Equity in antenatal care quality: an analysis of 91 national household surveys

The Lancet Global Health, Volume 6, No. 11, Year 2018

Ukuhunyushwa

Background: Emerging data show that many low-income and middle-income country (LMIC) health systems struggle to consistently provide good-quality care. Although monitoring of inequalities in access to health services has been the focus of major international efforts, inequalities in health-care quality have not been systematically examined. Methods: Using the most recent (2007–16) Demographic and Health Surveys and Multiple Indicator Cluster Surveys in 91 LMICs, we described antenatal care quality based on receipt of three essential services (blood pressure monitoring and urine and blood testing) among women who had at least one visit with a skilled antenatal-care provider. We compared quality across country income groups and quantified within-country wealth-related inequalities using the slope and relative indices of inequality. We summarised inequalities using random-effects meta-analyses and assessed the extent to which other geographical and sociodemographic factors could explain these inequalities. Findings: Globally, 72·9% (95% CI 69·1–76·8) of women who used antenatal care reported blood pressure monitoring and urine and blood testing; this number ranged from 6·3% in Burundi to 100·0% in Belarus. Antenatal care quality lagged behind antenatal care coverage the most in low-income countries, where 86·6% (83·4–89·7) of women accessed care but only 53·8% (44·3–63·3) reported receiving the three services. Receipt of the three services was correlated with gross domestic product per capita and was 40 percentage points higher in upper-middle-income countries compared with low-income countries. Within countries, the wealthiest women were on average four times more likely to report good quality care than the poorest (relative index of inequality 4·01, 95% CI 3·90–4·13). Substantial inequality remained after adjustment for subnational region, urban residence, maternal age, education, and number of antenatal care visits (3·20, 3·11–3·30). Interpretation: Many LMICs that have reached high levels of antenatal care coverage had much lower and inequitable levels of quality. Achieving ambitious maternal, newborn, and child health goals will require greater focus on the quality of health services and their equitable distribution. Equity in effective coverage should be used as the new metric to monitor progress towards universal health coverage. Funding: Bill & Melinda Gates Foundation. We selected all Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) done in LMICs in the past 10 years and included the most recent survey for each country (as of Jan 15, 2018). The DHS and MICS, respectively funded by the US Agency for International Development and the United Nations Children’s Fund, gather data on a range of population health indicators with a strong focus on maternal and child health. Standardised questionnaires ensure that data collected are comparable across countries. Sampling strategies and methodology have been described previously.17, 18 Our population of interest included all women of reproductive age (15–49 years) who had at least one livebirth in the past 2 years (MICS) or 5 years (DHS). In each country, we estimated antenatal care coverage as the proportion of women who had at least one antenatal care visit with a skilled provider during their last pregnancy. We used country-specific definitions of skilled providers as defined in the DHS and MICS. These included doctors, nurses, midwives, and country-specific skilled providers (such as maternal and child health aides in Sierra Leone and health extension workers in Ethiopia). Country-specific definitions of skilled antenatal care providers are available in the appendix. Guided by the framework of the Lancet Global Health Commission on High-Quality Health Systems in the SDG Era2 and by the WHO recommendations3 on antenatal care for a positive pregnancy experience, we assessed the availability of potential indicators of antenatal care quality in household surveys. Quality antenatal care involves the provision of respectful, evidence-based care including appropriate patient assessments such as history questions, examinations, and diagnostic tests (eg, full blood count testing and urine culture); appropriate preventive and curative treatments (eg, tetanus toxoid vaccination and iron supplementation); and patient counselling and education (eg, on healthy eating and signs of complications). In the DHS and MICS, women who reported attending antenatal care were asked whether they received specific services during consultations. We found 13 indicators related to antenatal care quality: weight and height measurement, blood pressure monitoring, urine and blood samples taken, HIV testing and counselling, tetanus vaccination, iron supplements, malaria prophylaxis, drugs for intestinal worms, counselling on signs of complications, and counselling on where to go in case of complications. The number of items collected varied across countries and only three indicators remained consistently measured in all countries and relevant in all contexts: blood pressure monitoring and urine and blood testing. To obtain a comparable measure across the largest possible set of countries, we limited our estimate of antenatal care quality to these three indicators. Antenatal care quality was therefore included as a binary outcome measuring the proportion of women who reported having their blood pressure checked and giving a urine and blood sample at any point during pregnancy among those who sought care from skilled providers. These three services do not comprise the full range of necessary antenatal care services and offer a limited view of antenatal care quality. However, they are recommended by WHO as essential components of antenatal care and are crucial to the detection of several pregnancy risks including hypertension, pre-eclampsia, infections, anaemia, and nutritional deficiencies.3 Our quality measure is also limited by the fact that information on the specific urine and blood tests done is not available in the DHS and MICS; women were asked whether they gave urine and blood specimens but not what the tests were for. As a sensitivity analysis, and given the importance of counselling for the detection of pregnancy complications, we also estimated antenatal care quality by including a fourth indicator available in 55 (60%) of 91 countries. This indicator measured whether women were counselled on potential danger signs to look out for during pregnancy or where to go in case of a complication. The survey questions for these four indicators are shown in the appendix. At the country level, we included gross domestic product (GDP) per capita and country income groups specific to the survey year based on World Bank classification as independent variables. At the individual level, we used the wealth index constructed by the DHS and MICS as an estimate of socioeconomic position. The wealth index is based on a household’s ownership of selected assets, housing construction materials, and types of water access and sanitation facilities and is estimated by principal component analysis. As a further independent variable at the individual level, we also used the woman’s educational attainment based on country-specific categories. Most surveys contained a variable with six categories (no education, attended primary, completed primary, attended secondary, completed secondary, or attended higher education). A few surveys used between three and five education categories, making inequality measured by education groups less comparable across countries. We also used the woman’s age at childbirth categorised into three groups (15–19 years, 20–35 years, and 35–49 years); her place of residence (urban or rural); region, state, or province of residence; and the total number of antenatal care visits attended (modelled as a continuous variable). To assess inequalities between countries, we ranked countries by levels of antenatal care coverage and quality and compared results across country income groups (low income, lower-middle income, and upper-middle income). We also plotted antenatal care coverage and quality against GDP per capita. To assess inequalities within countries, we ranked women using the wealth index and assigned a relative ranking based on their position in the cumulative wealth distribution. We then measured inequalities in antenatal care coverage and quality using the slope index of inequality (SII) and the relative index of inequality (RII).19, 20 Inequalities have been found to differ substantially when measured according to dimensions of inequality other than wealth;12 therefore, we also measured the SII and RII using the woman’s education and show these results in the appendix. The SII expresses the absolute percentage point difference in antenatal care coverage or quality between the predicted poorest and richest in the wealth distribution, assuming a linear relation between social rank and the outcome.21 The RII expresses the ratio of the predicted outcomes between the two extremes of the wealth distribution, assuming a log-linear relation.21 We used logistic regression models to estimate the association between the woman’s relative rank and her antenatal care outcomes. The SII and RII were obtained using marginal effects and the lincom and nlcom post-estimation commands in Stata version 14.2. Individual-level sampling weights and robust SEs were used in all regressions.17, 18 To summarise coverage, quality, and inequalities across countries, we pooled the estimates using random-effects meta-analyses weighted by the inverse variance of the estimates.22 We assessed heterogeneity across countries using I2 statistics. Finally, to assess the extent to which wealth-related inequalities in antenatal care quality could be explained by other geographical and socioeconomic determinants, we sequentially added five variables to the wealth rank in the regression models used to estimate the SII and RII: the woman’s education and age group, urban versus rural residence, subnational region, and total number of antenatal care visits (because women who attend more visits might have more opportunities to receive the three services we assessed). The study sponsors did not have any role in study design, data analysis, data interpretation, writing of the report, or submission for publication. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.

