Incentives to yield to Obstetric Referrals in deprived areas of Amansie West district in the Ashanti Region, Ghana

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Study Justification:
– Obstetric referrals are crucial for ensuring safe delivery and reducing maternal and child mortalities.
– The efficiency of obstetric referral systems is hindered by lack of accessible transportation and socio-economic disparities in healthcare access.
– This study aimed to evaluate the role of socio-economic factors, perception, and transport availability in honoring obstetric referrals in deprived areas of the Amansie West district in Ghana.
Study Highlights:
– The study involved 720 confirmed pregnant women randomly sampled from five sub-districts in the Amansie West district.
– Data were collected through structured questionnaires and analyzed using statistical software.
– Logistic regression models were used to determine the influence of socio-demographic characteristics and pregnancy history on obstetric referrals.
– Results showed that 21.7% of the women honored referrals, while others refused due to lack of money (58%) and lack of transport (17%).
– Higher household wealth quintile and perception of disease condition as emergencies and severe increased the odds of honoring obstetric referrals.
Recommendations for Lay Reader and Policy Maker:
– Clients’ perceptions about the severity of health conditions and low income are barriers to seeking healthcare and honoring obstetric referrals in deprived areas.
– Implementing social interventions could improve the situation and help achieve maternal health targets in deprived areas.
– Policies should focus on improving transportation infrastructure and accessibility, as well as addressing socio-economic disparities in healthcare access.
– Awareness campaigns should be conducted to educate pregnant women about the importance of honoring obstetric referrals and available support services.
Key Role Players:
– Ministry of Health: Responsible for implementing policies and interventions to improve obstetric referral systems.
– District Health Directorate: Coordinates healthcare services and ensures the availability of transportation for obstetric referrals.
– Community Health Workers: Provide education and support to pregnant women, emphasizing the importance of honoring referrals.
– Non-Governmental Organizations: Collaborate with the government to implement social interventions and support healthcare services.
Cost Items for Planning Recommendations:
– Transportation infrastructure improvement: Includes road construction, maintenance, and provision of ambulances or other means of transportation.
– Awareness campaigns: Costs associated with designing and disseminating educational materials, organizing community meetings, and conducting media campaigns.
– Training and capacity building: Expenses related to training healthcare workers and community health workers on obstetric referrals and providing support services.
– Social interventions: Funding for programs aimed at addressing socio-economic disparities, such as income support or financial assistance for healthcare expenses.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is relatively strong, but there are some areas for improvement. The study design is clearly described as a cross-sectional study, and the sample size and data collection methods are provided. The logistic regression models are used to analyze the data. However, there are some limitations to consider. The study only focuses on one district in Ghana, which may limit the generalizability of the findings. Additionally, the abstract does not provide information on the response rate or potential biases in the sample. To improve the evidence, it would be helpful to include information on the response rate and any potential biases in the sample. Additionally, conducting a multi-district study could increase the generalizability of the findings.

Background: Obstetric referrals, otherwise known as maternal referrals constitute an eminent component of emergency care, and key to ensuring safe delivery and reducing maternal and child mortalities. The efficiency of Obstetric referral systems is however marred by the lack of accessible transportation and socio-economic disparities in access to healthcare. This study evaluated the role of socio-economic factors, perception and transport availability in honouring Obstetric referrals from remote areas to referral centres. Methods: This was a cross-sectional study, involving 720 confirmed pregnant women randomly sampled from five (5) sub-districts in the Amansie west district in Ghana, from February to May 2015. Data were collected through structured questionnaire using face-to-face interviewing and analyzed using STATA 11.0 for windows. Logistic regression models were fitted to determine the influence of socio-demographic characteristics and pregnancy history on obstetric referrals. Results: About 21.7 % of the women studied honoured referral by a community health worker to the next level of care. Some of the pregnant women however refused referrals to the next level due to lack of money (58 %) and lack of transport (17 %). A higher household wealth quintile increased the odds of being referred and honouring referral as compared to those in the lowest wealth quintile. Women who perceived their disease conditions as emergencies and severe were also more likely to honour obstetric referrals (OR = 2.3; 95 % CI = 1.3, 3.9). Conclusion: Clients’ perceptions about severity of health condition and low income remain barriers to seeking healthcare and disincentives to honour obstetric referrals in a setting with inequitable access to healthcare. Implementing social interventions could improve the situation and help attain maternal health targets in deprived areas.

