Development and validation of HBV surveillance models using big data and machine learning.

BACKGROUND: The construction of a robust healthcare information system is fundamental to enhancing countries' capabilities in the surveillance and control of hepatitis B virus (HBV). Making use of China's rapidly expanding primary healthcare system, this innovative approach using big data and machine learning (ML) could help towards the World Health Organization's (WHO) HBV infection elimination goals of reaching 90% diagnosis and treatment rates by 2030. We aimed to develop and validate HBV detection models using routine clinical data to improve the detection of HBV and support the development of effective interventions to mitigate the impact of this disease in China. METHODS: Relevant data records extracted from the Family Medicine Clinic of the University of Hong Kong-Shenzhen Hospital's Hospital Information System were structuralized using state-of-the-art Natural Language Processing techniques. Several ML models have been used to develop HBV risk assessment models. The performance of the ML model was then interpreted using the Shapley value (SHAP) and validated using cohort data randomly divided at a ratio of 2:1 using a five-fold cross-validation framework. RESULTS: The patterns of physical complaints of patients with and without HBV infection were identified by processing 158,988 clinic attendance records. After removing cases without any clinical parameters from the derivation sample (n = 105,992), 27,392 cases were analysed using six modelling methods. A simplified model for HBV using patients' physical complaints and parameters was developed with good discrimination (AUC = 0.78) and calibration (goodness of fit test p-value >0.05). CONCLUSIONS: Suspected case detection models of HBV, showing potential for clinical deployment, have been developed to improve HBV surveillance in primary care setting in China. (Word count: 264).

This study has developed a suspected case detection model for HBV, which can facilitate early identification and treatment of HBV in the primary care setting in China, contributing towards the achievement of WHO's elimination goals of HBV infections.We utilized the state-of-art natural language processing techniques to structure the data records, leading to the development of a robust healthcare information system which enhances the surveillance and control of HBV in China.

Global impacts of COVID-19 pandemic on sexual and reproductive health services: An international comparative study on primary care from the INTRePID Consortium.

OBJECTIVE: To understand how the COVID-19 pandemic has impacted sexual and reproductive health (SRH) visits. DESIGN: An ecological study comparing SRH services volume in different countries before and after the onset of the COVID-19 pandemic. SETTING: Seven countries from the INTernational ConsoRtium of Primary Care BIg Data Researchers (INTRePID) across four continents. POPULATION: Over 3.8 million SRH visits to primary care physicians in Australia, China, Canada, Norway, Singapore, Sweden and the USA. METHODS: Difference in average SRH monthly visits before and during the pandemic, with negative binomial regression modelling to compare predicted and observed number of visits during the pandemic for SRH visits. MAIN OUTCOME MEASURES: Monthly number of visits to primary care physicians from 2018 to 2021. RESULTS: During the pandemic, the average volume of monthly SRH visits increased in Canada (15.6%, 99% CI 8.1-23.0%) where virtual care was pronounced. China, Singapore, Sweden and the USA experienced a decline (-56.5%, 99% CI -74.5 to -38.5%; -22.7%, 99% CI -38.8 to -6.5%; -19.4%, 99% CI -28.3 to -10.6%; and -22.7%, 99% CI -38.8 to -6.5%, respectively); while Australia and Norway showed insignificant changes (6.5%, 99% CI -0.7 to -13.8% and 1.7%, 99% CI -6.4 to -9.8%). The countries that maintained (Australia, Norway) or surpassed (Canada) pre-pandemic visit rates had the greatest use of virtual care. CONCLUSIONS: In-person SRH visits to primary care decreased during the pandemic. Virtual care seemed to counterbalance that decline. Although cervical cancer screening appeared insensitive to virtual care, strategies such as incorporating self-collected samples for HPV testing may provide a solution in a future pandemic.