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| Main Authors: | , , |
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| Format: | Preprint |
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2026
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| Online Access: | https://arxiv.org/abs/2605.24208 |
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| _version_ | 1866914594301149184 |
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| author | Hathaway, Brett Kagan, Evgeny Jones, John |
| author_facet | Hathaway, Brett Kagan, Evgeny Jones, John |
| contents | Emergency departments (EDs) often use a shared-queue setup in which physicians self-assign cases from a pool of triaged patients. We conduct a multi-method study to examine this self-assignment behavior and its effects on system performance. Using data from five EDs spanning 1.4 million patient visits, we show that batching, i.e., self-assigning multiple patients at once, is common and associated with longer stays for batched patients, even after controlling for clinical acuity, physician fixed effects, and ED congestion. We then develop a continuous-time queueing model that characterizes the optimal self-assignment policy under individual and group throughput incentives. We use the model predictions to test experimentally with 203 healthcare workers and 73 ED physicians whether batching is a rational response to incentives or a deeper behavioral tendency that persists independent of incentives. Indeed, batching is pervasive across both samples, with 94% of healthcare workers and 73% of physicians choosing to batch even when it reduces their own payoffs -- a behavior that we term the personal productivity bias. Together, these results suggest that compensation redesign alone is unlikely to eliminate batching, and suggest changes to the assignment interface in the electronic health record system as a more promising remedy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_24208 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | One at a Time? The Personal Productivity Bias in Emergency Department Patient Assignment Hathaway, Brett Kagan, Evgeny Jones, John General Economics Economics Emergency departments (EDs) often use a shared-queue setup in which physicians self-assign cases from a pool of triaged patients. We conduct a multi-method study to examine this self-assignment behavior and its effects on system performance. Using data from five EDs spanning 1.4 million patient visits, we show that batching, i.e., self-assigning multiple patients at once, is common and associated with longer stays for batched patients, even after controlling for clinical acuity, physician fixed effects, and ED congestion. We then develop a continuous-time queueing model that characterizes the optimal self-assignment policy under individual and group throughput incentives. We use the model predictions to test experimentally with 203 healthcare workers and 73 ED physicians whether batching is a rational response to incentives or a deeper behavioral tendency that persists independent of incentives. Indeed, batching is pervasive across both samples, with 94% of healthcare workers and 73% of physicians choosing to batch even when it reduces their own payoffs -- a behavior that we term the personal productivity bias. Together, these results suggest that compensation redesign alone is unlikely to eliminate batching, and suggest changes to the assignment interface in the electronic health record system as a more promising remedy. |
| title | One at a Time? The Personal Productivity Bias in Emergency Department Patient Assignment |
| topic | General Economics Economics |
| url | https://arxiv.org/abs/2605.24208 |