A cross-sectional study, which employed quantitative methods, was conducted from February to May 2015 in the Amansie West district in the Ashanti region, Ghana. The district, which has Manso Nkwanta as its capital is one of the 35 districts in the region. It is about 1,364 sq km in size and uniformly rural and deprived. The topography is characterised by waterlogged and dust during the wet and dry seasons respectively. The large expanse of land coupled with rugged relief makes transporting emergencies cases very difficult and sometimes impossible. It takes an average of 5–7 h to transport emergency case from the remote areas to the district hospital at Agroyesum or nearby district hospitals. There is a burden of heavy workload on the few available health staff. The district has a projected population of 149,437 as at 2014 with an annual growth rate of 2.7 %. There are currently 22 health facilities and 54 functional CHPS zones. The doctor to population ratio is 1: 74,719; nurse to population ratio 1:2, 767 and midwife to women in fertility age (WIFA) ratio is 1:4,528. There is a high rate of illiteracy (70 %) and a high dropout rate in schools especially among girls. These conditions are possible risk factors for teenage pregnancies and obstetric complications [16]. The study population consisted of diagnosed second trimester pregnant women presenting at the antenatal clinic who provided written informed consent and satisfying the group-based inclusion criteria. A multi-stage sampling technique was employed for this study. The antenatal clinics in the study communities were selected from numbers 1 to 10, without replacement by research assistants. At the selected community antenatal clinic, systematic random sampling, guided by a sampling interval (estimated as the required sample size divided by the total attendants), was used to select the required subjects for the study. The sample size was estimated with recourse to Cochran (1977) [17]. Using this formula, and assuming access to referral service at 50 % and a non-response of 20 %, a total of 720 pregnant women were sampled from five towns; one each from the five sub-districts to participate in the study. The required respondents from selected health facilities were proportional to size of total eligible population per community. The distribution of respondents according to the sub district was Manso Nkwanta 120, Edubia 141, Agroyesum114, Antoakrom 140 and Esuowin 205, Table 1. Sample distribution from the study communities A structured questionnaire was used to elicit information on respondents’ socio-demographic and socio-economic characteristics, pregnancy history, experiences and perceptions of obstetric referrals. The questionnaires were pretested among 20 respondents in a sub-district with similar characteristics like the study sub-districts to check for clarity, consistency, and acceptability. The pretested sub-district was excluded from the study to avoid spill over effects. Questionnaires were interviewer administered and the interview results from the field were checked for completeness and internal errors prior to data entry. Data entry and preliminary analysis were done in EPIDATA and more detailed analysis done with Stata 11.0 for windows [18]. Descriptive statistics were summarized and displayed in graphs and charts. Verified data were cleaned on a regular basis through running programmes on legal values and consistency checks. Data analysis consisted of descriptive statistics, checking of potential assumption violations and testing of the study hypothesis. Continuous variables were compared using student t-test and discrete variables analyzed using χ2 in r X n tables. Logistic regression models were fitted to determine the influence of socio-demographic characteristics and pregnancy history on obstetric referrals, and to control for covariates. The binary outcome (obstetric referral) was based on respondents’ response to the question on whether they honoured referrals for obstetric reasons to the secondary level or not. Two models were fitted; model 1 consisted of only socio-economic variables (education, employment, length of stay in community, household wealth and self-rated socio-economic status) and model 2 involved the addition of pregnancy history (miscarriages and still births) and perception of disease condition. Variables in the multivariable analysis were selected based on p-value of less than 0.250 in the univariable analyses. For all analysis, a 2-tailed α with p < 0.05 was considered statistically significant.

Based on the information provided, here are some potential innovations that could improve access to maternal health in deprived areas of the Amansie West district in Ghana:

1. Mobile Obstetric Referral Units: Implementing mobile units equipped with medical professionals and necessary equipment to provide obstetric care and transport pregnant women from remote areas to referral centers.

2. Community-Based Transportation Services: Establishing community-based transportation services, such as ambulances or vehicles, to ensure that pregnant women have access to transportation when they need to be referred to higher-level healthcare facilities.

3. Financial Incentives: Introducing financial incentives, such as cash transfers or subsidies, to help pregnant women overcome the barrier of lack of money and encourage them to honor obstetric referrals.

4. Awareness Campaigns: Conducting targeted awareness campaigns to educate pregnant women and their families about the importance of obstetric referrals and the potential risks of not seeking timely medical care.

