Proactive community case management and child survival: Protocol for a cluster randomised controlled trial

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Study Justification:
– Community health workers (CHWs) have been shown to improve access to care and reduce maternal, newborn, and child morbidity and mortality.
– CHWs are a key strategy to achieve health-related Sustainable Development Goals (SDGs).
– However, recent evaluations of CHW-led integrated community case management (iCCM) programs have not found benefits on access to care and child mortality.
– Developing innovative ways to maximize the potential benefits of iCCM is critical to achieving the SDGs.
Study Highlights:
– The study is a cluster randomized controlled trial conducted in rural Mali.
– It aims to test the efficacy of proactive case detection by CHWs compared to a conventional approach to iCCM service delivery in reducing under-five mortality.
– In the intervention arm, CHWs conduct daily proactive case-finding home visits and provide doorstep counsel, care, referral, and follow-up.
– In the control arm, CHWs provide the same services exclusively out of a fixed community health site.
– The primary endpoint is under-five mortality, measured as deaths among children under 5 years of age per 1000 person-years at risk of mortality.
– The trial has received ethical approval and will disseminate results through peer-reviewed publications, conferences, workshops, and media outlets.
Recommendations for Lay Reader:
– Proactive case detection by CHWs through home visits can potentially reduce under-five mortality.
– This study aims to compare the effectiveness of proactive case detection with the conventional approach to iCCM service delivery.
– The results of this study will provide valuable insights into improving access to care and reducing child mortality in rural areas.
Recommendations for Policy Maker:
– Consider implementing proactive case detection by CHWs as a strategy to improve access to care and reduce child mortality.
– Evaluate the effectiveness of proactive case detection through rigorous research and monitoring.
– Allocate resources to train and support CHWs in conducting proactive case-finding home visits.
– Remove user fees for CHW and referral services to ensure equitable access to care.
– Disseminate the findings of this study to inform policy decisions and scale-up of proactive case detection programs.
Key Role Players:
– Community health workers (CHWs): They will conduct proactive case-finding home visits and provide doorstep care.
– Ministry of Health: Responsible for implementing and supporting CHW programs.
– Research team: Conducts the cluster randomized controlled trial and analyzes the data.
– Clinical Research Associate (CRA): Provides external monitoring of the study.
– Data Safety and Monitoring Board (DSMB): Provides oversight and evaluates interim results.
Cost Items for Planning Recommendations:
– CHW salaries: CHWs will receive a salary circa minimum wage.
– Training and supervision: Resources needed to train and supervise CHWs.
– CHW mobile application: Equip CHWs with smartphones and develop a mobile application for tracking services rendered.
– Electronic Medical Records (EMR) system: Equip primary health centers with computers and train staff in data collection.
– Programmatic costs: Personnel, drugs, laboratory tests, and other inputs used to provide services.
– Household costs: Time spent accessing health services and out-of-pocket expenses.
Please note that the above information is a summary of the study and its components. For more detailed information, please refer to the original publication in BMJ Open, Volume 9, No. 8, Year 2019.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is strong, but there are some areas for improvement. The abstract provides a clear description of the study design, methods, and objectives. It also mentions ethical approval and plans for dissemination of results. However, it does not provide specific details about the sample size calculation, randomization process, or statistical analysis plan. Including these details would strengthen the evidence. Additionally, the abstract could benefit from a clearer statement of the primary and secondary endpoints. To improve the evidence, the authors should consider providing more information on the statistical analysis plan and clearly stating the primary and secondary endpoints.

Introduction Community health workers (CHWs) – shown to improve access to care and reduce maternal, newborn, and child morbidity and mortality – are re-emerging as a key strategy to achieve health-related Sustainable Development Goals (SDGs). However, recent evaluations of national programmes for CHW-led integrated community case management (iCCM) of common childhood illnesses have not found benefits on access to care and child mortality. Developing innovative ways to maximise the potential benefits of iCCM is critical to achieving the SDGs. Methods and analysis An unblinded, cluster randomised controlled trial in rural Mali aims to test the efficacy of the addition of door-to-door proactive case detection by CHWs compared with a conventional approach to iCCM service delivery in reducing under-five mortality. In the intervention arm, 69 village clusters will have CHWs who conduct daily proactive case-finding home visits and deliver doorstep counsel, care, referral and follow-up. In the control arm, 68 village clusters will have CHWs who provide the same services exclusively out of a fixed community health site. A baseline population census will be conducted of all people living in the study area. All women of reproductive age will be enrolled in the study and surveyed at baseline, 12, 24 and 36 months. The survey includes a life table tracking all live births and deaths occurring prior to enrolment through the 36 months of follow-up in order to measure the primary endpoint: under-five mortality, measured as deaths among children under 5 years of age per 1000 person-years at risk of mortality. Ethics and dissemination The trial has received ethical approval from the Ethics Committee of the Faculty of Medicine, Pharmacy and Dentistry, University of Bamako. The results will be disseminated through peer-reviewed publications, national and international conferences and workshops, and media outlets.

