Impact of the community healthcare plan and the free maternity services programme on maternal and child healthcare utilisation in rural Kenya: A dairy farmer population-based study

African Health Sciences, Volume 19, No. 3, Year 2019

Ukuhunyushwa

Background: Access to and utilisation of quality maternal and child healthcare services is generally recognized as the best way to reduce maternal and child mortality. Objectives: We evaluated whether the introduction of a voluntary family health insurance programme, combined with quality improvement of healthcare facilities [The Community Health Plan (TCHP)], and the introduction of free access to delivery services in all public facilities [Free Maternity Services programme (FMS)] increased antenatal care utilisation and use of facility deliveries among pregnant women in rural Kenya. Methods: TCHP was introduced in 2011, whilst the FMS programme was launched in 2013. To measure the impact of TCHP, percentage points (PP) changes in antenatal care utilisation and facility deliveries from the pre-TCHP to the post-TCHP period between the TCHP programme area and a control area were compared in multivariable difference-in-differences analysis. To measure the impact of the FMS programme, PP changes in antenatal care utilisation and facility deliveries from the pre-FMS to the post-FMS period in the pooled TCHP programme and control areas was assessed in multivariable logistic regression analysis. Data was collected through household surveys in 2011 and 2104. Households (n=549) were randomly selected from the member lists of 2 dairy companies, and all full-term pregnancies in the 3.5 years preceding the baseline and follow-up survey among women aged 15-49 at the time of pregnancy were eligible for this study (n=295). Results: Because only 4.1% of eligible women were insured through TCHP during pregnancy, any increase in utilisation attributable to the TCHP programme could only have come about as a result of the quality improvements in TCHP facilities. Antenatal care utilisation significantly increased after TCHP was introduced (14.4 PP; 95% CI: 4.5–24.3; P=0.004), whereas no effect was observed of the programme on facility deliveries (8.8 PP; 95% CI: -14.1 to +31.7; P=0.450). Facility deliveries significantly increased after the introduction of the FMS programme (27.9 PP; 95% CI: 11.8–44.1; P=0.001), but antenatal care utilisation did not change significantly (4.0 PP; 95% CI: -0.6 to +8.5; P=0.088). Conclusion: Access to the FMS programme increased facility deliveries substantially and may contribute to improved maternal and new-born health and survival if the quality of delivery services is sustained or further improved. Despite low up-take, TCHP had a positive effect on antenatal care utilisation among uninsured women by improving the quality of existing healthcare facilities. An alignment of the two programmes could potentially lead to optimal results. Funding: The study was funded by the Health Insurance Fund (http://www.hifund.org/), through a grant from the Dutch Ministry of Foreign Affairs. Nandi County is situated in the Western region of Kenya with a total population of 752,965 based on the 2009 National Population and Housing Census. The 2008–2009 Kenyan demographic health survey reported that in Nandi County, 91.5% of women made at least one antenatal care visit with a skilled provider, as opposed to no visits or visits with a community health worker or traditional birth attendant, and 42.6% of women delivered in a healthcare facility.6 On 1 April 2011, TCHP began providing health insurance to dairy farmer households of Tanykina Dairy Company, a cooperative of dairy farmers in Nandi North (TCHP programme area). In the 2 months before the insurance was introduced, the programme facilitated quality improvements in 7 participating healthcare facilities (3 public, 3 private, and 1 public referral hospital). Dairy farmer households of Lelbren Dairy Company in Nandi East were chosen as the TCHP control study group, as they were comparable to dairy farmer households in the TCHP programme area in terms of socio-demographic and socio-economic characteristics. Before the introduction of the programme, the healthcare facilities in both areas provided similar quality services. Enrolment in the TCHP insurance scheme was voluntary and on a family basis. Covered maternity services included antenatal care, delivery including caesarean section, neonatal care, and pharmacy costs for prescribed medication. At the time of this study, the insurance premium was 300 Kenyan Shilling (KSh) for a basic package and 1,100 KSh for a comprehensive package per family per month, which corresponded to ∼0.9% and ∼3.3% of average monthly household consumption, respectively, among the surveyed households before the introduction of TCHP. The basic package gave access to out-patient primary and maternity care up to a referral level and the comprehensive package additionally gave access to inpatient care up to a referral level. Quality and efficiency of healthcare were monitored through independent audits by an international quality improvement and assessment body called SafeCare9, a partnership between the Pharm Access Foundation, the American Joint Commission International and the Council for Health Services Accreditation of Southern Africa. Prior to participation in TCHP, SafeCare would conduct a baseline assessment of a healthcare facility and formulate a quality improvement plan, which subsequently was implemented by the facility. Examples of quality improvement interventions included implementation of treatment guidelines and protocols for waste management, and hospital infection control, training of staff in guideline-based care and adequate medical file keeping, hospital renovation, upgrading of laboratory equipment, and training of laboratory staff in basic laboratory testing, and assurance of continuous essential drug supplies. SafeCare monitored the progress on quality improvement through annual follow-up assessments collecting scores using the SafeCare Quality Standards.10,11 On 1 June 2013, the national FMS programme was introduced by the Kenyan government. After the launch of the FMS programme delivery care services, including caesarean delivery, were free of charge in all public healthcare facilities (delivery costs would be reimbursed by the government directly to providers). It was assumed that the facilities would cover the costs of antenatal care visits from their FMS budget such that it would be free of charge to all pregnant women, as well. Additionally, women in the study area also had access to National Health Insurance Fund (NHIF) health insurance