Research Projects
Horizon Scanning of medium- to long-term burden of depression and care needs in Hong Kong (SCAN-2030)


Programme(s) to which this project applies:

☑ MPhil/PhD ☒ MRes[Med] ☑ URIS

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.

Dr SX Li, Department of Medicine

Dr Li’s primary research interests lie in health technology assessment (HTA), health economics and real-world outcome (HEOR) research using decision analytic models and routine health data (healthcare big data). Dr Li has expertise in healthcare data analytics, cost-effectiveness assessment for healthcare interventions, and health service and policy research. Since joining HKU, Dr Li has led and contributed to many HEOR projects, all of which involves dynamic interactions with local and international academic collaborators, local government, industry partners, NGOs and other key opinion leaders.

Dr Li’s recent research focuses on biologics utilization and safety, the regional economic burden and cost-effective solutions for autoimmune diseases, and the development of outcome-based risk-sharing model for innovative and curative therapies. As a core member of CARE Programme (COVID-19 Vaccines Adverse Events Response and Evaluation Programme), Dr Li has led and contributed to several territory-wide, population-based vaccine safety assessment, particularly for patients with immunological conditions. Dr Li also acts as a Co-principal investigator of AI and Pharmaceuticals in Non-Communicable Diseases at the Laboratory of Data Discovery for Health (D²4H).

Dr Li’s research work has been supported by RGC/Early Career Scheme (PI), RGC/Research Impact Fund (PC), RGC/Collaborative Research Fund (co-PI), Health and Medical Research Fund of the Food and Health Bureau of Hong Kong SAR Government (PI). Dr Li has published actively in the field of HTA and health policy. She has co-authored more than 140 research articles in top-tier specialty journals including Lancet, JAMA, BMJ and Nature families.

Biography
HKU Scholars Hub
Lab
ORCID
sxueli@hku.hk

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:

  1. your CV,
  2. a brief description of your research interest and experience, and
  3. 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.