Impacts of emergency department crowding : from identification to mitigation
Abstract/Contents
- Abstract
- This thesis explores three problems in the field of Healthcare Operations Management and Behavioral Healthcare Management in the setting of the emergency department (ED). We first study the problem of how to quantify and mitigate the delay imposed on high-acuity patients by low-acuity patients in the ED. We first provide evidence that the arrival of an additional low-acuity patient \textit{substantially} increases the wait time to start of treatment for high-acuity patients, contradicting the long-standing prior conclusion in the medical literature that the effect is ``\textit{negligible}." Whereas the medical literature underestimates the effect by neglecting how delay propagates in a queuing system. Then we construct and validate a new estimation method based on queuing theory, machine learning, and causal inference. Moreover, using wait time information displayed to low-acuity patients, we develop a quasi-randomized instrumental variable. We show that a low-acuity patient increases wait times for high-acuity patients through pre-triage delay; delay of lab tests ordered for high-acuity patients; and transition-delay when an ED interrupts treatment of a low-acuity patient in order to treat a high-acuity patient. Hence high-acuity patients' wait times could be reduced by: reducing the standard deviation or mean of those transition delays, particularly in bed-changeover; providing vertical or "fast track" treatment for more low-acuity patients, especially ESI 3 patients; standardizing providers' test-ordering for low-acuity patients; and designing wait time information systems to divert (especially when the ED is highly congested) low-acuity patients that do not need ED treatment. Second, we study the problem of how to provide wait time related information to improve patients' own waiting experience. In a field experiment that we run in an ED, we find that providing wait time information statistically improves patients' waiting satisfaction, statistically decreases the probability of patients leaving the ED without being seen by physicians (LWBS). For the former, patients' waiting satisfaction ratings are collected using an incentives text-based survey. For the latter, we use patients' electronic medical records to obtain their waiting behavior. We recommend EDs provide wait time related information as a relatively inexpensive method to improve patients waiting satisfaction and to decrease the probability of LWBS; both are important performance measures valued by EDs. Also, such finding provides insights on how to divert low-acuity patients who do not need ED treatment when ED is highly congested. Third, we study the problem of how ED congestion affects the number of diagnostic tests that physicians order for patients. We find that physicians are ordering fewer laboratory tests and radiology tests when ED is busy, i.e., ED's occupancy level is greater than 50% of the maximum patient census over the year. Leveraging a field experiment in an ED on wait time information provision, we establish the causal claim. We find that on average, when the ED is busy, physicians will order 3 less laboratory tests per patient, and 1 less radiology test per patient. We wish to further investigate the root causes for such behavior and to understand the implication of such behavior on patients' health outcomes, ED utilization efficiency and other related performance measures in the future.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2021; ©2021 |
| Publication date | 2021; 2021 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Luo, Danqi |
|---|---|
| Degree supervisor | Bayati, Mohsen |
| Degree supervisor | Plambeck, Erica L |
| Thesis advisor | Bayati, Mohsen |
| Thesis advisor | Plambeck, Erica L |
| Thesis advisor | Leider, Stephen |
| Degree committee member | Leider, Stephen |
| Associated with | Stanford University, Graduate School of Business |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Danqi Luo. |
|---|---|
| Note | Submitted to the Graduate School of Business. |
| Thesis | Thesis Ph.D. Stanford University 2021. |
| Location | https://purl.stanford.edu/th581vg5318 |
Access conditions
- Copyright
- © 2021 by Danqi Luo
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...