Under-Promising and Over-Delivering to Improve Patient Satisfaction at Emergency Departments: Evidence from a Field Experiment Providing Wait Information

33 Pages Posted: 24 Jun 2022

See all articles by Sina Ansari

Sina Ansari

DePaul University - Kellstadt Graduate School of Business

Laurens Debo

Dartmouth College - Tuck School of Business

Maria Ibanez

Northwestern University - Kellogg School of Management; Harvard University - Business School (HBS)

Seyed Iravani

Northwestern University - Department of Industrial Engineering and Management Sciences

Sanjeev Malik, M.D.

Northwestern University - Feinberg School of Medicine

Date Written: June 13, 2022

Abstract

Overcrowded Emergency Departments (EDs) across locations struggle to improve patient experience while dealing with long waits, which erodes medical and financial performance. We investigate whether and how managers could improve patient satisfaction by communicating waits to patients.

We conduct a field experiment at an urban ED. We develop a machine learning-based wait time prediction application and implement it within the electronic medical records system. Our treatments provide patients with personalized estimated waits with no overestimation (the median), moderate overestimation (70th-percentile), or high overestimation (90th-percentile).

Patients report higher satisfaction when receiving their estimated waits, but the effect vary widely depending on the announcement. Drawing on Prospect theory, we hypothesize that the announced wait acts as a reference point against which patients compare the actual wait and that patients are lossaverse (end effect): Waits longer than announced will lower satisfaction more than waits shorter than announced will increase satisfaction. Overestimating waits will then improve satisfaction. At the same time, however, rising the announced wait will reduce satisfaction initially and while waiting (initial effect), and this effect will dominate over the end effect for high levels of overestimation. Accordingly, we hypothesize and show that patients are more satisfied when they are told an estimate based on the 70 or 90th-percentiles, with the benefit being the largest for the 70thpercentile announcement. Wait estimates based on the median have a null effect.

Despite the benefits from wait announcements in settings where queues are unobservable, less is known about their effects in EDs, where queues are partially observable. With the Centers for Medicare & Medicaid Services tying reimbursements to patients’ ratings, our research suggests a cost-effective lever to improve patients’ satisfaction and hospitals’ financial performance: under-promising and over-delivering by providing moderately overestimated wait information.

Note:
Funding Information: None to declare.

Conflict of Interests: None to declare.

Ethical Approval: The research was declared 'not human research' by the IRB office.

Keywords: Wait, Patient Satisfaction, Emergency Department, ED, Prospect Theory, Healthcare

Suggested Citation

Ansari, Sina and Debo, Laurens and Ibanez, Maria and Iravani, Seyed and Malik, M.D., Sanjeev, Under-Promising and Over-Delivering to Improve Patient Satisfaction at Emergency Departments: Evidence from a Field Experiment Providing Wait Information (June 13, 2022). Tuck School of Business Working Paper No. 4135705, Available at SSRN: https://ssrn.com/abstract=4135705 or http://dx.doi.org/10.2139/ssrn.4135705

Sina Ansari

DePaul University - Kellstadt Graduate School of Business ( email )

1 E. Jackson Blvd.
Chicago, IL
United States

Laurens Debo

Dartmouth College - Tuck School of Business ( email )

Hanover, NH 03755
United States

Maria Ibanez (Contact Author)

Northwestern University - Kellogg School of Management ( email )

2001 Sheridan Road
Evanston, IL 60208
United States

HOME PAGE: http://www.kellogg.northwestern.edu/faculty/directory/ibanez_maria.aspx

Harvard University - Business School (HBS)

Soldiers Field Road
Morgan 270C
Boston, MA 02163
United States

Seyed Iravani

Northwestern University - Department of Industrial Engineering and Management Sciences ( email )

Evanston, IL 60208-3119
United States

Sanjeev Malik, M.D.

Northwestern University - Feinberg School of Medicine

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