Clean data is critical for the accurate detection and diagnosis of public health risks

A researcher from the University of Wollongong’s School of Computing and Information Technology looked at data quality for public health information systems and identified a vital need for “high quality data and effective data quality assessment”.

Associate Professor Ping Yu’s research on data quality for public health information systems, published in 2014, conceptualises data quality assessment from three aspects: the quality of data, data use, and the data collection process.

The study noted there was limited research on the quality of the data collection process for public health information systems, in which data quality problems frequently occur.

“We have developed a four-dimensional (4D) framework for assessing the quality of the public health data process,” Professor Yu said.

“Using a four-dimensional (4D) framework will help the public health management identify the facilitators and address the barriers that affect the quality of the public health data collection process.”

The 4D Framework looks at data collection management, the data collection environment, data collection personnel, and data collection system.

The research team applied the 4D Framework to evaluate the quality of the HIV/AIDS data collection process in China and identified that Chinese AIDS information system has achieved better quality in data collection management “than that in the data collection environment and data collection system”.

“There were also areas for improvement, including engaging frontline staff in the design of data collection protocols, standardising quality assurance procedures, strengthening leadership, recognising data collector’s contributions, and meeting end-users’ needs for the system,” Professor Yu said.

“Leadership and acknowledgement of the contribution and efforts of our health workers should be top priority, not only in the context of their critical role during the public health HIV/AIDS prevention and control, but in other public health domains.

“If a large proportion of frontline data collectors such as clinicians, nurses and public health professionals become sick of the job with job fatigue, the ability to respond to public health emergencies such as the COVID-19 pandemic and HIV/AIDS epidemic would be compromised, ” she said.

“We believe that the 4D Framework can be an evaluation tool to guide international effort in the assessment of the quality of the public health data collection process.”