since 1966. At the time of this study, NHIF offered both in-patient and out-patient health insurance to all Kenyan citizens. The in-patient scheme was compulsory for formal sector workers and their family members and premiums were dependent on income, whereas for informal sector workers it was voluntary. The out-patient scheme was available for civil servants only. The inpatient scheme covered maternity services, comparable to the coverage under the TCHP scheme. Upon his re-election in October 2017, President Kenyatta indicated that he wanted all Kenyans to have comprehensive health insurance within 5 years. NHIF was tasked with this promise. Hereto, NHIF introduced SupaCover, a comprehensive health insurance package covering both outpatient and inpatient care to formal sector employees as well as the informal sector. We applied a quasi-experimental controlled before-after design to measure the impact of the TCHP programme 3.5 years after its introduction. Additionally, since the FMS programme was launched in the whole country, including in the TCHP control area, a before-after design was used to measure the effect of the FMS programme 1.5 years after it was launched. Based on the Tanykina and Lelbren Dairy Company member lists, a random representative sample of 1,200 households was drawn from the TCHP programme and control areas. A baseline survey was carried out among the 1,200 households in February 2011, shortly before the introduction of TCHP. A follow-up survey was carried out among a smaller random subsample of 549 households in November 2014. In this study we used the baseline and follow-up data of these 549 households only. A fixed sample size of 549 households would allow us to measure a minimum impact of a 12.7 percentage points (PP) increase in the outcomes, with a power of 80% using a twotailed test and a 0.05 level of significance. Households were included in the surveys after written informed consent was obtained from the individual adult household members. For members younger than 18 years consent was obtained from the household head. In addition, 25 in-depth stakeholder interviews about the TCHP, FMS, and NHIF programmes were conducted in November 2014. Stakeholder interviews were conducted with directors of healthcare facilities in Nandi County, government officials, and employees from Tanykina Dairy Company, TCHP, and NHIF. The 3.5 years prior to the baseline survey were defined as pre-TCHP period (1 September 2007–28 February 2011) and the 3.5 years after its introduction were defined as post-TCHP period (1 May 2011–31 October 2014). Within the post-TCHP period, the 2 years prior to the FMS programme was launched were defined as pre-FMS period (1 March 2011–31 May 2013) and the 1.5 years after its launch were defined as post-FMS period (1 June 2013–31 October 2014). All reported pregnancies and deliveries (full-term pregnancies) between 1 September 2007 and 31 October 2014 from women aged 15 to 49 years at the time of pregnancy were eligible for this study (repeated cross-sections). Ethical approval for the study was obtained from the Kenyan Medical Research Institute in Nairobi, Kenya (16/09/2014, KEMRI/RES/7/3/1). Antenatal care utilisation was defined as making at least 1 antenatal care visit at a healthcare facility and facility delivery was defined as delivery in any healthcare facility, as reported by the women during the household surveys. If a woman delivered twice during the follow-up-period (n=6), then only her most recent delivery was included in the analyses, as within the baseline-period only information of the last delivery was available. We measured the intention-to-treat impact of the TCHP programme as very few eligible women were enrolled in the TCHP insurance scheme during the post-TCHP period. All women living in the TCHP programme area had the opportunity to utilise improved quality maternal and child health services in the upgraded TCHP facilities, regardless their enrolment in the TCHP health insurance, although uninsured women had to pay for these services. The intention-to-treat approach considers all women to be in the intervention group irrespective of whether they were insured through the TCHP scheme, which therefore avoids the bias introduced by voluntary insurance uptake and incorporates the independent effect of the quality improvements on uninsured women. Difference-in-differences analysis wasused to estimate the intention-to-treat impact, as the percentage points (PP) change in antenatal care utilisation and facility deliveries from the pre-TCHP period to the post-TCHP period in the TCHP programme area, adjusted for the change in the TCHP control area (see the Supplementary Data for more information on the specified difference-in-differences model).11,12,13,14 As the FMS programme was introduced in both areas, the effect of the FMS programme was estimated by a before-after comparison of the outcome variables in the pooled TCHP programme and control areas. Logistic regression analysis was used to estimate the effect of the FMS programme,15 as the PP change in antenatal care utilisation and facility deliveries from the pre-FMS period to the post-FMS period (see the Supplementary Data for more information on the specified logistic model). The effect of being enrolled in NHIF health insurance was also estimated in this analysis. Since most women had mandatory insurance with NHIF through work in the formal sector, selection bias-as a result of women who enrolled in the NHIF insurance scheme because they expected to get pregnant in the near future and consequently wanted to use NHIF for maternal healthcare utilisation-does not pose a problem here. Confounders were selected based on Gabrysch and Campbell’s conceptual framework.16 This framework distinguishes four sets of variables related to maternal and child healthcare utilisation, namely perceived needs (age, parity, and complications during previous deliveries), socio-demographic factors (religion and ethnicity), socio-economic factors (marital status, female household head, educational level household head, household consumption, daily per capita consumption below US$2, and NHIF enrolment status), and physical accessibility (distance to nearest health facility). Educational level of the household head and household consumption were included at their baseline value to avoid endogeneity problems. In the multivariable analyses, all a-priori selected confounders were included, irrespective of whether they were statistically significant. In addition, all analyses were corrected for heteroscedasticity. Data was analysed using STATA, version 12.1 (StataCorp LP, College Station, Texas, USA).

