Studying Disease Progression and Complication Development in Diabetes, Hypertension and Hyperlipidemia (DHL) patients
Main Applicant – Clinical Associate Professor Tan Ngiap Chuan
SingHealth Polyclinics

This project aims to develop tools that help primary care teams stop or slow disease progression and complication development in Diabetes, Hypertension and Hyperlipidemia (DHL) patients by 20% in 5 years.

SingHealth Polyclinics (SHP) has a dataset containing extensive information about patients with DHL who have visited SHP. This study will be linking the SHP dataset with available TRUST’s data of the identified SHP cohort. This will provide additional information of the SHP cohort thus providing a better understanding of the patient journey with information such as diagnosis, medication and laboratory results from other clusters/settings.

With the dataset from TRUST, the research team will be looking at:

• validating of the existing models developed using SingHealth dataset
• refining the developed models with the bigger dataset
• developing new models based on new variables made available from TRUST
• health outcomes such as hospitalization, morbidity (CAD, CVA, CRF, Cancer risks due to selected medications) and mortality as an integral component to enhance the CVD risk prediction model and treatment goals