Is Expert Input Valuable? The Case of Predicting Surgery Duration

Abstract

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. [ABSTRACT FROM AUTHOR] Copyright of Seoul Journal of Business is the property of Seoul National University, College of Business Administration and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)