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Field
Trial Status
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Before
in_development
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After
on_going
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Abstract
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Before
Access to high quality healthcare is a critical driver of human capital and a cornerstone of broader individual and societal well-being. In Uganda, rural access to health care and to essential medicines remains a persistent challenge; although 86% of Ugandans live in rural areas, only 15-20% of the country’s doctors work in those same areas, which contributes to poorer health outcomes among rural populations. Aside from a few irregular, one-day “mobile clinics” or sponsored medical missions, there are few resources in place for delivering healthcare on a regular basis to people in remote areas. We partnered with Health Access Connect (HAC), a Ugandan-based NGO that coordinates monthly, financially self-sustainable outreach visits by clinical staff from government health facilities to rural communities that are located at least 5 km away from public health facilities. Through a cluster-randomized trial in 64 health facilities and 128 villages, this study will evaluate the impact of HAC’s community-based outreach activities on the demand, quality, and utilization of health services, household health outcomes, child schooling and human capital, and household labor market incomes.
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After
Access to high quality healthcare is a critical driver of human capital and a cornerstone of broader individual and societal well-being. In Uganda, rural access to health care and to essential medicines remains a persistent challenge; although 86% of Ugandans live in rural areas, only 15-20% of the country’s doctors work in those same areas, which contributes to poorer health outcomes among rural populations. Aside from a few irregular, one-day “mobile clinics” or sponsored medical missions, there are few resources in place for delivering healthcare on a regular basis to people in remote areas. We partnered with Health Access Connect (HAC), a Ugandan-based NGO that coordinates monthly, financially self-sustainable outreach visits by clinical staff from government health facilities to rural communities that are located at least 5 km away from public health facilities. Through a cluster-randomized trial in 64 health facilities and 192 villages, this study will evaluate the impact of HAC’s community-based outreach activities on the demand, quality, and utilization of health services, household health outcomes, child schooling and human capital, and household labor market incomes.
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Trial Start Date
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Before
January 01, 2025
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After
January 01, 2026
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Trial End Date
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Before
August 18, 2027
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After
September 30, 2028
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Last Published
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Before
January 27, 2025 10:15 AM
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After
June 12, 2026 10:14 PM
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Field
Intervention (Public)
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Before
The HAC program establishes one-day integrated care outreach clinics in remote communities (communities that are greater than 5 km from the nearest health facility) every 1-2 months. Government healthcare workers are transported from the health faciliy to target communities to provide a range of health services. Local Community Associations in remote communities are trained to lead the program in collaboration with the local health facility and are also supported in financing the costs of the outreach clinics.
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After
The HAC program establishes one-day integrated care outreach clinics in remote communities (communities that are greater than 5 km from the nearest health facility) every 1-2 months. Government healthcare workers are transported from the health facility to target communities to provide a range of health services. Local Community Associations in remote communities are trained to lead the program in collaboration with the local health facility and are also supported in financing the costs of the outreach clinics.
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Field
Intervention Start Date
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Before
July 01, 2025
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After
July 01, 2026
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Intervention End Date
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Before
August 18, 2027
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After
August 31, 2028
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Field
Primary Outcomes (End Points)
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Before
Health Utilization, Health Outcomes, Schooling Outcomes, and Labor Market Outcomes
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After
Health Utilization; Family Planning Method Usage
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Field
Primary Outcomes (Explanation)
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Before
Health utilization is measured by whether an individual received any healthcare in the past 30 days for all age groups as well as separately for those aged 5–17 and 18–60.
Health outcomes are assessed by the number of days an individual was sick in the past 30 days, analyzed for all age groups as well as separately for those aged 5–17 and 18–60.
Schooling outcomes are measured by the number of school days missed in the past 30 days for individuals aged 5–17.
Labor market outcomes include the number of workdays missed due to usual work activities in the past 30 days for individuals across all age groups and whether individuals aged 18–60 are currently engaged in wage labor. These variables will be collected through multiple rounds of household surveys.
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After
Health utilization is measured by (i) whether an individual received any healthcare in the past 30 days for all age groups as well as separately for those aged 0-5, 5–17, and 18–65, and (ii) family planning method usage during the study period by the primary respondent.
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Experimental Design (Public)
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Before
This study is a two-armed randomized control trial that will be conducted among 64 health facilities, 128 corresponding communities / villages (2 villages per health facility) that are located within each health facility’s catchment area, and an estimated 3,200 eligible households (approximately 25 households per selected village). The study consists of a baseline survey with health facilities, villages, and households, followed by randomization of health facilities into the HAC intervention and control arms and the implementation of the two-year family planning intervention. Two follow-up surveys were conducted one and two years after the baseline survey, respectively.
