Distance is “a big problem”: a geographic analysis of reported and modelled proximity to maternal health services in Ghana

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Study Justification:
This study aims to address the geographic barriers to healthcare in Ghana, particularly in relation to maternal health services. It compares reported distance challenges accessing healthcare with modelled travel times to evaluate their relationship with skilled birth attendance. The study also examines the socio-demographic factors associated with self-reported distance problems in accessing healthcare. By understanding the impact of geographic access on maternal health outcomes, this study provides valuable insights for improving healthcare delivery and reducing disparities.
Highlights:
– Women reporting distance challenges accessing healthcare had significantly longer travel times to the nearest health facility.
– Poverty significantly increased the odds of reporting challenges with distance, while living in urban areas and having health insurance reduced the odds.
– Women with a skilled attendant at birth, four or more skilled antenatal appointments, and timely skilled postnatal care had shorter travel times to the nearest health facility.
– Factors such as wealth, health insurance, higher education, living in urban areas, and completing four or more antenatal care appointments increased the odds of skilled birth attendance.
Recommendations:
– Recognize the differential impact of geographic access to healthcare on poor rural women in studies relying on modelled travel times.
– Scale up physical access to maternal health care in rural areas.
– Increase utilization of maternal health services by improving livelihoods.
Key Role Players:
– Ministry of Health: Responsible for policy development and implementation of strategies to improve maternal health services.
– Ghana Health Service: Provides oversight and coordination of health facilities and services.
– District Health Management Teams: Responsible for implementing and monitoring healthcare programs at the district level.
– Non-governmental Organizations (NGOs): Collaborate with the government to support maternal health initiatives and provide resources.
– Community Health Workers: Play a crucial role in delivering healthcare services and promoting awareness at the community level.
Cost Items for Planning Recommendations:
– Infrastructure Development: Construction and renovation of health facilities in rural areas.
– Transportation: Provision of ambulances and transportation services to improve access to healthcare.
– Training and Capacity Building: Training healthcare workers, including midwives and nurses, to provide skilled maternal health services.
– Health Education and Awareness Campaigns: Conducting community outreach programs to educate and raise awareness about the importance of maternal health services.
– Livelihood Improvement Programs: Implementing initiatives to improve the economic conditions of rural communities, thereby increasing their ability to access healthcare.
Please note that the provided cost items are general categories and not actual cost estimates. The actual budget would depend on various factors such as the scale of implementation, specific interventions, and local context.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, but there are some areas for improvement. The study design is cross-sectional, which limits the ability to establish causality. Additionally, the abstract does not provide information on the statistical significance of the findings. To improve the evidence, the study could consider using a longitudinal design to establish causality and provide p-values or confidence intervals for the reported associations.

Background: Geographic barriers to healthcare are associated with adverse maternal health outcomes. Modelling travel times using georeferenced data is becoming common in quantifying physical access. Multiple Demographic and Health Surveys ask women about distance-related problems accessing healthcare, but responses have not been evaluated against modelled travel times. This cross-sectional study aims to compare reported and modelled distance by socio-demographic characteristics and evaluate their relationship with skilled birth attendance. Also, we assess the socio-demographic factors associated with self-reported distance problems in accessing healthcare. Methods: Distance problems and socio-demographic characteristics reported by 2210 women via the 2017 Ghana Maternal Health Survey were included in analysis. Geospatial methods were used to model travel time to the nearest health facility using roads, rivers, land cover, travel speeds, cluster locations and health facility locations. Logistic regressions were used to predict skilled birth attendance and self-reported distance problems. Results: Women reporting distance challenges accessing healthcare had significantly longer travel times to the nearest health facility. Poverty significantly increased the odds of reporting challenges with distance. In contrast, living in urban areas and being registered with health insurance reduced the odds of reporting distance challenges. Women with a skilled attendant at birth, four or more skilled antenatal appointments and timely skilled postnatal care had shorter travel times to the nearest health facility. Generally, less educated, poor, rural women registered with health insurance had longer travel times to their nearest health facility. After adjusting for socio-demographic characteristics, the following factors increased the odds of skilled birth attendance: wealth, health insurance, higher education, living in urban areas, and completing four or more antenatal care appointments. Conclusion: Studies relying on modelled travel times to nearest facility should recognise the differential impact of geographic access to healthcare on poor rural women. Physical access to maternal health care should be scaled up in rural areas and utilisation increased by improving livelihoods.