Our cluster randomised controlled trial aims to: The trial will be conducted in the Bankass health district of the Mopti region in eastern Mali, approximately 600 km east of the nation’s capital, Bamako. The district has a 2016 population of approximately 300 000 people and is served by a public secondary referral hospital located in Bankass, the largest town in the district.26 Within the Bankass health district, the study is being conducted in 7 (of 22) health catchment areas: Dimbal, Doundé, Ende, Kani Bozon, Koulongon, Lessagou and Soubala (figure 1). The study area has a 2016 population of approximately 100 000 people.26 Each health catchment area is served by a PHC operated by the Ministry of Health. Map of study area; colours indicate the seven health catchment areas within which the trial is being conducted. This is an unblinded, pragmatic, cluster randomised controlled trial, with 69 village clusters in the intervention arm and 68 village clusters in the comparison arm. Clusters are randomised to receive either enhanced iCCM from stationary CHW(s) serving patients exclusively at a community health site (control) as per Mali’s national iCCM strategy,27 or ProCCM from CHW(s) conducting daily proactive case-finding home visits in addition to serving patients at a community health site. Only the intervention arm will receive door-to-door proactive case detection by CHWs, including doorstep care and home-based follow-up. Local community members—female candidates encouraged—who can read and write in French will be recruited, trained, supervised and supported as CHWs from the village cluster in which they will work. CHW coverage will be based on Mali’s national iCCM strategy, which recommends one CHW for a population of 700 in the southern region where the study area is situated.27 Clusters, therefore, may have one or multiple resident CHWs, depending on the size of the cluster population. Clusters with less than 200 people and within 3 km of another cluster assigned to the same study arm will share a CHW, provided there is no geographic barrier (ie, river) between the two clusters and no linguistic barrier for the CHW. In both arms, CHWs will provide a comprehensive set of primary care services, including iCCM in accordance with national and international standards,2 as well as maternal and reproductive health for women of reproductive age (see table 1 for a full description of the CHW package of care). CHW services will include counselling, diagnostics, treatment, referral to reinforced PHCs and follow-up care. CHWs will be required to be on call, available to receive and care for patients who seek them out, 24 hours per day, 7 days per week. CHWs will receive a salary circa minimum wage (FCFA40 000 per month), and user fees will be removed for all CHW and referral services for all patients in the study area. A detailed description of the entire health system strengthening intervention in both arms is provided in the online supplementary document. Community health worker (CHW) package of care, provided at the patient’s doorstep (intervention arm) or at the CHW’s health site (both arms) *These services are also offered by conventional CHWs in the Malian context, according to the Ministry of Health’s policy on CHW care.27 iCCM, integrated community case management; IUD, intrauterine device; PHC, primary health centre. bmjopen-2018-027487supp001.pdf In clusters assigned to the control arm, CHWs will be stationed at a community health site to provide the comprehensive package of primary care services for at least 4 hours per day, 6 days per week, available to receive patients seeking care. The community health site is at the cluster level and separate from the PHC. In clusters assigned to the intervention arm, CHW(s) will be trained and deployed to conduct proactive case finding, door-to-door home visits for at least 2 hours each day, 6 days a week, with the goal of visiting each household at least two times each month. During the home visit, CHWs will screen all household members for recent illness or symptoms and provide services at the home, including follow-up for sick children and adults, pregnant women, newborns and postpartum mothers. In addition to home visits, ProCCM CHWs will provide care at their community health site for at least 2 hours a day, 6 days per week, according to a calendar shared with the community. At the health site, CHWs will provide the same services as those offered by CHWs in the control arm to care-seeking patients. In order to identify distinct clusters, a field team visited all villages and hamlets in the study area and collected global positioning system (GPS) coordinates at the public space where community-wide meetings, announcements and festivities are held. GPS coordinates were mapped and the cardinal distances between neighbouring villages and hamlets were calculated. Villages and hamlets 1 km or less from each another were grouped into clusters, resulting in 160 individual villages and hamlets grouped into 137 unique clusters. A cluster definition based in geographical reality rather than administrative delineation helps to mitigate against contamination. Clusters located 1.0 or more km from a PHC were stratified by health catchment area and distance to the nearest PHC (1.0–5.0 km vs more than 5.0 km). The cut-off point of 5.0 km was defined in accordance with national iCCM guidelines,27 which deploys CHWs to deliver iCCM services only in communities greater than 5.0 km from a PHC. An additional stratum included all villages where the PHC was located to ensure balanced assignment of PHC villages across arms. Within each stratum, clusters were randomly assigned to the control or treatment arm using a computer-generated random number. Randomisation was conducted by a member of the research team based in the USA who did not have any involvement in CHW recruitment or participant enrolment. Trial statisticians will remain blinded to cluster allocation until the end of the trial. The primary endpoint is under-five mortality, measured as deaths among children under 5 years of age per 1000 person-years at risk of mortality. In Mopti, the region of the study site, the 10-year under-five mortality rate (U5MR) was 111 deaths per 1000 live births during 2012–2013 Demographic and Health Survey (DHS), which is higher than the national U5MR.28 Since the 2013 DHS, intermittent prophylactic therapy in children for malaria has been rolled out across the region. As intermittent preventive treatment in children is associated with a risk ratio of all-cause under-five mortality of 0.66 in areas of seasonal transmission of malaria,29 we estimate that baseline U5MR in the area of the intervention will be 111*0.66=72.6/1000. The sample size for the trial was based on this primary endpoint, derived using methods for cluster randomised trials30 in which each cluster was treated as an observation and the cluster-level outcome was defined as the U5MR per person-years at risk. We used a negative binomial model to simulate the number of deaths among children under 5. According to 2014 national population estimates adjusted for 2016 using