I-AI Digest

Study Justification:

This study aimed to examine the quality of antenatal care in low-income and middle-income countries (LMICs) and assess the inequalities in access to quality care. While previous efforts have focused on monitoring inequalities in access to health services, the quality of care has not been systematically examined. The study aimed to fill this gap and highlight the importance of focusing on the quality of health services to achieve maternal, newborn, and child health goals.

Study Highlights:

– The study analyzed data from 91 LMICs using the most recent Demographic and Health Surveys and Multiple Indicator Cluster Surveys.
– Globally, 72.9% of women who used antenatal care reported receiving blood pressure monitoring and urine and blood testing.
– Antenatal care quality was lower in low-income countries, where 86.6% of women accessed care but only 53.8% reported receiving the three essential services.
– Wealth-related inequalities were observed, with the wealthiest women being four times more likely to report good quality care than the poorest.
– Inequalities remained even after adjusting for factors such as subnational region, urban residence, maternal age, education, and number of antenatal care visits.

Study Recommendations:

– Greater focus on the quality of health services and their equitable distribution is needed to achieve ambitious maternal, newborn, and child health goals.
– Equity in effective coverage should be used as a new metric to monitor progress towards universal health coverage.

Key Role Players:

– Policy makers and government officials responsible for healthcare planning and implementation.
– Health professionals, including doctors, nurses, midwives, and other skilled antenatal care providers.
– International organizations and donors, such as the World Health Organization and the Bill & Melinda Gates Foundation, who can provide support and funding for improving antenatal care quality.

Cost Items for Planning Recommendations:

– Training and capacity building for healthcare providers to ensure they can deliver high-quality antenatal care.
– Infrastructure and equipment upgrades to support the provision of essential services, such as blood pressure monitoring and urine and blood testing.
– Information systems and data collection tools to monitor and evaluate the quality of antenatal care.
– Awareness campaigns and community engagement activities to promote the importance of antenatal care and encourage women to seek care from skilled providers.
– Research and evaluation activities to assess the impact of interventions aimed at improving antenatal care quality.
Please note that the cost items provided are general suggestions and may vary depending on the specific context and needs of each country or region.

Amandla Obufakazi

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, as it is based on a comprehensive analysis of 91 national household surveys in low-income and middle-income countries. The study provides detailed information on antenatal care quality, inequalities, and factors that contribute to these inequalities. However, to improve the evidence, the abstract could include more specific details on the methodology used, such as the sampling strategies and statistical analysis techniques. Additionally, providing information on the limitations of the study would enhance the overall quality of the evidence.

Abstract

We selected all Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) done in LMICs in the past 10 years and included the most recent survey for each country (as of Jan 15, 2018). The DHS and MICS, respectively funded by the US Agency for International Development and the United Nations Children’s Fund, gather data on a range of population health indicators with a strong focus on maternal and child health. Standardised questionnaires ensure that data collected are comparable across countries. Sampling strategies and methodology have been described previously.17, 18 Our population of interest included all women of reproductive age (15–49 years) who had at least one livebirth in the past 2 years (MICS) or 5 years (DHS). In each country, we estimated antenatal care coverage as the proportion of women who had at least one antenatal care visit with a skilled provider during their last pregnancy. We used country-specific definitions of skilled providers as defined in the DHS and MICS. These included doctors, nurses, midwives, and country-specific skilled providers (such as maternal and child health aides in Sierra Leone and health extension workers in Ethiopia). Country-specific definitions of skilled antenatal care providers are available in the appendix. Guided by the framework of the Lancet Global Health Commission on High-Quality Health Systems in the SDG Era2 and by the WHO recommendations3 on antenatal care for a positive pregnancy experience, we assessed the availability of potential indicators of antenatal care quality in household surveys. Quality antenatal care involves the provision of respectful, evidence-based care including appropriate patient assessments such as history questions, examinations, and diagnostic tests (eg, full blood count testing and urine culture); appropriate preventive and curative treatments (eg, tetanus toxoid vaccination and iron supplementation); and patient counselling and education (eg, on healthy eating and signs of complications). In the DHS and MICS, women who reported attending antenatal care were asked whether they received specific services during consultations. We found 13 indicators related to antenatal care quality: weight and height measurement, blood pressure monitoring, urine and blood samples taken, HIV testing and