Is Expert Input Valuable? The Case of Predicting Surgery Duration

Most data-driven decision support tools do not include input from people. We study whether and how to incorporate physician input into such tools, in an empirical setting of predicting the surgery duration. Using data from a hospital, we evaluate and compare the performances of three families of models: models with physician forecasts, purely data-based models, and models that combine physician forecasts and data. We find that combined models perform the best, which suggests that physician forecasts have valuable information above and beyond what is captured by data. We also find that applying simple corrections to physician forecasts performs comparably well.