With an aging population, rising costs and an increasing number of cancer cases, predicting the outcome of cancer care services is important for health care planning. Predictions can be based on computer models that take information from simple processes into larger systems. A model’s accuracy can be determined by comparing its predictions with real-world data and activity. As an MSFHR scholar, Dr. Chris Bajdik created a model to predict demand for hereditary cancer services in BC. He is now working to further develop prediction models for cancer care services. These new models will predict outcomes associated with cancer screening, treatment, supportive and palliative care. The predictions described through modeling will be compared with observed outcomes from provincial, national and international cancer care services. Dr. Bajdik’s approach provides a cost-effective way to predict outcomes – using the experience reflected in previously-collected data. Most importantly, these models will provide healthcare planners with a tool to predict the outcomes associated with new cancer care services and health policies. If the predictions are considered accurate, health care agencies can better plan and evaluate their services to care for those with cancer. The methods can be generalized to develop models for other forms of health care and other diseases.