We will select 64 HC-III or HC-IV health facilities (HFs), and we will identify 128 villages (2 villages per HF) that are located more than 5 km away from the 64 HFs. From each village, we will select 25 households with at least one school-aged child (aged 5-17) for baseline surveys.
Following a baseline survey with 3200 households and 64 HFs, we will randomize HFs, and their corresponding villages and houesholds, into a treatment group or a control group:
• 32 HFs will be randomly selected as the control group. These HFs, and their corresponding villages and households, will receive no interaction with the HAC intervention, and no HAC outreach services will take place.
• 32 HFs will be randomly selected as the treatment group. Staff at these HFs will partner with HAC and will provide outreach services to households in the corresponding villages that are part of the HF's service catchment area..
We will then conduct several rounds of follow-up over a two year period to: (i) measure impacts of the HAC intervention on short-term and long-term outcomes of interest, (ii) identify any effects of the HAC intervention on the service delivery at health facilities. After 1 year of implementation, we will survey an additional 1600 households outside the target villages in order to detect any unintended impacts of the HAC intervention on service utilization at HFs and the resulting spillover effects that these unintended effects may have had on non-target communities.
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After
This study is a two-armed randomized control trial that will be conducted among 64 health facilities, 192 corresponding communities / villages (3 villages per health facility) that are located within each health facility’s catchment area, and an estimated 3840 eligible households (approximately 20 households per selected village). The study consists of a baseline survey with health facilities, villages, and households, followed by randomization of health facilities into the HAC intervention and control arms and the implementation of the two-year family planning intervention. The endline survey will be conducted around one year after the implementation begins.
We will select 64 HC-III or HC-IV health facilities (HFs), and we will identify 128 villages (2 villages per HF) that are located more than 5 km away from the 64 HFs and another 64 communities (1 community per HF) that are located adjacent to (within 5km of) the 64 HFs. From each village/community, we will select 20 households with women aged 18–35 who are non-pregnant and at least six months postpartum for baseline surveys.
Following a baseline survey with 3840 households and 64 HFs, we will randomize HFs, and their corresponding villages and households, into a treatment group or a control group:
• 32 HFs will be randomly selected as the control group. These HFs, and their corresponding villages and households, will receive no interaction with the HAC intervention, and no HAC outreach services will take place.
• 32 HFs will be randomly selected as the treatment group. Staff at these HFs will partner with HAC and will provide outreach services to households in the corresponding villages that are part of the HF's service catchment area..
We will then follow up with the surveyed households and health facility one year after the intervention rollout to: (i) measure impacts of the HAC intervention on short-term outcomes of interest, specifically contraception, (ii) identify any effects of the HAC intervention on the service delivery at health facilities, (iii) detect any unintended impacts of the HAC intervention on service utilization at HFs and the resulting spillover effects that these unintended effects may have had on non-target communities, and (iv) estimate the cost-effectiveness of the HAC.
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Planned Number of Clusters
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Before
64 health facilities, with additional 6 facilities as backup in the baseline survey
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After
64 health facilities
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Field
Planned Number of Observations
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Before
64 health facilities (plus an additional 6 facilities in the baseline survey), 192 villages, and 4800 households.
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After
64 health facilities, 192 villages, and 3840 households.
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Sample size (or number of clusters) by treatment arms
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Before
Treatment group: 32 health facilities and their corresponding 64 villages and 1600 households within the catchment area.
Control group: 32 health facilities and their corresponding 64 villages and 1600 households within the catchment area.
Indirect analysis: 64 villages, and their corresponding 1600 households, that are located close to the health facilities.
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After
Treatment group: 32 health facilities and their corresponding 64 villages and 1280 households within the catchment area.
Control group: 32 health facilities and their corresponding 64 villages and 1280 households within the catchment area.
Indirect analysis: 64 communities, and their corresponding 1280 households, that are located close to the health facilities.
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Power calculation: Minimum Detectable Effect Size for Main Outcomes
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Before
We focus on the primary outcomes measured in year 2 of our intervention. For health utilization, the standardized MDE for receiving health care among all individuals is 0.15 standard deviation (SD), with a 94% power, corresponding to a 6.7 percentage point (pp) increase in health care receipt. For individuals aged 5–17 and 18–60, the MDEs are also 0.15 SD with power levels of 90% and 85%, respectively, corresponding to a 6.2 pp and 6.5 pp increase in health care receipt. Regarding health outcomes, the MDE for days sick across all individuals is 0.15 SD with 99% power, equating to a 0.74-day reduction in days sick. For school-aged children (5–17), the MDE is 0.15 SD with 95% power, corresponding to a 0.52-day reduction, while for individuals aged 18–60, it is 0.15 SD with 95% power, translating to a 0.75-day reduction. In terms of schooling outcomes, the MDE for days of school missed among children aged 5–17 is 0.11 SD with 83% power, representing a 0.22-day reduction in school absences. For labor market outcomes, the MDE for the likelihood of currently working for pay among individuals aged 18–60 is 0.14 with 81% power, corresponding to a 5.7 pp increase. Additionally, the MDE for days of usual work activity missed among all individuals is 0.07 SD with 87% power, reflecting a 0.24-day reduction. These results indicate the study's strong ability to detect meaningful changes across a range of outcomes, with standardized MDEs ranging from 0.07 to 0.15 SD and high statistical power (≥80%) across all measures.