a 2.2% annual growth rate,26 the seven health catchment areas encompassed a population of 103 848 inhabitants. Assuming that 20% of the population was children aged 0–59 months and 22% was women aged 15–49, we calculated a mean of 152 children and 167 women per cluster. Person-years at risk were calculated assuming 3 years of prospective study follow-up with 10% attrition based on experience with previous trials in Mali.31 32 We used a coefficient of variation of k=0.2930 to model the extra variation due to clustering (1/k2 is the size parameter in the negative binomial model). With these parameters, the trial will be able to detect a relative difference of 25% (alpha=0.05, two-tailed test) in the under-five mortality incidence between treatment and control arms with 81.8% power after 36 months. We will also estimate the effect of the intervention on a number of secondary endpoints: Any individual in the study area at any point during the study period, including visitors, is eligible to receive the health services offered through the intervention. Only permanent residents of the study area are eligible to be included in the household survey. All women aged 15–49 permanently residing in the study area at baseline who provide consent or assent and report no foreseeable plans to leave the study area are eligible to participate in the women’s questionnaire of the household survey—the data source used for the measurement of primary and secondary endpoints. Women who did not meet the inclusion criteria at baseline but who become newly eligible during the course of the study are invited to participate at follow-up household survey rounds. The effects of the ProCCM model of service delivery, compared with the iCCM model, for the primary and secondary endpoints will be assessed using data from three sources: (1) household surveys, (2) the CHW mobile application and (3) facility records. A household survey will be administered to all eligible women at baseline (prior to the launch of the intervention), and 12, 24 and 36 months after the intervention start. Surveyors will not be members of the villages they survey, nor will they be members of the intervention healthcare delivery staff. All surveyors will be female, as the survey tool contains sensitive questions regarding contraception and reproductive health. The survey includes a household roster, which may be completed by the female head of household, and a questionnaire administered to consenting or assenting women of reproductive age (15–49). The household survey instrument was adapted from the Mali DHS and designed in Open Data Kit, which permits real-time quality and completeness control on data collection. The women’s questionnaire will include a full birth history to capture all live births, which will then be updated during each of the follow-up survey rounds. To track maternal mortality, the survey will record all household deaths occurring the previous year, with additional information on timing of death (during pregnancy, childbirth, after childbirth) for women of reproductive age. The survey also captures detailed information on household and individual sociodemographic characteristics, access and utilisation of reproductive and maternal healthcare, and care-seeking behaviours and investments for recently ill children under 5. Follow-up household survey rounds will add new household members to the study cohort (eg, due to births, migration) and record absences due to out-migration or death. Surveyors will attempt to contact each eligible woman up to three additional times if she is absent at the first visit. CHWs in both study arms will be equipped with an Android smartphone and trained to use a mobile application to track services rendered. The app is also designed to be a job aid with integrated data validation and prompts to guide the CHW through the appropriate case management protocol. Population census data collected at baseline, including individual unique identifiers and demographic information, will be prepopulated into the CHW application so that each CHW can access the records of families in his/her service delivery zone. During each encounter with a prospective patient, the CHW will either identify the individual in the application or register newborns, new arrivals or visitors, before selecting the appropriate form in the application for the specific health concern (eg, malaria case management). The types of actions displayed under a patient’s profile are linked to her sex and age (eg, pregnancy follow-up is displayed only for women aged 15–49). The application will also alert the CHW of upcoming tasks related to patient follow-up, with an action calendar for 24-hour follow-up available starting at midnight each day. Each PHC will be equipped with five laptop computers, and the physician-in-chief, midwife, pharmacist, vaccine administration technician and receptionist will be trained in data collection on an Electronic Medical Records (EMR) system. Population census data collected at baseline will be imported into the EMR system, including individual unique identifiers and basic demographic information. When attending a PHC, patients will present first to reception, where their medical records will be identified using their unique identifier, name, family and/or village information. During the patient consultation, the service provider will record patient health information (ie, diagnostic tests, results, treatment, posology) in both the EMR and in the paper facility registers, the source documents of the Malian Ministry of Health and required by law. Referral by a CHW will be recorded. Analyses of the primary and secondary endpoints will estimate intention-to-treat (ITT) effects. Using data collected prospectively in the 12, 24 and 36 months follow-up household surveys, we will test for the difference in the incidence of deaths among children under 5 across treatment and control arms using a Poisson regression model with cluster-level random effects, controlling for household distance to PHC (less than 5 km vs 5 km or more). Children surveyed at baseline will contribute person-years of exposure from the start date of the trial’s intervention launch; children born during the trial will contribute person-years of exposure beginning at birth. Children who enter the trial after baseline will contribute person-years of exposure beginning at the household survey interview date in which they are enrolled. All children included in the analysis will contribute person-years through the date of their death, or are right censored on their fifth birthday or the end date of the trial, whichever comes first. The coefficient of interest with be the incidence rate ratio estimated on a dichotomous variable that indicates the child’s residence in a treatment versus control cluster. We will control for the non-constant risk of mortality in early childhood by controlling for age (in months) constant over time, and will control for any individual-level characteristics that are unbalanced at baseline. To estimate mortality, a child’s date of birth, date of interview, vital status at interview, and if