I-AI Digest

Study Justification:

The study aimed to evaluate the impact of two healthcare programs, the Community Health Plan (TCHP) and the Free Maternity Services (FMS) program, on maternal and child healthcare utilization in rural Kenya. Access to quality healthcare services is crucial for reducing maternal and child mortality rates. The study aimed to assess whether these programs increased antenatal care utilization and facility deliveries among pregnant women in rural Kenya.

Highlights:

1. The introduction of the TCHP program led to a significant increase in antenatal care utilization among uninsured women. This increase can be attributed to the quality improvements in healthcare facilities.
2. The FMS program resulted in a substantial increase in facility deliveries. This program has the potential to improve maternal and newborn health and survival if the quality of delivery services is sustained or further improved.
3. The study suggests that aligning the TCHP and FMS programs could lead to optimal results in improving maternal and child healthcare utilization.

Recommendations:

1. Sustain and improve the quality of healthcare facilities to ensure the positive impact of the TCHP program on antenatal care utilization continues.
2. Strengthen the quality of delivery services to maximize the benefits of the FMS program in increasing facility deliveries.
3. Consider aligning the TCHP and FMS programs to enhance their effectiveness in improving maternal and child healthcare utilization.

Key Role Players:

1. Healthcare facilities: Responsible for providing quality healthcare services and implementing the recommended improvements.
2. TCHP and FMS program administrators: Oversee the implementation and coordination of the programs.
3. Government officials: Provide support and resources for the programs and ensure their sustainability.
4. Tanykina Dairy Company and Lelbren Dairy Company: Cooperatives of dairy farmers involved in the TCHP program.
5. Health Insurance Fund (HIF): Funded the study and may play a role in implementing the recommendations.

Cost Items for Planning Recommendations:

1. Quality improvement interventions in healthcare facilities: Includes training of staff, renovation, upgrading of equipment, and ensuring essential drug supplies.
2. Monitoring and assessment of healthcare quality: Involves independent audits and follow-up assessments by organizations like SafeCare.
3. Insurance premiums: Budgeting for the cost of health insurance coverage, such as the TCHP and NHIF schemes.
4. Reimbursement for delivery costs: Ensuring that healthcare facilities are reimbursed for the costs of delivery services under the FMS program.
5. Resource allocation for program coordination and administration: Funding the necessary personnel and infrastructure to oversee and manage the TCHP and FMS programs.
Please note that the provided cost items are general categories and not actual cost figures.

