This talk lays out an emerging research area in industrial engineering. Specifically, health care delivery and analysis can be classified under either quality or operations engineering. The World Health Organization (WHO) defines Health as “a state of complete physical, mental, and social well-being.” An open research question is whether a person’s health can be measured and quantified. If the answer is yes, can an unhealthy state be predicted before a disease strikes? A data collection method is first addressed for the data structure to be analyzed. Then an intelligent statistical process control (SPC) framework is proposed to solve the health status monitoring question. This proposed framework deviates significantly from the classic SPC Phase I and Phase II framework. An active data set based on a person’s numbers of steps and floors walked, sedentary, and activity levels is used as an example to demonstrate the proposed framework. Finally, this motivational example is extended to a much larger problem of predicting elderly fall risk.