counselling, tetanus vaccination, iron supplements, malaria prophylaxis, drugs for intestinal worms, counselling on signs of complications, and counselling on where to go in case of complications. The number of items collected varied across countries and only three indicators remained consistently measured in all countries and relevant in all contexts: blood pressure monitoring and urine and blood testing. To obtain a comparable measure across the largest possible set of countries, we limited our estimate of antenatal care quality to these three indicators. Antenatal care quality was therefore included as a binary outcome measuring the proportion of women who reported having their blood pressure checked and giving a urine and blood sample at any point during pregnancy among those who sought care from skilled providers. These three services do not comprise the full range of necessary antenatal care services and offer a limited view of antenatal care quality. However, they are recommended by WHO as essential components of antenatal care and are crucial to the detection of several pregnancy risks including hypertension, pre-eclampsia, infections, anaemia, and nutritional deficiencies.3 Our quality measure is also limited by the fact that information on the specific urine and blood tests done is not available in the DHS and MICS; women were asked whether they gave urine and blood specimens but not what the tests were for. As a sensitivity analysis, and given the importance of counselling for the detection of pregnancy complications, we also estimated antenatal care quality by including a fourth indicator available in 55 (60%) of 91 countries. This indicator measured whether women were counselled on potential danger signs to look out for during pregnancy or where to go in case of a complication. The survey questions for these four indicators are shown in the appendix. At the country level, we included gross domestic product (GDP) per capita and country income groups specific to the survey year based on World Bank classification as independent variables. At the individual level, we used the wealth index constructed by the DHS and MICS as an estimate of socioeconomic position. The wealth index is based on a household’s ownership of selected assets, housing construction materials, and types of water access and sanitation facilities and is estimated by principal component analysis. As a further independent variable at the individual level, we also used the woman’s educational attainment based on country-specific categories. Most surveys contained a variable with six categories (no education, attended primary, completed primary, attended secondary, completed secondary, or attended higher education). A few surveys used between three and five education categories, making inequality measured by education groups less comparable across countries. We also used the woman’s age at childbirth categorised into three groups (15–19 years, 20–35 years, and 35–49 years); her place of residence (urban or rural); region, state, or province of residence; and the total number of antenatal care visits attended (modelled as a continuous variable). To assess inequalities between countries, we ranked countries by levels of antenatal care coverage and quality and compared results across country income groups (low income, lower-middle income, and upper-middle income). We also plotted antenatal care coverage and quality against GDP per capita. To assess inequalities within countries, we ranked women using the wealth index and assigned a relative ranking based on their position in the cumulative wealth distribution. We then measured inequalities in antenatal care coverage and quality using the slope index of inequality (SII) and the relative index of inequality (RII).19, 20 Inequalities have been found to differ substantially when measured according to dimensions of inequality other than wealth;12 therefore, we also measured the SII and RII using the woman’s education and show these results in the appendix. The SII expresses the absolute percentage point difference in antenatal care coverage or quality between the predicted poorest and richest in the wealth distribution, assuming a linear relation between social rank and the outcome.21 The RII expresses the ratio of the predicted outcomes between the two extremes of the wealth distribution, assuming a log-linear relation.21 We used logistic regression models to estimate the association between the woman’s relative rank and her antenatal care outcomes. The SII and RII were obtained using marginal effects and the lincom and nlcom post-estimation commands in Stata version 14.2. Individual-level sampling weights and robust SEs were used in all regressions.17, 18 To summarise coverage, quality, and inequalities across countries, we pooled the estimates using random-effects meta-analyses weighted by the inverse variance of the estimates.22 We assessed heterogeneity across countries using I2 statistics. Finally, to assess the extent to which wealth-related inequalities in antenatal care quality could be explained by other geographical and socioeconomic determinants, we sequentially added five variables to the wealth rank in the regression models used to estimate the SII and RII: the woman’s education and age group, urban versus rural residence, subnational region, and total number of antenatal care visits (because women who attend more visits might have more opportunities to receive the three services we assessed). The study sponsors did not have any role in study design, data analysis, data interpretation, writing of the report, or submission for publication. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Izinto zokwakha

