Page 85 - Hospital Authority Convention 2017

Symposiums

S4.1 Clinical Application of Big Data 16:15 Convention Hall C

How Could Big Data Improve Quality of Healthcare
Saria S
Department of Computer Science, Johns Hopkins University, USA HOSPITAL AUTHORITY CONVENTION 2017
The widespread adoption of electronic health data, wearables, and high throughput measurement technologies are leading
to explosion of datasets that measure – in a granular way – progression of disease and changes in health over time. The
challenge lies in developing technologies and delivery processes that can effectively leverage this data to enable efficient and
accurate decision making. Sepsis is the 11th leading cause of death. In this talk, I will do a deep dive in our work in reducing
this and other preventable harms in the hospital setting; I will also discuss applications of these ideas in managing patients
with complex, chronic diseases.

S4.2 Clinical Applications of Big Data 16:15 Convention Hall C Tuesday, 16 May

Biostatistics Approach to Big Data in Medical Device Development – Automatic Retinal Image Analysis as an
Example
Zee B, Lee J, Chong M, Wang M, Kwok C, Lai M
Division of Biostatistics, The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong
Kong

Advances in science and technology will bring many new treatments and diagnostics to the healthcare world. It is equally
important to extend the innovation and technology advancements for disease prevention, health promotion, and health
systems for prolonging life and improving quality of life in the general population. However, the healthcare demands of the
public and the costs to achieve high standard from the healthcare providers are continuously increasing. Effective methods
for disease prevention and monitoring would save lives and improve quality of life, reduce the risk of developing serious
conditions or complications, and if appropriately utilise, it would reduce healthcare expenditure. Innovative approaches to
health information management and in particular innovative disease monitoring techniques are therefore important to ensure
that our healthcare services are affordable, accessible, and available both in the hospital and in the community.
In this presentation, we will discuss new biostatistics approaches and research on developments using: (1) cloud and
internet computing; (2) mobile health management; (3) machine learning and predictive analytic methods; and (4) automation
approach for potential applications that contribute to solving part of the public health problems. We would discuss our own
projects, including some of the older projects that were not as successful due to various reasons, and also the “Automatic
Retinal Image Analysis (ARIA)” method for stroke risk assessment, early dementia and other vascular related indications as
a relatively more successful example. The aim of this presentation is to foster communication for more fruitful collaboration
between healthcare professionals and biostatisticians.

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