Language:

Audit of the Sydney Local Health District Public Health Unit notification and contact tracing system during the first wave of COVID‐19

Australian and New Zealand Journal of Public Health, 2021-10, Vol.45 (5), p.526-530 [Peer Reviewed Journal]

2021 Copyright 2021 THE AUTHORS. ;2021 The Authors ;2021 The Authors. ;COPYRIGHT 2021 John Wiley & Sons, Inc. ;2021. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2021. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1326-0200 ;EISSN: 1753-6405 ;DOI: 10.1111/1753-6405.13145 ;PMID: 34473383

Digital Resources/Online E-Resources

Citations Cited by

Actions
1. Add to My Research
2. Remove from My Research
3. E-mail
4. Print
5. Permalink
6. Citation
7. EasyBib
8. EndNote
9. RefWorks
10. Delicious
11. Export RIS
12. Export BibTeX

Title:
Audit of the Sydney Local Health District Public Health Unit notification and contact tracing system during the first wave of COVID‐19
Author: Jain, Naveena ; Moore, Corey B. ; Quinn, Emma ; Liu, Huei Ming ; Liu, Darith ; Heaton, Maria ; Gehlot, Priyanka ; Dhakal, Yashoda ; Gupta, Leena ; Hogbin, Rebecca ; Eastwood, John G.
Subjects: Accuracy ; Administrative agencies ; audit ; Audits ; Australia - epidemiology ; Contact Tracing ; continuous quality improvement ; Coronaviruses ; COVID-19 ; COVID-19 - diagnosis ; COVID-19 - epidemiology ; Data Accuracy ; Data base management systems ; Data quality ; Disease transmission ; Electronic data processing ; Epidemiology ; Evaluation ; Humans ; Infections ; Information management ; Intervention ; Interviews ; Laboratories ; Management Audit ; Management Information Systems ; Mortality ; Public Health ; public health unit ; Quality assessment ; Quality control ; Quality Improvement ; Regression analysis ; Regression models ; Severe acute respiratory syndrome coronavirus 2 ; Surveillance ; Teams ; Time ; Total quality ; Training ; Variables ; Workload ; Workloads
Is Part Of: Australian and New Zealand Journal of Public Health, 2021-10, Vol.45 (5), p.526-530
Description: To conduct a real‐time audit to assess a Continuous Quality Improvement (CQI) activity to improve the quality of public health data in the Sydney Local Health District (SLHD) Public Health Unit during the first wave of COVID‐19. A real‐time audit of the Notifiable Conditions Information Management System was conducted for positive cases of COVID‐19 and their close contacts from SLHD. After recording missing and inaccurate data, the audit team then corrected the data. Multivariable regression models were used to look for associations with workload and time. A total of 293 cases were audited. Variables measuring completeness were associated with improvement over time (p<0.0001), whereas those measuring accuracy reduced with increased workload (p=0.0003). In addition, the audit team achieved 100% data quality by correcting data. Utilising a team, separate from operational staff, to conduct a real‐time audit of data quality is an efficient and effective way of improving epidemiological data. Implementation of CQI in a public health unit can improve data quality during times of stress. Auditing teams can also act as an intervention in their own right to achieve high‐quality data at minimal cost. Together, this can result in timely and high‐quality public health data.
Publisher: United States: Elsevier B.V
Language: English
Identifier: ISSN: 1326-0200
EISSN: 1753-6405
DOI: 10.1111/1753-6405.13145
PMID: 34473383
Source: Coronavirus Research Database

Back to results list


INSPIRE LIBRARY - TON DUC THANG UNIVERSITY	(84-028) 37 755 057	Feedback
19 Nguyen Huu Tho St. Dist.7, HCM	thuvien@tdtu.edu.vn	Feedback

Audit of the Sydney Local Health District Public Health Unit notification and contact tracing system during the first wave of COVID‐19

Searching Remote Databases, Please Wait