Amandla Obufakazi

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong, but there are some areas for improvement. The study design is quasi-experimental, which provides some level of control, but it would be stronger with a randomized controlled trial design. Additionally, the sample size of 549 households is relatively small, which may limit the generalizability of the findings. To improve the strength of the evidence, future studies could consider increasing the sample size and using a randomized controlled trial design.

Abstract

Nandi County is situated in the Western region of Kenya with a total population of 752,965 based on the 2009 National Population and Housing Census. The 2008–2009 Kenyan demographic health survey reported that in Nandi County, 91.5% of women made at least one antenatal care visit with a skilled provider, as opposed to no visits or visits with a community health worker or traditional birth attendant, and 42.6% of women delivered in a healthcare facility.6 On 1 April 2011, TCHP began providing health insurance to dairy farmer households of Tanykina Dairy Company, a cooperative of dairy farmers in Nandi North (TCHP programme area). In the 2 months before the insurance was introduced, the programme facilitated quality improvements in 7 participating healthcare facilities (3 public, 3 private, and 1 public referral hospital). Dairy farmer households of Lelbren Dairy Company in Nandi East were chosen as the TCHP control study group, as they were comparable to dairy farmer households in the TCHP programme area in terms of socio-demographic and socio-economic characteristics. Before the introduction of the programme, the healthcare facilities in both areas provided similar quality services. Enrolment in the TCHP insurance scheme was voluntary and on a family basis. Covered maternity services included antenatal care, delivery including caesarean section, neonatal care, and pharmacy costs for prescribed medication. At the time of this study, the insurance premium was 300 Kenyan Shilling (KSh) for a basic package and 1,100 KSh for a comprehensive package per family per month, which corresponded to ∼0.9% and ∼3.3% of average monthly household consumption, respectively, among the surveyed households before the introduction of TCHP. The basic package gave access to out-patient primary and maternity care up to a referral level and the comprehensive package additionally gave access to inpatient care up to a referral level. Quality and efficiency of healthcare were monitored through independent audits by an international quality improvement and assessment body called SafeCare9, a partnership between the Pharm Access Foundation, the American Joint Commission International and the Council for Health Services Accreditation of Southern Africa. Prior to participation in TCHP, SafeCare would conduct a baseline assessment of a healthcare facility and formulate a quality improvement plan, which subsequently was implemented by the facility. Examples of quality improvement interventions included implementation of treatment guidelines and protocols for waste management, and hospital infection control, training of staff in guideline-based care and adequate medical file keeping, hospital renovation, upgrading of laboratory equipment, and training of laboratory staff in basic laboratory testing, and assurance of continuous essential drug supplies. SafeCare monitored the progress on quality improvement through annual follow-up assessments collecting scores using the SafeCare Quality Standards.10,11 On 1 June 2013, the national FMS programme was introduced by the Kenyan government. After the launch of the FMS programme delivery care services, including caesarean delivery, were free of charge in all public healthcare facilities (delivery costs would be reimbursed by the government directly to providers). It was assumed that the facilities would cover the costs of antenatal care visits from their FMS budget such that it would be free of charge to all pregnant women, as well. Additionally, women in the study area also had access to National Health Insurance Fund (NHIF) health insurance since 1966. At the time of this study, NHIF offered both in-patient and out-patient health insurance to all Kenyan citizens. The in-patient scheme was compulsory for formal sector workers and their family members and premiums were dependent on income, whereas for informal sector workers it was voluntary. The out-patient scheme was available for civil servants only. The inpatient scheme covered maternity services, comparable to the coverage under the TCHP scheme. Upon his re-election in October 2017, President Kenyatta indicated that he wanted all Kenyans to have comprehensive health insurance within 5 years. NHIF was tasked with this promise. Hereto, NHIF introduced SupaCover, a comprehensive health insurance package covering both outpatient and inpatient care to formal sector employees as well as the informal sector. We applied a quasi-experimental controlled before-after design to measure the impact of the TCHP programme 3.5 years after its introduction. Additionally, since the FMS programme was launched in the whole country, including in the TCHP control area, a before-after design was used to measure the effect of the FMS programme 1.5 years after it was launched. Based on the Tanykina and Lelbren Dairy Company member lists, a random representative