Throughout the power analysis, we assume 20% random attrition rates per year. We also include allowance for the increase in precision due to the inclusion of covariates as follows: 13% increase in R-2 from individual covariates; 8% increase in R-2 from village-level covariates; an increase in R-2 of 27% from HF covariates. These parameters are based upon regression estimates using covariates correlated with days sick and days of usual activity missed due to sickness. We use empirical ICCs at various levels taken from either the 2019-2020 UNPS or 2016 Uganda DHS.
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After
We focus on the primary outcomes measured one year after the intervention rollout. In remote villages we can detect a 0.2 SD increase in current family planning use, or a 9.4 pp change, and a 0.235 SD increase in ever use during the intervention period, or a 11.3 pp increase. These estimates are reasonable, as our intervention directly delivers health care to an underserved population receiving outreaches for the first time. We remain well-powered to detect changes in months of usage among current users at a 70% take-up rate and unmet demand at 80% take up. Similarly, at a 90% take-up rate, we have approximately 80% power to detect a 0.239-0.26 SD change in overall healthcare utilization
For our primary comparison, the study is powered to detect 0.215 SD changes on health care utilization in the last 30 days in remote villages. This corresponds to an increase of 9.4 percentage points over a baseline mean of 26%. For family planning outcomes, the study is powered to detect a 0.235 SD (or 11.449.46 pp) improvement in ever using a family planning method during the intervention period.
Throughout the power calculations, we assume 80% power, 5% significance, and a 10% endline attrition. We assume intra-cluster correlation (ICC) and R-squared gains from covariates from existing data sources as well as a 0.27 improvement in R-squared by including covariates at health facility level. Our study may suffer from non-compliance at either an outreach level (i.e., the outreaches do not occur) or at a respondent level (i.e., the respondent does not take up contraception). We aggregate both forms of non-compliance into the “take-up rate” and analyze sensitivity of statistical power to various scenarios.
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Secondary Identifying Number(s)
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Before
USAID: 7200AA24FA00009
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After
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Field
Intervention (Hidden)
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Before
We have partnered with Health Access Connect (HAC), a Ugandan-based non-profit organization that monthly, financially self-sustainable outreach visits by clinical staff from government health facilities to rural communities that are located at least 5 km away from public health facilities. The HAC approach is based on an integrated community outreach program that focuses on comprehensive care delivery rather than on a single health condition while leveraging the existing health workforce. HAC has developed a scalable model focused on delivering comprehensive primary care at low cost while emphasizing sustainability, self-reliance, and health equity.
HAC’s model of service implementation is both simple and innovative. HAC coordinates one-day integrated care outreach clinics in remote communities (communities that are located more than 5 km from the nearest health facility) every 1-2 months. The HAC outreach team is comprised of public health workers from the local government health facilities who provide free health services at these outreach clinic sites. Services that are provided as part of the outreach visit include vaccines, malaria treatment, family planning, perinatal, pediatric care, antiretroviral therapy (ART), HIV testing and counselling, health education, and other primary healthcare services.
At health facilities without a reliable form of transportation, HAC microfinances a motorcycle (Medicycles) or boat taxi to a local entrepreneur, who is required to service outreach clinics as a condition of the loan. HAC supports local communities to organize themselves into a group that collects funds to support transportation costs, which range from $22-30 per outreach clinic to that particular village. Individuals contributing to these collective, village-level cost of the outreach are the beneficiaries that are able to attend and receive care at the integrated outreach occurring in their village.
HAC’s model distinguishes itself from other existing models in two key ways. First, HAC focuses on delivering services in situ rather than building far-away facilities. Health facilities are expensive, and resources to support them are limited. HAC reduces costs by eliminating the need for physical infrastructure and by minimizing transportation costs. For HAC’s outreaches, each patient pays only half to one-tenth of what they would pay to reach the nearest health facility by public means. This wealth pooling also promotes self-reliance by empowering patients to advocate for more or better services. The opportunity for interested motorcycle entrepreneurs to obtain low-interest loans by participating in monthly health outreaches is another defining feature of HAC’s approach.
