surveillance System for Predicting CLABSI.
Central-line-associated bloodstream infection (CLABSI) rates are a key quality metric for comparing hospital quality and safety. Manual surveillance systems for CLABSIs are time-consuming and often limited to intensive care units (ICUs). A computer-automated method of CLABSI detection can improve th...
| Published in: | BioMed Research International Vol. 2018; pp. 1 - 12 |
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| Main Authors: | , , , , , |
| Format: | algorithm pictorial research tables/charts Journal Article |
| Published: |
Wiley-Blackwell
7/5/2018
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=130506042&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 130506042 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 7/5/2018 vid: 2018 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 130506042 130506042 130506042 10.1155/2018/5419313 130506042 ppf: 1 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: WMSS: A Web-Based Multitiered Surveillance System for Predicting CLABSI. aug: au: Noaman, Amin Y. Ragab, Abdul Hamid M. Al-Abdullah, Nabeela Jamjoom, Arwa Nadeem, Farrukh Ali, Anser G. affil: Department of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia sug: subj: Catheter-Related Bloodstream Infections Diagnosis Catheter-Related Bloodstream Infections Prevention and Control Disease Surveillance World Wide Web Diagnosis, Computer Assisted Human Algorithms Medical Records Health Care Costs Information Technology Smartphone Computers, Portable Internet Scanners Databases, Health Multimedia Decision Making, Clinical Health Policy Clinical Competence ab: Central-line-associated bloodstream infection (CLABSI) rates are a key quality metric for comparing hospital quality and safety. Manual surveillance systems for CLABSIs are time-consuming and often limited to intensive care units (ICUs). A computer-automated method of CLABSI detection can improve the validity of surveillance. A new web-based, multitiered surveillance system for predicting and reducing CLABSI is proposed. The system has the capability to collect patient-related data from hospital databases and hence predict the patient infection automatically based on knowledge discovery rules and CLABSI decision standard algorithms. In addition, the system has a built-in simulator for generating patients’ data records, when needed, offering the capability to train nurses and medical staff for enhancing their qualifications. Applying the proposed system, both CLABSI rates and patient treatment costs can be reduced significantly. The system has many benefits, among which there is the following: it is a web-based system that can collect real patients’ data from many IT resources using iPhone, iPad, laptops, Internet, scanners, and hospital databases. These facilities help to collect patients’ actual data quickly and safely in electronic format and hence predict CLABSI efficiently. Automation of the patients’ data diagnosis process helps in reducing CLABSI detection times. The system is multimedia-based; it uses text, colors, and graphics to enhance patient healthcare report generation and charts. It helps healthcare decision makers to review and approve policies and surveillance plans to reduce and prevent CLABSI. pubtype: Academic Journal doctype: algorithm pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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