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Programme(s) to which this project applies: |
| ☑ MPhil/PhD | ☑ MRes[Med] | ☑ URIS |
About the Project
This project is supported by RGC-Research Impact Fund (R7707_22F) and focus on the use of healthcare big data and simulation modeling for chronic disease burden projection. The focused therapeutic areas are major depression disorder, inflammatory bowel disease and prostate cancer).
Policymakers and healthcare providers often face ever-expanding choices of products and services that are expected to meet the health needs of the population. Given the limited resources for healthcare and inelastic demand for effective treatments, there is a need to call for balance between cost and benefit. Health technology assessment (HTA) is useful to guide evidence-based decision making for resource prioritisation and formulary listing decisions, therefore, to maximise health equity. Horizon scanning, as an essential tool for HTA, actively and systematically identify novel interventions that impacts and brings about paradigm shifts.
Objectives
(1) To assess the local current disease burden, medication utilisation pattern, unmet needs of innovative medicines and economic burden in three selected chronic diseases (depression, inflammatory bowel disease, prostate cancer) by utilising real-world data;
(2) To project the local population-specific 10-year disease burden and care using disease simulation modelling;
(3) To evaluate the cost-effectiveness, return-on-investment and budget impact of innovative medicine versus standard care, using decision-analytic modelling.
Significance
The findings will help locate service gaps and enable pre-emptive healthcare resource planning to appropriate areas to improve patient care. Results from economic evaluation will also hint whether reimbursing high-priced innovative medicines will be cost-effective and yield positive gain from the investment for the Hong Kong public health ecosystem.
Research Plan and Methodology
The student(s) will develop protocols and accomplish this research project under supervision and deliver:
(1) Epidemiological studies based on territory-wide population-based electronic medical records (real-world evidence) to understand local care needs;
(2) Disease simulation modelling studies for burden estimation and economic evaluation of treatments based on real-world evidence projection.
Students with backgrounds in epidemiology, health economics and policy, biostatistics, and/or clinical knowledge, or other relevant disciplines are desirable and welcomed. However, essential training will also be provided for research methodology, biostatistics, programming, data collection and results interpretation.
About the Supervisor
Professor SX Li, Department of Medicine
With over 10 years of experience in real-world and outcome research (HEOR) and decision analytics, I am currently working as an Assistant Professor at HKUMed. My research passion lies in bridging real-world evidence, disease simulation modelling and decision analytics for transparent and evidence-based health policymaking for cutting-edge innovative medicine (e.g. biologics, precision medicine, vaccine) and healthcare interventions (e.g. AI tools for screening and clinical decision assistance).
My research often involves dynamic interactions with local and international academic collaborators, local government, industry partners, NGOs and other key opinion leaders. As the principal investigator of several HEOR projects funded by the Hong Kong government, I have led research projects covering the therapeutic areas of mental health, cardiovascular diseases, autoimmune diseases, oncology, rare genetic disorders and vaccinology, and published in world-leading medical journals such as Annals of Internal Medicine, JAMA Pediatrics, Annals of the Rheumatic Disease, eClinicalMedicine and Lancet Regional Health Western Pacific. I have co-authored ~120 peer-reviewed articles (total citation ~2800; H-index 28 as of Feb 2024) and have been selected as the Top 2% most cited scientists by Stanford University. As a Project Coordinator, I also lead the first Horizon Scanning project funded by the RGC Research Impact Fund to launch the HEOR training and root the Health Technology Assessment ecosystem for early innovative adoption in Hong Kong and the Greater Bay Area.
My current team (Xue’s lab) includes 12 full-time Postdoc/PhD/MPhil students and research fellows. With a team spirit of Proactive – Empathy – Resilience – Teamwork, and Self-motivation (X-PERTS), we embrace and enjoy the open research environment, international collaboration, and breakthrough methodologies in health science. Please email sxueli@hku.hk for full-time or part-time Postdoc/PhD/MPhil/RA opportunities.
Next Step?
For more information or to express interest for this project, please email the supervisor or the specified contact point in the project description. Interested candidates are advised to enclose with your email:
- your CV,
- a brief description of your research interest and experience, and
- two reference letters (not required for HKUMed UG students seeking MRes[Med]/URIS projects).
Information on the research programme, funding support and admission documentations could be referenced online at the Research Postgraduate Admissions website. General admission enquiries should be directed to rpgmed@hku.hk.
HKUMed MBBS students interested in the Master of Research in Medicine (MRes[Med]) programme may visit the programme website for more information.
HKUMed UG students interested in the Undergraduate Research Internship Scheme (URIS) may visit the scheme’s website for more information.
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