Delivering on Universal Health Coverage promises in the hardest-to-reach areas of Madagascar through drone delivery services.

Last registered on August 10, 2023

Pre-Trial

General Information

Title

RCT ID

AEARCTR-0011710

Initial registration date

August 08, 2023

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

August 10, 2023, 1:39 PM 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

Katherine Tumlinson

Affiliation

UNC Chapel Hill

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Other Primary Investigator(s)

PI Name

Daniel Crapper

PI Affiliation

Population Services International

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PI Name

Sandrah Rahantanirina

PI Affiliation

Population Services International

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PI Name

Paul Bouanchaud

PI Affiliation

Population Services International

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PI Name

Mungai Mwangi

PI Affiliation

Innovations for Poverty Action-Kenya

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Additional Trial Information

Status

On going

Start date

2023-06-19

End date

2024-10-31

Keywords

Health

Additional Keywords

Family planning, Reproductive health, Health services, Contraceptive stockouts, Contraceptive supply, Drone Delivery

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

Purpose: Drones can provide reliable on-demand delivery of medical commodities to healthcare facilities that are hard-to-reach via land-based transportation. Although drone delivery has been implemented in several countries in sub-Saharan Africa as a means of improving supply chain logistics, there is little evidence of the impact of drone delivery on supply availability, service utilization, quality of care, and health outcomes in low- and middle-income countries (LMICs). This study aims to quantify the impact of drone delivery on supply availability, quality of care, and health outcomes in rural Madagascar.

Participants: Study participants will include healthcare providers and exiting clients at 109 public-sector healthcare facilities and women of reproductive age living in the catchment areas of these facilities in three regions of Madagascar (Alaotra Mangoro, Atsinanana, and Vatovavy Fitovinany).

Procedures: This is a cluster randomized experiment in which 109 hard-to-reach public healthcare facilities located in three regions of Madagascar will be randomly assigned to receive either drone delivery or standard land-based delivery of medical supplies. Prior to facility randomization, we will first stratify by the seven districts and by a binary measure of facility remoteness. This will ensure treatment balance across the districts and by facility location.

Each study arm will contain approximately 54 facilities, which, on average, serve approximately 9,000 people. Pre- and post-intervention data will be collected at both the facility and individual level to estimate treatment effects.

External Link(s)

Registration Citation

Citation

Bouanchaud, Paul et al. 2023. "Delivering on Universal Health Coverage promises in the hardest-to-reach areas of Madagascar through drone delivery services.." AEA RCT Registry. August 10. https://doi.org/10.1257/rct.11710-1.0

Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)

The study will include two arms: the intervention group and the control group. The intervention group will receive treatment with health products delivered for the last miles using a combination of drones and land transportation. Some health products will be delivered by drones, while others will be transported by land. In contrast, the control group will solely receive health products delivered for the last miles using land transportation.

Intervention Start Date

2023-09-01

Intervention End Date

2024-09-30

Primary Outcomes

Primary Outcomes (end points)

Improved availability of commodities
Improved access to health care for all
Higher child survival
Improved maternal health

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

To determine how relative cost effectiveness varies across study sites in order to identify sites where drone delivery is likely to be superior to standard practice for given levels of operational scale.

Secondary Outcomes (explanation)

Here, we will conduct a comparative cost effectiveness analysis (CEA) of the program by relating the incremental costs of the program to the incremental effects estimated from the RCT. The incremental costs, to be collected during implementation, will include the costs of the program over and above the standard of care, as well as costs averted. Costs will include both monetary and non-monetary costs facing program administrators and beneficiaries and will be itemized using the ingredients method. As the trial assesses effects on multiple outcomes, we will estimate cost effectiveness using each individual outcome as well as a combined outcome in terms of DALYs averted (cost-utility). Data permitting, we will also conduct a limited cost-benefit analysis to estimate total returns of the program by modelling the relationship between short-run trial outcomes and longer-term measures of well-being. All analyses will be presented in terms of programmatic as well as social perspectives.

Experimental Design

This is a cluster randomized experiment in which 109 public healthcare facilities located in range of the drone site will be randomly assigned to one of two study arms: 1. Drone commodity delivery, 2. The control arm. Each study arm will contain approximately 54 facilities, which, on average, serve approximately 9,000 households each. Prior to randomization, we will ensure each arm is balanced with respect to district and remoteness of the facility using stratification.

Randomization will be conducted at facility level stratifying by facility type/size. Before and after implementing the intervention, individual- and facility-level pre- and post-intervention surveys will be conducted. The individual-level surveys will be conducted within a representative sample of households with women of reproductive age. The facility-level surveys will be conducted in all selected facilities and will be used to measure commodity availability and service utilization.

Experimental Design Details

Not available

Randomization Method

Randomization done using computer algorithm

Randomization Unit

Our unit of randomization is the public-sector facility and a corresponding community, called a ‘Fokontany'

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

109 hard-to-reach public-sector healthcare facilities located

Sample size: planned number of observations

1200 individual household surveys at baseline – 3300 at endline; 109 facility audits (surveyed at baseline and endline) with health providers 300 Providers, (surveyed at baseline and endline); 200 Community health workers (surveyed at baseline and endline); 800 Client exit interviews (400 baseline, 400 endline)

Sample size (or number of clusters) by treatment arms

55 facilities control, 54 facilities treatment arm

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Individual levels surveys: We estimate an effect size of just under two standard deviations (which correlates to a change in the prevalence of modern contraceptive use of approximately 7 percentage points) Facility level: The study is powered to detect a change in the probability of stock outs to below 3%.

Supporting Documents and Materials

IRB

Institutional Review Boards (IRBs)

IRB Name

PSI Research Ethics Board

IRB Approval Date

2023-06-12

IRB Approval Number

1636.2022

Analysis Plan