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Knowledge exchange on healthcare big data analytics

Ongoing

Project description

Utilising existing healthcare databases has huge potential for improving healthcare services. However, research methods used in existing studies on analyzing healthcare databases for preventive services are limited to parametric methods and the availability of recent non-parametric methods including big-data analytics provide new opportunities for healthcare management researchers to understand diverse social and biographical factors that causes diseases through explorative approaches.

The objective of this project is to facilitate an inter-disciplinary research collaboration through knowledge exchange on the application of big-data analytics to the healthcare management between Brunel University London and Seoul National University (SNU).

More specifically, the collaboration will primarily focus on cancer survivorship and comprehensive community care based on the ongoing projects in each counterpart. SNU team have long been working on social and biological factors of diseases using healthcare databases in Republic of Korea.

On the other hand, having an MBA programme on Healthcare Management in its Business School, Brunel team have been working on healthcare management applying various data analytics methods including big data mining and process mining. Through the knowledge exchange collaboration, the SNU team is expected to have access to NHS data in the UK and innovative data analytics methods while the Brunel team to Healthcare Database in Republic of Korea as well as cases developed by SNU team to be used in their MBA and research group seminars.

For the sustainable collaboration between two parties, the proposed collaboration will develop a joint funding proposal that exploit innovative data analytics for healthcare management through the joint seminars. The specific objectives of the collaboration program include

  • to broaden knowledge of scientists of both parties including early stage researchers on non-parametric big data analytics methods for healthcare management through at least 10 joint seminars based on conference calls and two onsite symposia;
  • to secure access to healthcare related databases for partners in hosting countries as a part of knowledge exchange seminars; and
  • to ensure long-term collaboration by developing a joint funding proposal as the outcomes of the joint seminars.

The proposed collaboration is expected to make following scientific impacts. Firstly, it has methodological contribution in terms of Big data analytics on healthcare data. The development of electronic medical records and healthcare claim data warehouse requires new data mining approaches over traditional statistical approaches to incorporate multidimensional complex data and identifying patterns in sequential events during treatment. Due to limited ability to deal with a prior knowledge, popular approaches such as machine learning and Bayesian approaches cannot answer a causal question. Big data analytics approaches used on social sciences can provide an insight into how we can deliver meaningful results from healthcare big data.

Secondly, it has contribution to improving community care in terms of domain knowledge. Community-based care focusing on improving access and uptake of healthcare service to specific groups (e.g. ethnic minority, elderly, deprived) requires different approaches than interventions conducted in a hospital setting in terms of the nature of the study hypothesis, eligibility, compliance of the participants, etc.

Healthcare systems of the UK (National Health Service) and Korea (Korea National Health Insurance Services) shares common interests including expanding prevention services, improving the accessibility of care, and developing effective healthcare delivery setting. This collaboration will provide an opportunity to share experiences of each country and to develop new strategies for improving community-based care.