An assessment of out of pocket payments in public sector health facilities under the free maternal healthcare policy in Ghana

listen audio

Study Justification:
– The study aimed to assess the prevalence of out of pocket (OOP) payments among pregnant women with valid national health insurance who sought skilled delivery services at public sector health facilities in Ghana.
– The study also aimed to identify health system factors associated with OOP payment.
– The findings of the study provide evidence of the high prevalence of OOP payment among women who had skilled delivery services in public sector health facilities, despite having valid national health insurance.
– The study highlights the need for measures to reduce OOP payment in public sector facilities, especially at hospitals and for women undergoing caesarean sections.
Study Highlights:
– The prevalence of OOP payment for skilled delivery services was found to be 19.0%.
– Hospital delivery services, caesarean section, and receiving intravenous infusion during delivery were associated with higher odds of OOP payment.
– Women who were discharged home 2 to 7 days after delivery had 19% lower odds of OOP payment compared to those discharged within 24 hours after delivery.
– The study provides important evidence on the challenges faced by pregnant women in accessing free maternal healthcare services in Ghana.
Recommendations for Lay Reader and Policy Maker:
– The government should institute measures to reduce OOP payment in public sector health facilities, particularly at hospitals and for women undergoing caesarean sections.
– Efforts should be made to ensure that pregnant women with valid national health insurance are not burdened with additional out of pocket expenses.
– Policies should be implemented to improve access to skilled delivery services and reduce financial barriers for pregnant women in Ghana.
– Further research is needed to explore the underlying reasons for the high prevalence of OOP payment and to identify additional strategies to address this issue.
Key Role Players:
– Government health agencies and policymakers
– National health insurance scheme administrators
– Public sector health facility administrators and staff
– Maternal health advocacy groups and NGOs
– Researchers and academics in the field of maternal health
Cost Items for Planning Recommendations:
– Training and capacity building for health facility staff on the implementation of measures to reduce OOP payment
– Development and implementation of information campaigns to educate pregnant women about their rights and entitlements under the free maternal healthcare policy
– Strengthening of health information systems to monitor and evaluate the impact of interventions aimed at reducing OOP payment
– Research funding for further studies on the prevalence and determinants of OOP payment in maternal healthcare services
– Collaboration and coordination costs between different stakeholders involved in implementing the recommendations

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it is based on a large sample size (7681 women) and utilizes multivariable logistic regression analysis to assess factors associated with out of pocket (OOP) payment. The study also accounts for clustering, stratification, and sampling weights. However, to improve the evidence, the abstract could provide more information on the representativeness of the sample and the generalizability of the findings. Additionally, it would be helpful to include information on the statistical significance of the associations found in the study.

Background: The free maternal healthcare policy was introduced in Ghana in 2008 under the national health insurance scheme as a social intervention to improve access to maternal health services. This study investigated the prevalence of out of pocket (OOP) payment among pregnant women with valid national health insurance who sought skilled delivery services at public sector health facilities in Ghana. The study also assessed the health system factors associated with OOP payment. Methods: We used data from the Ghana Maternal Health Survey (GMHS), which was conducted in 2017. The study comprised 7681 women who delivered at a public sector health facility and had valid national health insurance at the time of delivery. We used multivariable logistic regression analysis to assess factors associated with OOP payment, whiles accounting for clustering, stratification, and sampling weights. Results: The prevalence of OOP payment for skilled delivery services was 19.0%. After adjustment at multivariable level, hospital delivery services (adjusted Odds Ratio [aOR] = 1.23, 95% Confidence Interval [CI] = 1.00, 1.52), caesarean section (aOR = 1.73, 95% CI = 1.36, 2.20), and receiving intravenous infusion during delivery (aOR = 1.31, 95% CI = 1.08, 1.60) were associated with higher odds of OOP payment. Women who were discharged home 2 to 7 days after delivery had 19% lower odds of OOP payment compared to those who were discharged within 24 hours after delivery. Conclusion: This study provides evidence of high prevalence of OOP payment among women who had skilled delivery services in public sector health facilities although such women had valid national health insurance. Government may need to institute measures to reduce OOP payment in public sector facilities especially at the hospitals and for women undergoing caesarean sections.