applicable, date of death are required. We will replicate the procedures for missing mortality data used in the DHS, described in detail elsewhere.33 The same modelling approach will be used to estimate ITT effects for secondary endpoints (excluding the covariate for child’s age); regression analyses will test the significance of the regression coefficient on the treatment assignment variable. Linking functions will be chosen based on the type of outcome variable analysed (ie, logit for dichotomous outcomes). If 10% or fewer observations have missing secondary outcome data, we will drop observations from analysis; otherwise, we will determine and apply sample weights to estimates derived from the complete sample of observations. For any secondary endpoints that differ significantly by arm at baseline, we will use a difference-in-differences estimation approach to account for this difference. ITT estimates will be compared with estimates from a per-protocol analysis of primary and secondary outcomes. Our per-protocol analysis will estimate the effects of the intervention only for households that received the ProCCM CHW services according to the intervention protocol. This will be defined as households, which report they have received two or more visits from a CHW in the month preceding the household survey for each year they participated in the survey, regardless of treatment assignment. Finally, exploratory analyses will be conducted to assess the existence and magnitude of heterogeneous treatment effects according to village population size and household wealth. Cost-effectiveness analysis (CEA) compares different programme alternatives in terms of their cost-effectiveness ratio, which can be thought of as the average cost per unit of impact or benefit (eg, cost per life year saved). In most cases, CEA is used to determine whether or not a new alternative policy is better than the status quo, or whether the extra cost is worth the extra benefit. In such cases, the incremental cost-effectiveness ratio (ICER) is used, which takes the ratio between the incremental costs of the new programme with respect to the status quo, to the incremental benefits of the new programme with respect to the status quo. We will perform an ICER analysis to evaluate the relative cost-effectiveness of the ProCCM model with respect to the enhanced iCCM (control) model. We will calculate the total economic costs of both programmatic models, which will reflect the monetary value of programme and household resources used to deliver and access services, respectively. From the programme perspective, these will include personnel and other recurrent costs such as drugs, laboratory tests and other inputs used to provide services. These data will come from three sources: (1) the CHW mobile application, which reflects all services and supplies used by CHWs for service provision; (2) PHC EMR, which include the services rendered at the PHC and resources will be valued at prices paid by the Ministry of Health; and (3) programme records, including CHW’s time and value of work time vis-à-vis salaries. From the household perspective, costs include time used to access health services, valued at their opportunity costs (ie, time lost from work), as well as out-of-pocket expenses such as paying for drugs or health services. These data will be obtained from the household survey, which asks about out-of-pocket expenditures, time spent accessing services and earnings from paid work. The study was designed and implemented in partnership with national, district and local health officials of the Malian Ministry of Health. Bankass health district was chosen in consultation with the Ministry of Health for three reasons: (1) healthcare utilisation (prenatal and curative consultations) was low and under-five mortality was high; (2) there were no overlapping interventions by other non-governmental organisations at the time or intended for the period of the trial and (3) local authorities were highly engaged and interested in collaborating on study implementation. Research questions and outcome measures were also chosen in consultation, to answer questions of key concern to government partners for informing the design of the national strategic plan for iCCM scale-up, including whether the intervention is equitable, cost-effective and affordable at scale. Community consultation and permission will be sought prior to trial commencement in meetings with representatives of the village clusters, such as village chiefs and their advisories, politico-administrative authorities, religious leaders and representatives of women’s and youth associations. Representatives will then communicate with community members via open public meetings. Once the study has terminated, results will be disseminated to participants via dissemination workshops at all levels of local, regional, and national representation. The University of California, San Francisco exempted secondary analysis of the trial data from ethical approval. External monitoring of the study will be assured by a Clinical Research Associate (CRA) external to the trial team. Any substantial protocol amendments or deviations, or any unintended effects of trial interventions or conduct, will be submitted to the Ethics Committee and records reviewed by the CRA. Surveyors will obtain informed consent from all household survey respondents prior to enrolment in the trial, or from the respondent’s parent or guardian if she is a minor. Identifying information (ie, proper name, phone number) will be stored separately from the survey data, linked by the registration ID. Access to identifying information will be restricted to the data collection and management team; trial statisticians and other external collaborators will access only de-identified data. An independent Data Safety and Monitoring Board (DSMB) will provide oversight throughout the trial. The DSMB will oversee participant safety and evaluate interim results to determine if the trial should be stopped early. Interim analyses of the primary endpoint (under-five mortality) will be performed at 12 and 24 months, estimated using data from the first and second follow-up household surveys. The DSMB will terminate the study early if a 50% relative difference in under-five mortality is detected after 12 months (statistical significance at p<0.001) or a 35% relative difference in under-five mortality after 24 months (p<0.001), a stopping rule more stringent than Haybittle-Peto stopping rules.34 35 At the end of the trial period, or if the trial is terminated early, all participating villages will receive the care with the condition identified in the superior study arm. Trial results will be published in peer-reviewed journals following the International Committee of Medical Journal Editors guidelines. Findings will be disseminated via conferences and workshops with national and international stakeholders in community-based healthcare delivery including researchers, policy-makers and practitioners. De-identified data will be made publicly available after the conclusion of the trial and publication of the main effects.

