Rationing by Waiting, Information Frictions, and Patient Behavior

Last registered on September 28, 2026
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Pre-Trial

Trial Information

General Information

Title
Rationing by Waiting, Information Frictions, and Patient Behavior
RCT ID
AEARCTR-0019451
Initial registration date
September 26, 2026

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
September 28, 2026, 9:57 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

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Primary Investigator

Name
Catalina Gomez Colomer
Affiliation
Columbia University
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Other Primary Investigator(s)

PI Name
Ricardo Pommer Muñoz
PI Affiliation
Analysis Group
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Additional Trial Information

Status
In development
Start date
2026-12-01
End date
2028-01-01
Keywords
Behavior, Health
Additional Keywords
rationing by waiting, information frictions
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Public health systems ration surgical capacity through waiting times, which can be extremely long for elective surgery in low- and middle-income countries. While waiting, patients make consequential decisions about their health, finances and work, often with limited information. In partnership with a public hospital in Chile, we combine administrative data, a survey and an RCT to study how rationing by waiting shapes patient behavior and which policies can improve its efficiency and equity.
External Link(s)

Registration Citation

Citation
Gomez Colomer, Catalina and Ricardo Pommer Muñoz. 2026. "Rationing by Waiting, Information Frictions, and Patient Behavior." AEA RCT Registry. September 28. https://doi.org/10.1257/rct.19451-1.0
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Experimental Details

Interventions

Intervention(s)
We provide information to patients on the waitlist for elective surgery.
Intervention Start Date
2026-12-01
Intervention End Date
2027-03-01

Primary Outcomes

Primary Outcomes (end points)
Intention to exit the waitlist
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Healthcare utilization (primary care, specialists appointments, hospitalizations, urgent care, emergency room visits)
Self reported health
Labor and social-protection decisions: Do patients change the use of medical leave, self-reported probability of applying for disability insurance? Or make different labor market decisions?
Hospital complaints: Do patients change the frequency and content of official complaints made to the hospital?
Emotional responses: Are patients’ anxiety or depression measures changed?
Belief updating
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The study uses two stages of random assignment. In the first stage, patients on the surgical waiting list who meet the eligibility criteria are randomly assigned to be contacted for recruitment or not contacted, stratified by surgical procedure. In the second stage, recruited participants who complete a baseline survey are randomly assigned in equal proportions to a treatment group, which receives an informational intervention, or to a control group. This assignment is stratified by surgical procedure and time on the waiting list.
Experimental Design Details
Not available
Randomization Method
randomization done in an office on a computer
Randomization Unit
Patient
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
750 patients
Sample size: planned number of observations
750 patients
Sample size (or number of clusters) by treatment arms
375 treatment, 375 control
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We compute power for β3 in Y_i1 = β0 + β1 T_i + β2 G_i0 + β3 (T_i × G_i0) + β4 Y_i0 + δ_s + ε_i1, where Y_i1 is the primary outcome index at 3 months, standardized relative to the control group (mean 0, SD 1; Kling, Liebman & Katz 2007), Y_i0 its baseline value, T_i the information treatment, G_i0 a pre-specified baseline subgroup indicator, and δ_s stratum fixed effects. Monte Carlo simulation following McConnell & Vera-Hernández (2025), 2,000 replications per power evaluation, assuming N = 630 at endline (750 at baseline less attrition), individual 1:1 randomization within strata (no clustering), subgroups of equal size, and a baseline–endline correlation of the index of 0.5. MDE for β3 at 80% power and 5% significance (two-sided): around 0.39 SD of the index (39% of a standard deviation), equivalent to effects of about 0.2 SD in opposite directions for the two subgroups.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Columbia University Institutional Review Board
IRB Approval Date
2026-07-30
IRB Approval Number
IRB-ACYY2475
IRB Name
Comité de Ética Científico del Servicio de Salud Metropolitano Sur
IRB Approval Date
2026-07-09
IRB Approval Number
063-09062026
Analysis Plan