https://efashare.b-cdn.net/materials/a029629d38b8dcad1f7ae5a02394657b4bb08bf24b8277b2cd5cbd551a030fc7/mmc1.pdf

Emisha

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

1. Strengthening Health Systems: Implementing strategies to improve the quality of care provided by health systems in low-income and middle-income countries (LMICs). This could involve training healthcare providers, improving infrastructure and equipment, and ensuring the availability of essential supplies and medications.

2. Enhancing Antenatal Care Services: Developing and implementing comprehensive antenatal care programs that go beyond basic check-ups. This could include incorporating additional services such as comprehensive health assessments, counseling on nutrition and healthy lifestyles, and education on potential pregnancy complications.

3. Addressing Inequalities: Taking steps to reduce wealth-related inequalities in access to quality antenatal care. This could involve implementing targeted interventions to reach marginalized and disadvantaged populations, such as providing financial assistance for antenatal care services or improving transportation options for women in remote areas.

4. Strengthening Data Collection and Monitoring: Improving the collection and analysis of data on maternal health indicators, including antenatal care quality. This could involve enhancing the capacity of LMICs to conduct national surveys and monitoring systems, as well as promoting the use of standardized questionnaires and indicators to ensure comparability across countries.

5. Promoting Collaboration and Knowledge Sharing: Facilitating collaboration between LMICs, international organizations, and research institutions to share best practices and lessons learned in improving access to maternal health. This could involve establishing platforms for knowledge exchange, organizing conferences and workshops, and supporting research on innovative approaches to maternal health.

It is important to note that these recommendations are based on the provided information and may need to be tailored to specific contexts and resources available in each LMIC.

AI Innovations Description

The recommendation that can be developed into an innovation to improve access to maternal health based on the provided description is to focus on improving the quality of antenatal care services in low-income and middle-income countries (LMICs). The analysis of 91 national household surveys revealed that although antenatal care coverage is relatively high in many LMICs, the quality of care provided is often inadequate and inequitable.