Second, HAC’s model is designed for long-term operations. Many donor-funded outreaches are criticized for being prohibitively expensive, short-term, and focused on vertical project objectives. The prevailing paradigm for aid activities in Uganda often involves NGOs obtaining project grants, providing services for 2-5 years, and then ceasing operations as funding streams and global priorities shift. HAC creates long-term solutions by incentivizing the government to participate in a hybrid funding model that encourages sustained partnerships with international organizations while reducing aid dependency.
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After
We have partnered with Health Access Connect (HAC), a Ugandan-based non-profit organization that monthly, financially self-sustainable outreach visits by clinical staff from government health facilities to rural communities that are located at least 5 km away from public health facilities. The HAC approach is based on an integrated community outreach program that focuses on comprehensive care delivery rather than on a single health condition while leveraging the existing health workforce. HAC has developed a scalable model focused on delivering comprehensive primary care at low cost while emphasizing sustainability, self-reliance, and health equity.
HAC’s model of service implementation is both simple and innovative. HAC coordinates one-day integrated care outreach clinics in remote communities (communities that are located more than 5 km from the nearest health facility) every 1-2 months. The HAC outreach team is comprised of public health workers from the local government health facilities who provide free health services at these outreach clinic sites. Services that are provided as part of the outreach visit include vaccines, malaria treatment, family planning, perinatal, pediatric care, antiretroviral therapy (ART), HIV testing and counselling, health education, and other primary healthcare services.
At health facilities without a reliable form of transportation, HAC microfinances a motorcycle (Medicycles) or boat taxi to a local entrepreneur, who is required to service outreach clinics as a condition of the loan. HAC supports local communities to organize themselves into a group that collects funds to support transportation costs, which range from $22-30 per outreach clinic to that particular village. Individuals contributing to these collective, village-level cost of the outreach are the beneficiaries that are able to attend and receive care at the integrated outreach occurring in their village.
HAC’s model distinguishes itself from other existing models in two key ways. First, HAC focuses on delivering services in situ rather than building far-away facilities. Health facilities are expensive, and resources to support them are limited. HAC reduces costs by eliminating the need for physical infrastructure and by minimizing transportation costs. For HAC’s outreaches, each patient pays only half to one-tenth of what they would pay to reach the nearest health facility by public means. This wealth pooling also promotes self-reliance by empowering patients to advocate for more or better services. The opportunity for interested motorcycle entrepreneurs to obtain low-interest loans by participating in monthly health outreaches is another defining feature of HAC’s approach.
Second, HAC’s model is designed for long-term operations. Many donor-funded outreaches are criticized for being prohibitively expensive, short-term, and focused on vertical project objectives. The prevailing paradigm for aid activities in Uganda often involves NGOs obtaining project grants, providing services for 2-5 years, and then ceasing operations as funding streams and global priorities shift. HAC creates long-term solutions by incentivizing the government to participate in a hybrid funding model that encourages sustained partnerships with international organizations while reducing aid dependency.
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Secondary Outcomes (End Points)
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Before
Health Facility Service Delivery
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After
Health Facility Service Delivery, Health Outcomes, Schooling Outcomes, and Labor Market Outcomes
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Field
Secondary Outcomes (Explanation)
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Before
Service delivery is assessed at both the facility and individual levels to capture a comprehensive picture of the intervention's impact. At the individual level, it is measured through health utilization, health status, schooling, and labor market outcomes, focusing on villages located near health facilities that are not actively engaged in the HAC outreaches. At the facility level, service delivery is measured by key operational metrics, including the frequency of drug stockouts, adherence to facility operation schedules, and staffing levels among the participating health facilities.
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After
Service delivery is assessed at both the facility and individual levels to capture a comprehensive picture of the intervention's impact. At the individual level, it is measured through health utilization, health status, schooling, and labor market outcomes, focusing on villages located near health facilities that are not actively engaged in the HAC outreaches. At the facility level, service delivery is measured by key operational metrics, including the frequency of drug stockouts, adherence to facility operation schedules, and staffing levels among the participating health facilities.
Health outcomes are assessed by the number of days an individual was sick in the past 30 days, analyzed for all age groups as well as separately for those aged 5–17 and 18–60.
Schooling outcomes are measured by the number of school days missed in the past 30 days for individuals aged 5–17.
Labor market outcomes include the number of workdays missed due to usual work activities in the past 30 days for individuals across all age groups and whether individuals aged 18–60 are currently engaged in wage labor. These variables will be collected through multiple rounds of household surveys.
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