5. Telemedicine and Teleconsultation: Utilizing telemedicine and teleconsultation services to connect healthcare professionals in referral centers with pregnant women in remote areas, allowing for remote diagnosis and guidance, reducing the need for physical referrals.

6. Strengthening Community Health Worker Programs: Investing in training and capacity building for community health workers to improve their ability to identify high-risk pregnancies and effectively refer pregnant women to appropriate healthcare facilities.

7. Public-Private Partnerships: Collaborating with private sector organizations to improve transportation infrastructure and services in deprived areas, ensuring reliable and accessible transportation for obstetric referrals.

8. Maternal Health Insurance: Introducing or expanding maternal health insurance schemes to provide financial protection and coverage for obstetric referrals, reducing the financial burden on pregnant women and their families.

9. Improving Health Facility Infrastructure: Investing in the improvement of health facility infrastructure, including the construction or renovation of maternity wards and delivery rooms, to ensure that referral centers have the capacity to provide quality obstetric care.

10. Strengthening Data Collection and Monitoring Systems: Implementing robust data collection and monitoring systems to track obstetric referrals, identify barriers, and evaluate the effectiveness of interventions, enabling evidence-based decision-making and continuous improvement.
AI Innovations Description
The recommendation that can be developed into an innovation to improve access to maternal health is to implement social interventions that address the barriers faced by pregnant women in deprived areas. This can include providing incentives to encourage pregnant women to yield to obstetric referrals, particularly in areas with limited transportation and socio-economic disparities in access to healthcare.

The study conducted in the Amansie West district in Ghana found that lack of money and lack of transport were common reasons for pregnant women refusing obstetric referrals. Therefore, implementing social interventions such as providing financial assistance or transportation support could help overcome these barriers and encourage pregnant women to honor obstetric referrals.

Additionally, the study found that women who perceived their disease conditions as emergencies and severe were more likely to honor obstetric referrals. This suggests that improving awareness and education about the importance of obstetric referrals and the potential risks of not seeking appropriate care could also be an effective strategy.

Overall, by addressing the socio-economic factors, perception, and transport availability, social interventions can help improve access to maternal health in deprived areas and contribute to reducing maternal and child mortalities.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health in deprived areas of the Amansie West district in Ghana:

1. Improve transportation infrastructure: Address the lack of accessible transportation by investing in infrastructure development, such as roads and ambulances, to ensure timely and efficient transportation of pregnant women to referral centers.

2. Financial incentives: Introduce financial incentives, such as cash transfers or subsidies, to help pregnant women overcome the barrier of lack of money and encourage them to honor obstetric referrals.

3. Community awareness and education: Conduct community awareness campaigns to educate pregnant women and their families about the importance of obstetric referrals and the potential risks of not seeking timely healthcare. This can help change perceptions and increase the likelihood of honoring referrals.

4. Strengthen referral systems: Enhance the coordination and communication between community health workers and referral centers to ensure a smooth and efficient referral process. This can include training programs, improved documentation, and regular feedback mechanisms.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define indicators: Identify key indicators to measure the impact of the recommendations, such as the percentage of pregnant women honoring obstetric referrals, the time taken to transport emergency cases, and the number of maternal and child mortalities.

2. Data collection: Collect baseline data on the current state of access to maternal health in the Amansie West district, including information on transportation availability, socio-economic factors, and perception of obstetric referrals. This can be done through surveys, interviews, and existing data sources.

3. Modeling and simulation: Use statistical modeling techniques, such as logistic regression or simulation models, to analyze the collected data and simulate the impact of the recommendations. This can involve creating scenarios where the recommendations are implemented and assessing the potential changes in the identified indicators.

4. Evaluation and validation: Evaluate the results of the simulation and validate them against real-world data, if available. This can help assess the reliability and accuracy of the simulation model.

5. Policy recommendations: Based on the simulation results, provide policy recommendations on the most effective interventions to improve access to maternal health in the Amansie West district. Consider the feasibility, cost-effectiveness, and sustainability of the recommendations.

6. Implementation and monitoring: Implement the recommended interventions and establish a monitoring system to track the progress and impact of the implemented measures. Regularly evaluate and adjust the interventions based on the monitoring results to ensure continuous improvement.

It is important to note that the methodology described above is a general framework and may need to be adapted and customized based on the specific context and available resources in the Amansie West district.

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