The 2017 Ghana Maternal Health Survey (GMHS), a special DHS, sampled 25,062 women aged 15 to 49 years from 900 enumeration areas representative at national and regional levels [17]. The GMHS used a two staged cluster sample design with rural/urban stratification to collect data about women’s experiences and use of maternal health services between June and October 2017, achieving a 99% response rate. The GMHS also recorded the geographic location of clusters. This study includes information on women aged 15–49 who were asked about their last birth in the 5 years before the 2017 GMHS survey. Ghana Health Service (GHS) data on the location of health facilities providing birthing services in 2017 and spatial topographic data were used to model travel times. Spatial data representing terrain, land cover, roads, rivers/water bodies and topography were included to model the travel time to health facilities [26–28]. Travel time to the nearest health facilities providing birthing services was modelled in Accessmod version 5 [29], a free tool for measuring access to health services. To measure the travel time to each health facility, we first created an impedance cost surface (a gridded layer representing the difficulty of travel) by combining landcover, terrain, roads, and water bodies (e.g. rivers and lakes). Where roads of different classes met, the road with the maximum speed was prioritised. We assumed that patients would walk on all land cover types, then use mechanised transport on roads. Therefore, walking speeds were 5 kmh− 1 or less in forests, woodlands and croplands and other landcover types depending on how easily they can be traversed [30]. Following traffic regulations in Ghana, primary, secondary and tertiary roads were assigned 90 kmh− 1, 50 kmh− 1 and 30 kmh-1, respectively. The model ensures that the terrain’s steepness affects travel speed towards a health facility for persons walking or bicycling. Via the impedance surface, we estimated the travel times from each GMHS cluster location to the nearest health facility where birthing services are provided. Birth counts from routine GHS health data indicate health facilities providing birthing services. The longitudes and latitudes for DHS clusters are intentionally randomly displaced within two kilometres in urban clusters and five or up to ten in rural areas for data protection reasons. Therefore, we used two and five-kilometre buffers to compute the median travel times around urban and rural clusters respectively, calculating medians because travel times had skewed distributions within these buffers. These recommended distance buffers mitigate the likely effects of cluster displacement [31]. The DHS asks respondents if distance is a big problem in accessing healthcare when sick. The binary response from this question was the main outcome studied. The DHS questionnaire asked women the following question: “Many different factors can prevent women from getting medical advice or treatment for themselves. When you are sick and want to get medical advice or treatment, is each of the following a big problem or not a big problem: The distance to the health facility?” Response options: 1. Big problem 2. Not a big problem [32]. Secondly, we assessed the effect of proximity and socio-demographic variables on skilled birth attendance (SBA). For SBA, a woman was assisted by a skilled attendant if the most qualified person during childbirth was a midwife, doctor or nurse. The predictor variables were the number of antenatal care (ANC) appointments and postnatal care (PNC) within 48 hours after birth. Other variables included were age, rural-urban, wealth, region, health insurance and education [33]. In this study, ANC and PNC were defined as skilled if the service provider was a midwife, doctor or nurse. When two or more providers are present, the highest qualified service provider is used to classify skilled ANC and PNC. Based on the older WHO recommendation, the number of skilled ANC appointments were recoded into three (no ANC appointments, one to three, four or more) [34]. Similarly, timely PNC was defined as any woman who received a health check or visits from a skilled provider within 48 hours after delivery, while in the health facility or at home following delivery. The women’s ages were grouped into three classes (15 to 20 years, 21 to 30 years, 31 to 49 years). Household wealth quintiles were collapsed into three classes (poor, middle, and rich). We combined the “poorest” and “second” into “poor” and “fourth” plus “wealthiest” as “rich”. The DHS used household assets, livestock, drinking water source, type of toilet, type of cooking fuel, and building structure to construct the wealth index via a principal component analysis [35]. The highest education attained were recoded as no formal education, primary, secondary, and higher education. Due to the high proportion of missing values for women covered by health insurance, registration with a health insurance scheme was used as a proxy for insurance cover. The estimated median travel time between groups was reported with inter-quartile range (IQR). For categories with two levels, the differences in travel time were tested with the Wilcoxon rank sum test, whereas the Kruskal Wallis test was applied to groups with three or more levels. Non-parametric tests were chosen because the travel time distribution was skewed. To test for association between the reported distance and the independent variables, chi square tests were used. The descriptive statistics were presented in tables and plots to visualise the difference between groups. Logistic regression models were used to estimate the relationship between reported distance problems and SBA, controlling for socio-demographic and maternal health characteristics. The skilled birth outcome was chosen because it is the key determinant of maternal health outcomes [7]. Crude odds ratios were estimated between skilled birth attendance and each independent variable. All independent variables in the crude model associated with SBA at 10 % significance level were added to the adjusted models to allow for associations that can be insignificant in the crude model but change in the presence of other variables [36]. We tested all other associations at 5 % significance. Furthermore, a logistic regression analysis was conducted to estimate the relationship between socio-demographic backgrounds and reported challenges with distance. The outcome variable in this model was the binary self-reported distance. The independent variables were the socio-demographic variables and modelled travel time. Multicollinearity for both models was checked with a variance inflation factor threshold set at ten. We used the likelihood ratio test to compare the models. Finally, we included survey weights to correct for sampling and non-response error.

Based on the information provided, here are some potential innovations that could be used to improve access to maternal health:

1. Telemedicine: Implementing telemedicine services can allow pregnant women in remote areas to access healthcare consultations and advice remotely, reducing the need for travel to healthcare facilities.

2. Mobile clinics: Utilizing mobile clinics equipped with necessary medical equipment and staff can bring maternal health services closer to rural communities, making it easier for women to access care.

3. Community health workers: Training and deploying community health workers who can provide basic maternal health services, education, and referrals in remote areas can help bridge the gap in access to healthcare.

