My research interest include

• Economic evaluation of health interventions
• Cost-effectiveness analysis
• Cost of illness studies
• Health technology assessment
• Applied econometrics in health

Dr Son Nghiem has more than 10-year experience in applied econometrics and health economics research. Dr Nghiem has developed a strong track record with over 100 peer-reviewed papers published in high-impact journals in health economics, public health and health services research. He has been awarded over $1,500,000 in research grants and fellowship. One of his most impacted studies is the development of the Classification of Hospital Acquired Diagnoses (CHADx) to improve the safety of patients. The CHADx is now integrated into the Hospital-Acquired Complications by the Australian Commission on Safety and Quality in Health Care. Dr Nghiem has also developed a predictive model to estimate a risk score for trauma admissions using a machine learning approach. Recently, he led a study to predict the risk of frailty for older patients using the longitudinal study of cardiovascular admissions in Queensland. He is conducting various research projects on cardiovascular disease, including the development of a disease progression model for heart attack using a multi-state hidden Markov model and estimation of a hospital frailty risk score and assesses its ability to predict adverse health outcomes in Australia.

Dr Nghiem joined ANU College of Health and Medicine since Aprill 2022. He will be responsible for leading the economic evaluation of the the AusPathoGen project. He will also coordinate and deliver lecture for the POPH8103 course.

1. Inequalities in health service utilisation, morbidity and mortality of cardiovascular disease in Queensland adults: a longitudinal cohort study 
2. Individualised heat-health early warning systems: A novel digital solution
3. Sri Lanka Pandemic Preparedness Assessment ASA: Fiscal space for pandemic preparedness and routine health care delivery for a rapidly aging population
4. Point of care subepidermal moisture scanning technology: A novel approach to detect early pressure injury change
5. Real-world Validation of Deep Learning Algorithm ROP.AI for the Automated Diagnosis of Retinopathy of Prematurity

The compliance with Electronic Therapeutic Guidelines (eTG) and health outcomes in the management of heart failure across Queensland