Low-Acuity Patients Delay High-Acuity Patients in the Emergency Department

44 Pages Posted: 5 Jan 2018 Last revised: 14 Jan 2021

See all articles by Danqi Luo

Danqi Luo

Stanford Graduate School of Business

Mohsen Bayati

Stanford Graduate School of Business

Erica L. Plambeck

Stanford Graduate School of Business

Michael Aratow

affiliation not provided to SSRN

Date Written: December 31, 2017

Abstract

This paper provides evidence that the arrival of an additional low-acuity patient 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 ``negligible". Whereas the medical literature underestimates the effect by neglecting how delay propagates in a queuing system, this paper develops and validates a new estimation method based on queuing theory, machine learning and causal inference. Wait time information displayed to low-acuity patients provides a quasi-randomized instrumental variable. This paper shows 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.

Keywords: Health Care Management, Causal Inference, Empirical Research, Queueing Theory, Randomized Experiments

Suggested Citation

Luo, Danqi and Bayati, Mohsen and Plambeck, Erica L. and Aratow, Michael, Low-Acuity Patients Delay High-Acuity Patients in the Emergency Department (December 31, 2017). Available at SSRN: https://ssrn.com/abstract=3095039 or http://dx.doi.org/10.2139/ssrn.3095039

Danqi Luo

Stanford Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States

Mohsen Bayati (Contact Author)

Stanford Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States

HOME PAGE: http://web.stanford.edu/~bayati/

Erica L. Plambeck

Stanford Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States

Michael Aratow

affiliation not provided to SSRN

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