We are privileged for being one of the pioneer projects of the HA Data Collaboration Lab (HADCL), where we have dedicated our efforts to developing innovative machine learning (ML) models for predicting the risk of hepatocellular carcinoma (HCC), one of the most fatal complications of chronic viral hepatitis. Accurate HCC risk prediction plays a crucial role in tailoring surveillance strategies and ultimately reducing cancer-related mortality. Our team has utilised the remarkable real-world dataset from HA to conduct a comprehensive territory-wide study in Hong Kong spanning from 2000 to 2018. This study was based on detailed clinical data, including viral markers, diagnosis codes, and antiviral treatment for chronic viral hepatitis. We rigorously evaluated five cutting-edge ML methods - logistic regression, ridge regression, AdaBoost, decision tree, and random forest - to identify the most effective prediction model. With a dataset comprising 124,006 patients with chronic viral hepatitis and complete information, we embarked on constructing these models. Ridge regression led to consistently good performance in both training and validation cohorts. The low threshold (0.07) of the HCC ridge score (HCC-RS) achieved an impressive 90.0% sensitivity and 98.6% negative predictive value (NPV) in the validation cohort. Alternatively, the high threshold (0.15) of the HCC-RS demonstrated exceptional specificity (90.0%) and NPV (95.6%), leaving only 31.1% of patients in the indeterminate category. In conclusion, the HCC-RS derived from the ridge regression machine-learning model exhibits remarkable accuracy in predicting HCC in patients with chronic viral hepatitis. These ML models could potentially be integrated as essential tools or calculators in electronic health systems to help mitigate cancer-related mortality. 

Hip fractures are associated with significant morbidity and mortality, posing a major health challenge in aging populations such as Hong Kong. Accurate and timely detection is critical to saving lives and preserving patient independence. Despite advancements in medical imaging, X-rays remain the primary diagnostic tool for evaluating hip fractures. However, misdiagnosis rates can reach up to 10%, leading to delays in treatment. The emergence of artificial intelligence (AI) offers a promising solution, with advanced algorithms such as convolutional neural networks (CNNs) demonstrating potential in improving fracture detection. Here, we share our experience of a collaboration between local academic institutions and the Hospital Authority Data Collaboration Laboratory (HADCL) in developing an AI model for hip fracture detection on pelvic X-rays. We detail its integration into the Hospital Authority's Clinical Management System (CMS) and subsequent territory-wide deployment, exploring how this tool supports frontline clinicians and enhances patient care.

EH Plus Digital Technology Limited, a Hong Kong Hospital Authority spin-off, envisages transformative healthcare through digital innovation. EHP's Product and Services Portfolio spans three significant domains (i) Healthcare Information Technology (HCIT) Solutions, (ii) Data as a Service (focusing on leveraging, cultivating, and broadening the existing HA Data Collaboration Lab), and (iii) Healthcare and Technology Consulting Services. This diverse approach allows EHP to address a variety of challenges in today's healthcare landscape.
Harnessing an esteemed academic foundation and three decades of comprehensive data from the Hospital Authority, EHP aims to revamp Hong Kong into a premier hub for clinical data research. This initiative is designed to fuel revolutionary healthcare advancements and innovations.
Apart from the complete and high quality HA data sets contributed unparalleled value to HA's Research, EHP, by leveraging HAIT&HI significant experience, is developing five generations of hospital IT solutions (namely CMS, HAGO, Smart hospital, and AI) in the past 30 years. The solutions have been co-delivered by clinicians, health informatics, and IT engineers.
With recent HIMSS 7 accreditation for all the HA servig hospitals, EHS has expert advisors with 30 years of Digital Healthcare Strategy and experience including IT, EMR S, AI and Data, Digital Workspace, and IT resource.