Consumer Health Informatics for Personalized Treatment Decisions

Researchers: Fangzhou (Luna) Xie, Yangyuechen (Fiona) Zhao

With the growing emphasis on personalized healthcare, this project develops a decision support system (DSS) that facilitates collaboration among clinicians and patients when selecting medical treatments. The DSS addresses the complex balance between the treatment benefits and risks, which include their probabilities and magnitudes. Increasingly, these parameters are known and often their values can be customized based on the patient’s characteristics such as age and family history. However, it is difficult for a patient to make decisions in the context of uncertainty.

The types of treatments under consideration will tend to have specific benefits that are the main focus of attention, but these benefits can be uncertain. The risks of many treatments include potential side effects or long-term impacts. Examples include prostate cancer treatment (surgery versus hormone therapy/radiation), knee replacement (surgery versus physical therapy), vision correction (laser eye surgery versus eyeglasses), and high cholesterol (paramedical versus lifestyle change). The DSS will use visualizations to simplify patients’ decisions.