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Aust N Z J Public Health ; 45(5): 526-530, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1388133

ABSTRACT

OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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. Implications for public health: 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.


Subject(s)
COVID-19/diagnosis , Contact Tracing , Management Audit , Quality Improvement , Australia/epidemiology , COVID-19/epidemiology , Data Accuracy , Humans , Management Information Systems , Public Health , Workload
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