Based on the provided information, the innovation being tested in the cluster randomised controlled trial is the addition of proactive case detection by community health workers (CHWs) through door-to-door home visits. This innovation aims to improve access to maternal health by identifying and providing care to pregnant women, newborns, and postpartum mothers in rural Mali. The CHWs in the intervention arm will conduct daily proactive case-finding home visits, offering doorstep counsel, care, referral, and follow-up. This approach is compared to the conventional approach of providing services exclusively at a fixed community health site in the control arm. The trial will assess the efficacy of the proactive case detection approach in reducing under-five mortality, with the primary endpoint being deaths among children under 5 years of age per 1000 person-years at risk of mortality. The trial will also evaluate secondary endpoints, such as maternal mortality and access to reproductive and maternal healthcare. The results of the trial will be disseminated through peer-reviewed publications, conferences, workshops, and media outlets.
AI Innovations Description
The recommendation to improve access to maternal health is to implement a proactive community case management (ProCCM) approach. This approach involves training and deploying community health workers (CHWs) to conduct daily proactive case-finding home visits in addition to providing services at a community health site. The CHWs will conduct door-to-door visits, provide doorstep counsel, care, referral, and follow-up to pregnant women and new mothers. This proactive approach aims to improve access to care and reduce maternal and child morbidity and mortality.