sample of 1,200 households was drawn from the TCHP programme and control areas. A baseline survey was carried out among the 1,200 households in February 2011, shortly before the introduction of TCHP. A follow-up survey was carried out among a smaller random subsample of 549 households in November 2014. In this study we used the baseline and follow-up data of these 549 households only. A fixed sample size of 549 households would allow us to measure a minimum impact of a 12.7 percentage points (PP) increase in the outcomes, with a power of 80% using a twotailed test and a 0.05 level of significance. Households were included in the surveys after written informed consent was obtained from the individual adult household members. For members younger than 18 years consent was obtained from the household head. In addition, 25 in-depth stakeholder interviews about the TCHP, FMS, and NHIF programmes were conducted in November 2014. Stakeholder interviews were conducted with directors of healthcare facilities in Nandi County, government officials, and employees from Tanykina Dairy Company, TCHP, and NHIF. The 3.5 years prior to the baseline survey were defined as pre-TCHP period (1 September 2007–28 February 2011) and the 3.5 years after its introduction were defined as post-TCHP period (1 May 2011–31 October 2014). Within the post-TCHP period, the 2 years prior to the FMS programme was launched were defined as pre-FMS period (1 March 2011–31 May 2013) and the 1.5 years after its launch were defined as post-FMS period (1 June 2013–31 October 2014). All reported pregnancies and deliveries (full-term pregnancies) between 1 September 2007 and 31 October 2014 from women aged 15 to 49 years at the time of pregnancy were eligible for this study (repeated cross-sections). Ethical approval for the study was obtained from the Kenyan Medical Research Institute in Nairobi, Kenya (16/09/2014, KEMRI/RES/7/3/1). Antenatal care utilisation was defined as making at least 1 antenatal care visit at a healthcare facility and facility delivery was defined as delivery in any healthcare facility, as reported by the women during the household surveys. If a woman delivered twice during the follow-up-period (n=6), then only her most recent delivery was included in the analyses, as within the baseline-period only information of the last delivery was available. We measured the intention-to-treat impact of the TCHP programme as very few eligible women were enrolled in the TCHP insurance scheme during the post-TCHP period. All women living in the TCHP programme area had the opportunity to utilise improved quality maternal and child health services in the upgraded TCHP facilities, regardless their enrolment in the TCHP health insurance, although uninsured women had to pay for these services. The intention-to-treat approach considers all women to be in the intervention group irrespective of whether they were insured through the TCHP scheme, which therefore avoids the bias introduced by voluntary insurance uptake and incorporates the independent effect of the quality improvements on uninsured women. Difference-in-differences analysis wasused to estimate the intention-to-treat impact, as the percentage points (PP) change in antenatal care utilisation and facility deliveries from the pre-TCHP period to the post-TCHP period in the TCHP programme area, adjusted for the change in the TCHP control area (see the Supplementary Data for more information on the specified difference-in-differences model).11,12,13,14 As the FMS programme was introduced in both areas, the effect of the FMS programme was estimated by a before-after comparison of the outcome variables in the pooled TCHP programme and control areas. Logistic regression analysis was used to estimate the effect of the FMS programme,15 as the PP change in antenatal care utilisation and facility deliveries from the pre-FMS period to the post-FMS period (see the Supplementary Data for more information on the specified logistic model). The effect of being enrolled in NHIF health insurance was also estimated in this analysis. Since most women had mandatory insurance with NHIF through work in the formal sector, selection bias-as a result of women who enrolled in the NHIF insurance scheme because they expected to get pregnant in the near future and consequently wanted to use NHIF for maternal healthcare utilisation-does not pose a problem here. Confounders were selected based on Gabrysch and Campbell’s conceptual framework.16 This framework distinguishes four sets of variables related to maternal and child healthcare utilisation, namely perceived needs (age, parity, and complications during previous deliveries), socio-demographic factors (religion and ethnicity), socio-economic factors (marital status, female household head, educational level household head, household consumption, daily per capita consumption below US$2, and NHIF enrolment status), and physical accessibility (distance to nearest health facility). Educational level of the household head and household consumption were included at their baseline value to avoid endogeneity problems. In the multivariable analyses, all a-priori selected confounders were included, irrespective of whether they were statistically significant. In addition, all analyses were corrected for heteroscedasticity. Data was analysed using STATA, version 12.1 (StataCorp LP, College Station, Texas, USA).

