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The impact of i-PUSH on maternal and child health outcomes, health care utilization and financial protection: a cluster randomised controlled trial based on Financial and Health Diaries data
Last registered on June 26, 2020

Pre-Trial

Trial Information
General Information
Title
The impact of i-PUSH on maternal and child health outcomes, health care utilization and financial protection: a cluster randomised controlled trial based on Financial and Health Diaries data
RCT ID
AEARCTR-0006089
Initial registration date
June 26, 2020
Last updated
June 26, 2020 10:51 AM EDT
Location(s)
Region
Primary Investigator
Affiliation
Vrije Universiteit Amsterdam
Other Primary Investigator(s)
PI Affiliation
Vrije Universiteit Amsterdam & University of Amsterdam
PI Affiliation
African Population and Health Research Centre
PI Affiliation
African Population and Health Research Centre
Additional Trial Information
Status
In development
Start date
2019-10-01
End date
2021-12-31
Secondary IDs
Abstract
This study aims to understand how a mobile technology-based program, including mobile phone-based subsidized health insurance and training of community health volunteers (CHVs), improves health outcomes, access to healthcare and financial protection for low-income women and their family members in Western Kenya. The intervention, called i-PUSH (Innovative Partnership for Universal Sustainable Healthcare), is implemented by Amref Health Africa and PharmAccess Foundation. We conduct a cluster randomised controlled trial in 24 villages in Kakamega county, Kenya. In each village, we select 10 households with a child under four years old or a pregnant woman. We collect baseline data, followed by year-long weekly financial and health diaries, monthly pop-up modules and an endline survey. We also conduct incentivised lab-in-the-field experiments to elicit women’s empowerment, time preferences and risk preferences.
External Link(s)
Registration Citation
Citation
Donfouet, Hermann et al. 2020. "The impact of i-PUSH on maternal and child health outcomes, health care utilization and financial protection: a cluster randomised controlled trial based on Financial and Health Diaries data." AEA RCT Registry. June 26. https://doi.org/10.1257/rct.6089-1.0.
Experimental Details
Interventions
Intervention(s)
The Innovative Partnership for Universal Sustainable Healthcare (i-PUSH) program, developed by Amref Health Africa and PharmAccess Foundation (PAF), aims to empower low-income women of reproductive age and their families through innovative digital tools. Notably, i-PUSH fosters savings for healthcare and health insurance premiums through the mobile phone-based “health wallet”, and it stimulates enrolment in subsidized health insurance through the mobile health platform M-TIBA – both developed by PAF; it also seeks to improve health knowledge and behavior through Community Health Volunteers (CHVs) whose training is enhanced using the mobile phone-based LEAP training tool–as developed by Amref. I-PUSH has been ongoing in Nairobi and parts of Kakamega County since 2017. The study is being carried out in Khwisero Sub-county–where the I-PUSH program will expand to after the baseline survey.
Intervention Start Date
2020-07-01
Intervention End Date
2021-12-31
Primary Outcomes
Primary Outcomes (end points)
• Health care utilization
• Maternal and child health outcomes
• Out-of-pocket health expenditures
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Maternal and child health knowledge and behaviour, women’s empowerment, financial coping mechanisms
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The experimental design is a matched-pair, longitudinal cluster randomised controlled trial (RCT), with randomization at the village level. We first randomly selected 24 villages in the catchment area of four health facilities (six per health facility). We then matched villages in 12 pairs using Euclidean distance measures, based on village-level characteristics and aggregated household characteristics from the baseline survey. We randomly assigned one village per pair to the treatment arm by flipping a coin during a public ceremony.

