Data-Drive Training

Data-Driven Training for Health Care Professionals

ATC’s processes seek out performance data on which to base sound decisions about the curriculum; we analyze this data to help our clients establish training standards for each successive phase of their training. This methodical approach compares well with the ad hoc, probabilistic training approach commonly used in training health care professionals (the Halsted model*).

In these graphs, the box-and-whisker plots show the statistical distribution of surgical performance. Performance was measured in terms of physical damage to the retina and light toxicity, as both were induced by the participant. The retina damage index shown below combines the two, and is based on two attempts and two possible modes of iatrogenic injury. It becomes clear from the following graphs that the trainee’s first attempt to perform this kind of high risk surgery should not involve an actual patient. It also becomes clear that decreasing training standards could be successfully applied to successive phases of training to ensure that before the first actual surgery, the trainee’s performance on a simulator has significantly reduced the risk and improved surgical efficiency in the operating room.

The net result of the Systems Approach is to drive trainee performance up a predetermined curve while simultaneously reducing the risk to the live patient, as the following notional graphs illustrate. ATC is eager to help you bring this kind of systematic, methodical and data-driven training to your health care profession.

*William Stewart Halsted (1852-1922), usually credited with starting the first formal surgical apprenticeship training program in the United States