To address this issue, the following recommendations can be considered:

1. Strengthen training and capacity-building programs for skilled antenatal care providers: Ensure that healthcare providers have the necessary knowledge and skills to provide high-quality antenatal care services. This can be achieved through targeted training programs, continuous professional development, and mentorship opportunities.

2. Enhance the availability and accessibility of essential equipment and supplies: Improve the availability of blood pressure monitoring devices, urine and blood testing kits, and other necessary equipment and supplies in healthcare facilities. This can be done through procurement and distribution systems that prioritize the needs of maternal health services.

3. Implement evidence-based guidelines and protocols: Develop and disseminate standardized guidelines and protocols for antenatal care that are based on the latest evidence and best practices. These guidelines should outline the essential components of antenatal care and provide clear instructions for healthcare providers.

4. Promote patient-centered care and respectful maternity care: Ensure that antenatal care services are delivered in a respectful and culturally sensitive manner. This includes promoting shared decision-making, informed consent, and respectful communication between healthcare providers and pregnant women.

5. Strengthen monitoring and evaluation systems: Establish robust monitoring and evaluation systems to regularly assess the quality of antenatal care services. This can involve the use of quality indicators, regular audits, and feedback mechanisms to identify areas for improvement and track progress over time.

6. Address socioeconomic and geographic inequalities: Develop targeted interventions to address socioeconomic and geographic inequalities in access to high-quality antenatal care. This can involve implementing strategies to reach marginalized populations, such as providing mobile antenatal care clinics in remote areas or offering financial incentives to healthcare providers working in underserved communities.

By implementing these recommendations, it is possible to improve the quality of antenatal care services and ensure equitable access to maternal health services in LMICs. This will contribute to reducing maternal morbidity and mortality and achieving the maternal health goals outlined in the Sustainable Development Goals.

AI Innovations Methodology

Based on the provided description, here are some potential recommendations for improving access to maternal health:

1. Strengthening healthcare infrastructure: Investing in healthcare facilities, equipment, and trained healthcare professionals can improve access to maternal health services. This includes ensuring the availability of skilled antenatal care providers and necessary medical supplies.

2. Increasing awareness and education: Implementing educational programs and campaigns to raise awareness about the importance of maternal health and the available services can encourage more women to seek antenatal care. This can be done through community outreach programs, media campaigns, and partnerships with local organizations.

3. Improving transportation and logistics: Addressing transportation barriers by providing reliable and affordable transportation options can help pregnant women reach healthcare facilities more easily. This can involve improving road infrastructure, establishing transportation networks, or providing financial support for transportation costs.

4. Promoting telemedicine and mobile health solutions: Utilizing technology, such as telemedicine and mobile health applications, can help overcome geographical barriers and improve access to maternal health services. This allows pregnant women to receive medical advice, consultations, and monitoring remotely.

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

1. Define the indicators: Identify specific indicators that measure access to maternal health, such as the proportion of women receiving antenatal care, the number of skilled antenatal care providers per population, or the distance to the nearest healthcare facility.

2. Collect baseline data: Gather data on the current status of the selected indicators in the target population. This can be done through surveys, interviews, or existing data sources.

3. Develop a simulation model: Create a mathematical or computational model that simulates the impact of the recommendations on the selected indicators. This model should take into account various factors, such as population size, geographical distribution, healthcare infrastructure, and the effectiveness of the proposed interventions.

4. Input intervention scenarios: Define different scenarios that represent the implementation of the recommendations. This can include variations in the scale, timing, and coverage of the interventions. For example, one scenario could simulate the impact of strengthening healthcare infrastructure in all regions, while another scenario could focus on specific areas with the highest need.

5. Run simulations: Use the simulation model to calculate the projected changes in the selected indicators for each intervention scenario. This involves inputting the relevant data and parameters into the model and running the simulations.

6. Analyze results: Analyze the simulation results to assess the potential impact of the recommendations on improving access to maternal health. Compare the outcomes of different intervention scenarios to identify the most effective strategies.

7. Refine and validate the model: Continuously refine and validate the simulation model based on feedback, additional data, and real-world observations. This ensures that the model accurately represents the complexities of the healthcare system and provides reliable predictions.

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

Ababhali & Co-Ababhali

Statistics:

Citations: 96

Authors: 7

Identifiers:

DOI: 10.1016/S2214-109X(18)30389-9

Research Areas:

Disparities, Environmental, Genetics and Genomics, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Noncommunicable Diseases, Quality of Care, Sexual and Reproductive Health, Social Determinants, Workforce

Study Countries:

Burundi, Ethiopia, Multi-Countries, Sierra Leone

Study Design:

Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Female

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