Izinto zokwakha

N/A

Emisha

Based on the study, the recommendation to improve access to maternal health is to align and integrate the two programs, The Community Health Plan (TCHP) and the Free Maternity Services (FMS) program. This can be done by ensuring that the quality improvements in healthcare facilities under TCHP are sustained or further improved, while also providing free access to delivery services in all public facilities under the FMS program. By aligning and integrating these two programs, it is possible to achieve optimal results in improving access to maternal health, leading to improved maternal and newborn health and survival.

AI Innovations Description

The recommendation to improve access to maternal health based on the study is to align and integrate the two programs, The Community Health Plan (TCHP) and the Free Maternity Services (FMS) program. The study found that TCHP had a positive effect on antenatal care utilization among uninsured women by improving the quality of existing healthcare facilities. On the other hand, the FMS program significantly increased facility deliveries. By aligning and integrating these two programs, it is possible to achieve optimal results in improving access to maternal health. This could be done by ensuring that the quality improvements in healthcare facilities under TCHP are sustained or further improved, while also providing free access to delivery services in all public facilities under the FMS program. This alignment and integration would contribute to improved maternal and newborn health and survival.

AI Innovations Methodology

To simulate the impact of the main recommendations on improving access to maternal health, the following methodology can be used:

1. Identify the target population: Determine the specific population that will be the focus of the simulation, such as pregnant women in rural areas of Nandi County, Kenya.

2. Define the intervention: Clearly define the intervention to be simulated, which is the alignment and integration of the Community Health Plan (TCHP) and the Free Maternity Services (FMS) program.

3. Data collection: Collect relevant data on antenatal care utilization and facility deliveries from the pre-TCHP and pre-FMS periods. This data can be obtained from the baseline survey conducted in February 2011 and the follow-up survey conducted in November 2014.

4. Select control and intervention groups: Identify a control group that did not receive the intervention (TCHP and FMS programs) and an intervention group that received the integrated programs. The control group can be dairy farmer households of Lelbren Dairy Company in Nandi East, while the intervention group can be dairy farmer households of Tanykina Dairy Company in Nandi North.

5. Analyze the impact of TCHP: Use a multivariable difference-in-differences analysis to compare the percentage point changes in antenatal care utilization and facility deliveries between the pre-TCHP and post-TCHP periods in the TCHP program area and the control area. Adjust for confounding factors such as age, parity, complications during previous deliveries, religion, ethnicity, marital status, educational level, household consumption, NHIF enrollment status, and distance to the nearest health facility.

6. Analyze the impact of FMS: Use multivariable logistic regression analysis to assess the percentage point changes in antenatal care utilization and facility deliveries between the pre-FMS and post-FMS periods in the pooled TCHP program and control areas. Adjust for confounding factors as mentioned above.

7. Simulate the impact of alignment and integration: Based on the findings from the analysis, simulate the impact of aligning and integrating the TCHP and FMS programs. This can be done by estimating the potential increase in antenatal care utilization and facility deliveries that could be achieved by aligning the quality improvements in healthcare facilities under TCHP with the provision of free delivery services in all public facilities under the FMS program.

8. Evaluate the results: Assess the simulated impact of the alignment and integration of the programs on improving access to maternal health. Compare the simulated results with the actual findings from the study to validate the effectiveness of the recommendations.

9. Draw conclusions and make recommendations: Based on the simulated impact, draw conclusions about the potential benefits of aligning and integrating the TCHP and FMS programs. Make recommendations for implementing this alignment and integration in order to improve access to maternal health in the target population.

It is important to note that this methodology is a general framework and may need to be adapted based on the specific data and context of the study.

Umbhali

Dima Health

Statistics:

Citations: 3

Identifiers:

DOI: 10.4314/ahs.v19i3.36

ISSN: 16806905

Research Areas:

Community Interventions, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants

Study Countries:

Kenya

Study Design:

Cohort Study, Cross Sectional Study, Quasi Experimental Study, randomised-control-trial

Study Approach:

Mixed-methods, Qualitative, Quantitative

Participants Gender:

Female

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