4. Transportation support: Establishing transportation support systems, such as ambulance services or transportation vouchers, can help pregnant women overcome geographical barriers and reach healthcare facilities in a timely manner.

5. Maternal health awareness campaigns: Conducting targeted awareness campaigns to educate women and their families about the importance of maternal health and the available services can help increase utilization of healthcare services.

6. Financial incentives: Providing financial incentives, such as cash transfers or subsidies, to pregnant women from low-income backgrounds can help alleviate the financial burden associated with accessing maternal health services.

7. Public-private partnerships: Collaborating with private healthcare providers to expand the reach of maternal health services in underserved areas can help improve access and reduce the burden on public healthcare facilities.

8. Improving infrastructure: Investing in the development and improvement of roads, bridges, and transportation networks in rural areas can facilitate easier access to healthcare facilities for pregnant women.

9. Mobile applications: Developing mobile applications that provide information on maternal health, appointment reminders, and access to telemedicine consultations can empower women to take control of their own healthcare and improve access.

10. Data-driven decision making: Utilizing geospatial data and modeling techniques, as demonstrated in the study, to identify areas with the greatest need for maternal health services and strategically allocate resources to improve access.

These innovations, when implemented effectively, can help address the geographic barriers to maternal health and improve access to essential healthcare services for pregnant women.
AI Innovations Description
Based on the information provided, the recommendation to improve access to maternal health in Ghana is to focus on scaling up physical access to maternal healthcare in rural areas and increasing utilization by improving livelihoods. This can be achieved by implementing the following strategies:

1. Improve infrastructure: Enhance the availability and quality of health facilities in rural areas by constructing new facilities, upgrading existing ones, and ensuring they are well-equipped to provide comprehensive maternal health services.

2. Expand transportation options: Enhance transportation networks in rural areas to facilitate easier access to health facilities. This can include improving road infrastructure, providing reliable public transportation services, and exploring innovative solutions such as mobile clinics or telemedicine.

3. Increase healthcare workforce: Address the shortage of skilled healthcare providers in rural areas by recruiting and training more midwives, doctors, and nurses. This can be done through targeted recruitment campaigns, offering incentives for healthcare professionals to work in rural areas, and providing ongoing training and support.

4. Strengthen health insurance coverage: Ensure that women in rural areas have access to affordable health insurance coverage, as this can help reduce financial barriers to accessing maternal healthcare services. This can be achieved by expanding health insurance schemes and implementing strategies to increase enrollment among rural populations.

5. Promote community engagement: Engage local communities in the planning, implementation, and monitoring of maternal health programs. This can include raising awareness about the importance of maternal health, addressing cultural and social barriers, and involving community leaders and traditional birth attendants in promoting safe birthing practices.

6. Improve livelihoods: Address the underlying socio-economic factors that contribute to limited access to maternal healthcare in rural areas. This can include implementing poverty reduction programs, providing income-generating opportunities, and improving access to education and basic amenities.

By implementing these recommendations, it is expected that access to maternal health services in rural areas of Ghana will be improved, leading to better maternal health outcomes and reduced disparities in healthcare access.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Improve infrastructure: Enhance the availability and quality of roads, bridges, and transportation systems to reduce travel time and improve access to maternal health facilities.

2. Increase the number of health facilities: Establish more health facilities, particularly in rural areas, to ensure that pregnant women have access to nearby maternal health services.

3. Strengthen community-based care: Implement community-based programs that provide maternal health services, such as antenatal care and postnatal care, closer to women’s homes, reducing the need for long-distance travel.

4. Enhance telemedicine services: Utilize technology to provide remote consultations and medical advice to pregnant women in remote areas, reducing the need for physical travel to health facilities.

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

1. Data collection: Gather data on the current state of maternal health services, including the location of health facilities, travel times, and socio-demographic characteristics of the population.

2. Modelling travel times: Use geospatial methods to model travel times to the nearest health facility, taking into account factors such as roads, rivers, land cover, and travel speeds. This can be done using tools like Accessmod.

3. Analyze reported distance problems: Compare the reported distance problems from the Ghana Maternal Health Survey with the modelled travel times to assess the accuracy of women’s perceptions of distance-related challenges.

4. Assess socio-demographic factors: Evaluate the socio-demographic factors associated with self-reported distance problems in accessing healthcare, such as poverty, urban/rural residence, and health insurance coverage.

5. Predict skilled birth attendance: Use logistic regression analysis to predict the likelihood of skilled birth attendance based on factors such as wealth, education, urban/rural residence, and access to maternal health services.

6. Evaluate the impact of recommendations: Simulate the impact of the recommended interventions by adjusting the modelled travel times based on the proposed improvements in infrastructure, availability of health facilities, community-based care, and telemedicine services. Assess the resulting changes in travel times and access to maternal health services.

7. Compare outcomes: Compare the predicted outcomes, such as improved access to maternal health services and increased skilled birth attendance, before and after implementing the recommendations to determine the potential impact of the interventions.

By following this methodology, policymakers and healthcare providers can gain insights into the potential benefits of different interventions and make informed decisions to improve access to maternal health services.

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