The ProCCM approach will be tested through a cluster randomized controlled trial in rural Mali. The trial will compare the efficacy of the ProCCM approach with a conventional approach to integrated community case management (iCCM) service delivery. In the intervention arm, CHWs will conduct proactive case-finding home visits and provide care at the doorstep. In the control arm, CHWs will provide the same services exclusively at a fixed community health site.

The trial will be conducted in the Bankass health district of the Mopti region in eastern Mali. The study area has a population of approximately 100,000 people. The trial will include 69 village clusters in the intervention arm and 68 village clusters in the control arm. CHWs will be recruited, trained, supervised, and supported from the village clusters in which they will work. The CHW coverage will be based on Mali’s national iCCM strategy, which recommends one CHW for a population of 700.

The primary endpoint of the trial is under-five mortality, measured as deaths among children under 5 years of age per 1000 person-years at risk of mortality. Secondary endpoints include maternal mortality, access and utilization of reproductive and maternal healthcare, and care-seeking behaviors for sick children under 5.

The trial will collect data through household surveys, CHW mobile applications, and facility records. The data will be analyzed using intention-to-treat (ITT) effects and per-protocol analysis. Cost-effectiveness analysis will also be conducted to compare the relative cost-effectiveness of the ProCCM model with the enhanced iCCM model.

The trial has received ethical approval and will be monitored by a Data Safety and Monitoring Board (DSMB) to ensure participant safety. The results of the trial will be disseminated through peer-reviewed publications, conferences, workshops, and media outlets.

Implementing the ProCCM approach based on the findings of this trial has the potential to improve access to maternal health and reduce maternal and child morbidity and mortality in rural areas.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations for improving access to maternal health:

1. Implement proactive case detection: This involves training community health workers (CHWs) to conduct daily proactive case-finding home visits. CHWs can screen household members for any recent illness or symptoms and provide necessary care, referral, and follow-up. This approach ensures that pregnant women and new mothers receive timely and appropriate care.

2. Door-to-door counseling and care: CHWs can deliver doorstep counseling, care, referral, and follow-up services during their home visits. This approach eliminates the need for women to travel to healthcare facilities, making it more convenient and accessible for them to receive maternal health services.

3. Strengthen primary healthcare centers (PHCs): PHCs can be equipped with necessary resources and trained staff to provide comprehensive maternal and reproductive health services. This includes antenatal care, postnatal care, family planning, and other essential services. Strengthening PHCs ensures that women have access to quality care closer to their communities.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define the study area: Identify the specific region or district where the recommendations will be implemented. Consider factors such as population size, healthcare infrastructure, and existing maternal health indicators.

2. Randomized controlled trial: Conduct a cluster randomized controlled trial to compare the impact of the recommendations on maternal health outcomes. Randomly assign clusters (villages or catchment areas) to either the intervention group (implementing the recommendations) or the control group (continuing with existing practices).

3. Baseline data collection: Conduct a baseline population census to gather information on the target population, including women of reproductive age. Survey women at baseline and collect data on maternal health indicators such as antenatal care utilization, childbirth practices, and postnatal care.

4. Intervention implementation: Implement the recommendations in the intervention group. Train CHWs, equip PHCs, and establish systems for proactive case detection, door-to-door counseling, and care.

5. Follow-up data collection: Conduct follow-up surveys at regular intervals (e.g., 12, 24, and 36 months) to assess the impact of the recommendations. Collect data on maternal health outcomes, including maternal mortality, antenatal care utilization, skilled birth attendance, and postnatal care.

6. Data analysis: Analyze the collected data using appropriate statistical methods. Compare the maternal health indicators between the intervention and control groups to determine the impact of the recommendations. Calculate measures such as relative difference, incidence rate ratio, and cost-effectiveness ratios.

7. Dissemination of results: Share the findings of the study through peer-reviewed publications, national and international conferences, workshops, and media outlets. Ensure that the results reach relevant stakeholders, including policymakers, researchers, and healthcare practitioners.

By following this methodology, researchers can simulate the impact of the recommendations on improving access to maternal health and provide evidence-based insights for future interventions and policy decisions.

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