The implementing partners selected four health clinics to be included in the expansion of the I-PUSH program. Six (6) villages located in the catchment areas of each of these four clinics were randomly selected from a list of all villages in the catchment areas, for a total of 24 villages. The list of villages was provided by the Sub-county government jointly with the i-PUSH program area manager. Random selection was done by the research team using a computer program.
In each village, selected CHVs and PAF’s area manager provided a complete list of households and other necessary information within the work area of each CHV. Based on household demographics and pregnancy information, eligible households were identified. Eligible households included those with at least one woman of reproductive age (WRA) (18-49) who: a) had at least one child below 4 years living with her at baseline; or b) was pregnant at baseline. The team randomly selected 10 eligible households per CHV in each village to be included in the study sample. Additional eligible households per CHV were listed to serve as replacement households for refusals and dropouts.
Initially, the study sought a 50-50 allocation between households with a pregnant woman and households with a child under 4 years old. After the household listing exercise, it became clear that there were too few pregnant women in each village to fulfill this criterion. We then decided to include all pregnant women in our sample up to 50 percent, and randomly sample additional households with children under 4 years old until the cluster size (10 households per village) was achieved. The research team did a random selection as follows: all eligible households with children under 4 years old were entered in Excel sheet and receive a randomly assigned number.
We then conducted a baseline survey which collected information on household demographics, socio-economic indicators, food consumption indicators, financial inclusion, participation in community networks, as well as self-assessed health status, health-related knowledge and behavior, health care utilization and health expenditures, maternal health, mental health, intra-household decision-making processes and gender dynamics. We also collected village-level characteristics including demographic information, infrastructure and access to (health) services. After baseline data collection, villages were matched in pairs and one village in each pair was randomly assigned to the treatment group.
The weekly financial and health diaries commenced two weeks after the baseline data collection was completed and will continue for 12 months from the start of the intervention. The financial diaries record all financial transactions such as income, expenditures, loans, savings and gifts, remittances and loans, including those between household members, in the seven days prior to each interview. The health diaries provide a detailed picture of the incidence of illnesses and injuries, as well as preventive and curative health care utilization. Health diaries collect data on all health events that occurred to any of the household members (respondents, their children and other household members) in the seven days prior to each interview. This includes symptoms, whether any health care was sought, which health provider was visited, health services received, out-of-pocket health expenditures, date of onset of the symptoms and date of provider visit(s). Diaries respondents are also invited to participate in a number of incentivized lab-in-the-field experiments to measure women’s empowerment, risk attitudes, and time preferences.
The study will be concluded by an endline survey scheduled after 12 months of program implementation, incorporating the same modules as the baseline survey, as well as a satisfaction module on participation in the i-PUSH program for women in the treatment areas.
Experimental Design Details
Not available
Randomization Method
After the baseline household and village surveys, we matched villages in 12 pairs. We used the Euclidean distance for our matching process, which corresponds to the absolute difference between the standardized values of all of the covariates for a possible pair of matches. Our matching indicators included village-level indicators (demographics, infrastructure, availability of health services) and household-level indicators, aggregated at the village-level (female educational attainment, share of women earning income, membership of savings groups for women, mobile phone ownership for women, wealth, health care utilization, health expenditures, health insurance).
Randomization was blocked at the health facility level. Thus, each village was matched with one of the other five villages in the catchment area of its nearest health facility. This was done to ensure that each health clinic had an equal number of treatment and control villages in their catchment area. Hence we computed this distance measure between each village and all other villages within the same health clinic catchment area; “pair” the two villages with the minimum distance and remove them from the list; repeat the distance calculation excluding the pair made; and continue until all villages were paired.
After the matching process, the randomization assignment was carried out in the presence of key stakeholders including PAF, local liaison persons and village representatives, upon explaining all steps. Consent for the procedures was obtained from local government officials before the random assignment. The following steps were conducted: Papers with paired village names were folded and put in a bag; two village representatives from each paired village discussed whom would pick the paper; and after the other group members verified that the names could not be seen, one paper was picked. A Kenya Shilling 10 coin was used to decide which group the picked village belonged to by flipping the coin. The village representatives had decided that the head of the coin should represent the control group, justifying that Kenyatta (1st president of Kenya) was a controlling village and the shield to represent the intervention group. The process of choosing the folded paper and flipping of the coin was repeated for all paired villages.
Randomization Unit
The unit of randomization for treatment was the village-level.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
Planned number of units: 24 villages
Sample size: planned number of observations
Planned number of observations: 240 households, 1,197 individuals Planned number of observations for weekly diaries: 444 adults
Sample size (or number of clusters) by treatment arms
Treatment arm: 12 villages (120 households)
Control arm: 12 villages (120 households)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Amref Health Africa Ethics and Scientific Review Committee
IRB Approval Date
2019-08-08
IRB Approval Number
P679-2019