Data for the study was extracted from the Ghana Maternal Health Survey (GMHS), which was conducted in 2017. The survey was conducted by Ghana Statistical Service (GSS) with technical support from Inner City Fund (ICF) through the Demographic and Health Survey (DHS) program. GMHS used a multi-stage sampling where the first stage involved the selection of enumeration areas with probability proportional to the sizes of enumeration areas. In the second stage, households were selected from each enumeration area using systematic random sampling. Details of the sampling procedure is publicly available [24]. The 2017 GMHS was conducted among women aged 15–49 years who delivered a live birth or stillbirth from the period between 2012 to 2017. Our study population were women aged 15–49 years who delivered at a public sector health facility in Ghana and had valid national health insurance at the time of delivery. Women who delivered at a private sector health facility or at home were excluded from the study. Pregnant women who had a private health insurance or did not have any health insurance at the time of delivery were also excluded from the study. Our total sample size was 7681 women. Our outcome variable of interest was OOP payment from a mother with a valid health insurance card during skilled delivery  at public sector health facility. A valid health insurance was an active health insurance with the national health insurance scheme at the time of receiving skilled delivery service. The outcome variable was generated out of three forms of OOP payment; payment to see a doctor/midwife/nurse, payment for laboratory services and payment for medicines. Pregnant women who paid for anyone of these three were categorized as OOP payment, otherwise they were categorized as not having made OOP payment. The outcome was coded as a dummy variable “1 for yes and 0 for no”. The primary independent variables of interest were type of health facility, forceps or vacuum delivery, blood transfusion during delivery, intravenous infusion during delivery, delivery by caesarean section and length of stay after delivery. Type of health facility was categorized as (hospital, health center/clinic/Community-based Health Planning and Services (CHPS) compound); forceps or vacuum delivery (yes, no); blood transfusion during delivery (yes, no); intravenous infusion during delivery (yes, no); delivery by caesarean section (yes, no), and length of stay after delivery (24 hours, 2 to 7 days and more than a week). The secondary independent variables of interest were place of residence (urban, rural); age category (15–19, 20–34, 35–49); parity (primiparous, multiparous); education (no formal education, primary education, secondary education, higher education) and wealth (poor, middle, rich). The variable selection was based on literature review [19], and their availability in the GMHS dataset [13]. Data analysis was conducted using Stata/SE 14.0 (Stata Corp LLC, College Station, Texas USA). Descriptive statistics was used to assess the prevalence of OOP payment and characteristics of the study population. We conducted bivariate analysis using logistic regression to assess the relationship between independent variables and OOP payment. A statistical significance of p-value < 0.05 was set for inclusion of independent variables into the multivariable logistic regression model. Adjusted odds ratios (aORs) at 95% confidence interval (CI) were estimated. We accounted for clustering, stratification, and sampling weights in all our analysis because of the complex sampling design.

N/A

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

1. Strengthening the National Health Insurance Scheme: The government could focus on improving the coverage and effectiveness of the national health insurance scheme to ensure that pregnant women have access to affordable and comprehensive maternal health services without incurring out-of-pocket expenses.

2. Implementing Cashless Systems: Introducing cashless payment systems in public sector health facilities could help reduce the prevalence of out-of-pocket payments. This could involve using electronic payment methods or integrating health insurance cards with payment systems to streamline the billing process and eliminate the need for direct payments.

3. Increasing the Availability of Skilled Birth Attendants: Ensuring that there are an adequate number of skilled birth attendants in public sector health facilities can improve access to safe and quality maternal health services. This could involve training and deploying more midwives and other healthcare professionals to areas with limited access to skilled birth attendants.

4. Improving Health Facility Infrastructure: Investing in the improvement of health facility infrastructure, particularly in hospitals, can help reduce the need for referrals and out-of-pocket payments for services such as caesarean sections. Upgrading facilities to meet the necessary standards for safe deliveries can contribute to better maternal health outcomes.

5. Enhancing Community-Based Maternal Health Programs: Implementing community-based programs that focus on maternal health education, awareness, and support can help improve access to maternal health services. These programs can provide information on the importance of antenatal care, skilled deliveries, and postnatal care, as well as facilitate transportation and referrals for pregnant women in remote areas.

6. Strengthening Monitoring and Evaluation Systems: Establishing robust monitoring and evaluation systems can help identify gaps and challenges in the provision of maternal health services. This can enable policymakers to make evidence-based decisions and allocate resources effectively to address the specific needs of pregnant women.

