Health insurance as tool to smooth seasonal incomes - A randomized controlled trial

Last registered on August 02, 2023
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Pre-Trial

Trial Information

General Information

Title
Health insurance as tool to smooth seasonal incomes - A randomized controlled trial
RCT ID
AEARCTR-0010602
Initial registration date
December 07, 2022

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
December 13, 2022, 11:13 PM EST

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

Last updated
August 02, 2023, 2:24 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country
Côte d'Ivoire
Region
West Africa

Primary Investigator

Name
Günther Fink
Affiliation
Swiss Tropical and Public Health Institute
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Other Primary Investigator(s)

PI Name
Kelsey Jack
PI Affiliation
University of California, Santa Barbara
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PI Name
Daoda Dao
PI Affiliation
CSRS
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PI Name
Renate Strobl
PI Affiliation
Contact Investigator

Additional Trial Information

Status
On going
Start date
2022-04-04
End date
2024-12-31
Keywords
Agriculture, Finance & Microfinance, Health
Additional Keywords
insurance
JEL code(s)
G22, I12
Secondary IDs
NA
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
In this project, we aim to assess i) whether customized payment and enrolment schedules can increase the adoption of health insurance schemes in rural agricultural settings; and ii) the extent to which health insurance schemes with optimized payment schedules can reduce seasonality in consumption, investment and care-seeking.

We propose to conduct a 3-arm cluster-randomized controlled trial with 2400 rural households in central Cote d’Ivoire. One third of the study clusters will receive enrolment support during the lean season, 1/3 of clusters will receive enrolment support during the post-harvest season, and 1/3 will serve as a control group. Households in the first arm will be further randomized to either start contributions immediately, or to complete enrolment but start contributions after the harvest.

This study will contribute to the growing literature on seasonal constraints and their welfare impacts. Through the supported provision of insurance, the study also has the potential to improve the health and wellbeing of participating households.
External Link(s)

Registration Citation

Citation
Dao, Daoda et al. 2023. "Health insurance as tool to smooth seasonal incomes - A randomized controlled trial ." AEA RCT Registry. August 02. https://doi.org/10.1257/rct.10602-1.2
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
We propose to conduct a 3-arm cluster-randomized controlled trial with 2400 rural households in central Cote d’Ivoire. One third of the study clusters will receive enrolment support during the lean season, 1/3 of clusters will receive enrolment support during the post-harvest season, and 1/3 will serve as a control group. We will also test a salience treatment reminding households of recent health expenditure.
Intervention Start Date
2022-09-01
Intervention End Date
2023-12-31

Primary Outcomes

Primary Outcomes (end points)
The primary study outcomes are food security and health seeking behavior.
Primary Outcomes (explanation)
We will assess whether having health insurance will reduce the fluctuations in seasonal consumption and increase health care seeking during the lean season.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This is a three-arm trial with individual-level randomization and a total sample size of 2400 farmers.
Experimental Design Details
Not available
Randomization Method
Min-max randomization by a computer.
Randomization Unit
Households
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
12 villages and about 120 hamlets will be involved in this study.
Sample size: planned number of observations
2400 households
Sample size (or number of clusters) by treatment arms
800 households in each arm
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Our study is designed to detect an intention-to-treat effect of 0.25 SDs between the two intervention arms and the control arm assuming a conservative follow-up rate of 85% over the two year study period.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Ethikkommission Nordwest und Zentral Schweiz (EKNZ)
IRB Approval Date
2021-12-01
IRB Approval Number
AO202100070
Analysis Plan

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