Song-Hee, K;
Rouba, I;
(2019)
Is Expert Input Valuable? The Case of Predicting Surgery Duration.
Seoul Journal of Business
, 25
(2)
pp. 1-34.
10.35152/snusjb.2019.25.2.001.
Preview |
Text
SJB_Ibrahim and Kim_Vol25_2_001.pdf - Accepted Version Download (964kB) | Preview |
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.
| Type: | Article |
|---|---|
| Title: | Is Expert Input Valuable? The Case of Predicting Surgery Duration |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.35152/snusjb.2019.25.2.001 |
| Publisher version: | https://doi.org/10.35152/snusjb.2019.25.2.001 |
| Language: | English |
| Additional information: | © 2019 NRF. This is an Open Access article published under the terms of the Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) license (https://creativecommons.org/licenses/by-nc/3.0/). |
| Keywords: | healthcare operations, operating room, predicting surgery duration, expert input, discretion |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > UCL School of Management |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10119198 |
Archive Staff Only
 |
View Item |