It is important to note that these recommendations are based on the information provided and may need to be further assessed and tailored to the specific context and needs of Ghana’s maternal health system.
AI Innovations Description
Based on the findings of the study, the following recommendation can be developed into an innovation to improve access to maternal health:

1. Implement measures to reduce out-of-pocket (OOP) payments in public sector health facilities, especially at hospitals and for women undergoing caesarean sections. This can be achieved by:
– Increasing funding for maternal health services to cover the costs of skilled delivery services, including caesarean sections.
– Strengthening the implementation of the free maternal healthcare policy to ensure that women with valid national health insurance are not required to make OOP payments.
– Providing financial incentives to public sector health facilities to discourage the collection of OOP payments from women with valid health insurance.

2. Improve the availability and accessibility of skilled delivery services in public sector health facilities. This can be done by:
– Increasing the number of skilled healthcare providers, such as doctors, midwives, and nurses, in public sector health facilities.
– Ensuring that public sector health facilities have the necessary equipment and supplies for safe deliveries, including forceps or vacuum delivery, blood transfusion, and intravenous infusion.
– Reducing the length of stay after delivery to minimize the financial burden on women and their families.

3. Enhance health insurance coverage and enrollment among pregnant women. This can be achieved by:
– Conducting awareness campaigns to educate pregnant women about the importance of health insurance and the benefits it provides for maternal health services.
– Simplifying the health insurance enrollment process and ensuring that pregnant women have easy access to enrollment centers.
– Collaborating with community-based organizations and local leaders to promote health insurance enrollment among pregnant women, particularly in rural areas.

4. Conduct regular monitoring and evaluation of the implementation of the free maternal healthcare policy and its impact on OOP payments. This can be done by:
– Establishing a system for collecting and analyzing data on OOP payments in public sector health facilities.
– Conducting periodic surveys or assessments to measure the prevalence of OOP payments among women accessing skilled delivery services.
– Using the findings from monitoring and evaluation efforts to inform policy decisions and make necessary adjustments to improve access to maternal health services.

By implementing these recommendations, it is expected that access to maternal health services will be improved, and the financial burden on pregnant women and their families will be reduced. This will contribute to better maternal health outcomes and the overall well-being of women and their children.
AI Innovations Methodology
To improve access to maternal health, here are some potential recommendations:

1. Strengthening Health Infrastructure: Investing in the improvement and expansion of public sector health facilities, particularly in rural areas, can help increase access to maternal health services. This includes ensuring the availability of skilled healthcare providers, necessary medical equipment, and essential medicines.

2. Community-Based Interventions: Implementing community-based programs that focus on educating and empowering women about maternal health can help improve access. These programs can include antenatal and postnatal care, family planning services, and health education on pregnancy and childbirth.

3. Mobile Health Technologies: Utilizing mobile health technologies, such as telemedicine and mobile applications, can help overcome geographical barriers and provide remote access to maternal health services. This can include virtual consultations, appointment reminders, and health information dissemination.

4. Financial Support: Expanding financial support mechanisms, such as health insurance coverage or subsidies, can help reduce out-of-pocket expenses for maternal health services. This can make healthcare more affordable and accessible for pregnant women.

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

1. Define the Outcome: Clearly define the outcome measure that represents improved access to maternal health, such as an increase in the percentage of pregnant women receiving skilled delivery services at public sector health facilities.

2. Data Collection: Collect relevant data on the current state of maternal health access, including indicators such as the percentage of women utilizing skilled delivery services, distance to health facilities, and financial barriers.

3. Model Development: Develop a simulation model that incorporates the potential recommendations and their expected impact on the outcome measure. This can be done using statistical modeling techniques, such as regression analysis or mathematical modeling.

4. Parameter Estimation: Estimate the parameters of the simulation model using available data and evidence from literature or expert opinions. This may involve conducting surveys, analyzing existing data sources, or consulting with relevant stakeholders.

5. Scenario Analysis: Simulate different scenarios by varying the implementation levels of the recommendations. This can help assess the potential impact of each recommendation individually and in combination.

6. Evaluation and Interpretation: Analyze the simulation results to evaluate the potential impact of the recommendations on improving access to maternal health. Interpret the findings, considering the limitations and uncertainties of the simulation model.

7. Policy Recommendations: Based on the simulation results, provide evidence-based policy recommendations on which recommendations are most effective in improving access to maternal health. Consider the feasibility, cost-effectiveness, and sustainability of implementing these recommendations.

It is important to note that the methodology described above is a general framework and can be adapted based on the specific context and available data.

Partilhar isto:
Facebook
Twitter
LinkedIn
WhatsApp
Email