On measuring and decomposing inequality of opportunity in access to health services among Tunisian children: A new approach for public policy

Health and Quality of Life Outcomes, Volume 15, No. 1, Year 2017

Interpretation

Background: The early years in children’s life are the key to physical, cognitive-language, and, socio-emotional skills development. So, it is of paramount importance in this period to be interested in different indicators that would influence the child’s health. Methods: This paper measures inequality of opportunities among Tunisian children concerning access to nutritional and healthy services using Human Opportunity-Index and Shapely decomposition methods. Results: Many disparities between regions have been detected since 1982 until 2012. Tunisian children face unequal opportunities to develop in terms of health, nutrition, cognitive, social, and emotional development. Likewise, we found that, parents’ education, wealth, age of household head and geographic factors as key factors determining child development outcomes. Conclusion: Our findings suggested that childhood unequal opportunities in Tunisia are explained by pension funds deficiency and structural problem in the labor market. Trial registration: The results of a health care intervention on human participants “retrospectively registered”. We use data from the Multiple Indicator Cluster Surveys (MICS4), this survey was executed in 2011-2012 by the Ministry of Development and Cooperation with the National Institute of Statistics of Tunisia (INS), financial and technical support was provided by the United Nations Children’s Emergency Fund (UNICEF), the United Nations Population Fund (UNFPA) and the Swiss Cooperation Office in Tunisia. It is the only recent database available until our day, which contains rich information on the situation of women and children in this country. We use also data concerning place of residence, socio-economic and demographic indicators for three governorates of the center (Kasserine, Kairouan and Zidi-Bouzid) and for six regions of the country (District Tunis, North East, North West, Center East, South East and South West). Otherwise, we use 8 variables of circumstances: residence, age of household’s head, family wealth index, sex of household head, gender, number of children per household, level of education of household head and household size. Firstly, to study nutrition situation of Tunisian children we are based on a sample of 9600 selected households where 2938 children under 5 years were identified through the household question sheet. This question sheet was filled for 2768 of these children, which corresponds to a 94.2% answer rate among households with children under 5 years interviewed [24]. Descriptive statistics containing demographic information about of this sample are presented in the Table 10 Appendix. Then, to analyze the development of babies’ health in Tunisia, we use crucial index measuring opportunity access to basic services using data provided by the INS (2011-2012). The database covers 9867 women interviewed, of whom 4204 gave birth and 1059 gave birth during the last 2 years before the interview. The first sample of women, that have had children since 1982 until 2012, allows us to see the disparities in terms of access to basic health services for children. The last database which contains 1059 women who gave birth in the last years preceding the questionnaire is important in the sense that it allows us to follow the evolution of inequalities of chances in relation to previous years. For the choice of our variables, we are based on important indicators and outcomes identified in previous literature, and as constrained by the data availability, we considered nutritional and health care utilization variables as our proxy for health services access. The nutritional status of children is a reflection of their overall health. When children have access to adequate food, are not exposed to repeated morbid episodes and are healthy, they reach their growth potential and are considered well fed. Malnutrition is responsible for more than half of all child deaths worldwide. Undernourished children are more likely to die from common childhood illnesses and those who survive have recurrent diseases and stunted growth. One of the main goals of World Health Organization is to reduce the proportion of people who suffer from hunger. A reduction in the prevalence of malnutrition will also help to reduce infant mortality. In a well-nourished population, there is a reference distribution of the size and weight of children under 5 years of age. Under-nutrition in a population can be measured by comparing children to the reference population. The reference population used in this work is based on the WHO growth standards. Each of the three indicators of nutritional status can be expressed in units of standard deviations (reduced deviation) from the median of the reference population (Tables 13 and 14 in the Appendix). Weight-for-age is a measure of both acute and chronic malnutrition. Children whose weight-for-age is more than two standard deviations below the median of the reference population are considered to be low or moderate underweight, while those whose weight-for-age is more than three standard deviations below the median are considered to be severely underweight(Table 13). The length-for-age is a measure of linear growth. Children whose height-for-age is more than two standard deviations below the median of the reference population are considered to be too small for their age and are classified as having moderate or severe growth retardation. Those whose height-for-age is more than three standard deviations below the median are classified as having severe growth retardation. Stunting is a reflection of chronic malnutrition resulting from lack of adequate nutrition over a long period of time and from recurrent or chronic diseases (Table 13). Finally, children whose weight-for-height is more than two standard deviations below the median of the reference population are classified as moderately or severely emaciated, while those with more than three standard deviations below the median are considered severely emaciated. Emaciation is generally the result of a recent nutritional deficiency. The indicator may have significant seasonal variations associated with changes in food availability or disease prevalence (Table 14). Table 1 shows the percentages of children in each of these categories, based on the anthropometric measurements taken during the fieldwork. Based on the new WHO growth standards,1 2.57% of children under 5 years old in Tunisia are underweight (moderate or severe). Approximately one of ten children (10.33%) suffers from moderate or severe stunting and 2.2% are moderately or severely emaciated. Basic characteristics of children under 5 years according to selected characteristics (Nutrition) The second value in the table corresponds to the percentage contribution in the corresponding sample There are also variations in anthropometric indicators according to socio-demographic characteristics; boys appear to be slightly more likely than girls to accuse underweight, stunting, and emaciation. Disparities by environment are characterized by a higher prevalence of moderate or severe growth retardation in rural areas (≈14%) than in urban areas (8%). In terms of geographical variations, we can see a higher prevalence of underweight in the South West, Sidi Bouzid, Kairouan and North West (4%), while the prevalence of moderate or severe growth problem is touched in Kasserine (13.83%), in south-west, sidi bouzid, kairouan and north-west (more than 13%). Children whose mothers/guardians with secondary or superior education are the least likely to be underweight and stunted compared to the children of mothers who have never attended school. As for the disparities according to the level of economic well-being, the prevalence of underweight and stunting are higher among the poorest. Similarly, the prenatal period offers important opportunities to provide services that may be essential to the health of pregnant women and their infants [25]. A better understanding of the growth and development of the fetus and its relationship to maternal health has led to increased attention to prenatal care, which has been widely demonstrated to have an impact on improving maternal and neonatal health. For example, if the prenatal period is used to inform women and families about warning signs, symptoms and risks related to labor and delivery, it can guide women to give birth in the best possible way with the assistance of qualified care personnel. The prenatal period also provides an opportunity to provide information on birth spacing, recognized as an important factor in improving infant survival. Tetanus vaccination during pregnancy can save both mother and infant life. Preventing and treating malaria in pregnant women, managing anemia during pregnancy and treating STIs (sexually transmitted infections) can greatly improve the chances of survival of the fetus and the health of the mother. Adverse outcomes such as low birth weight can be prevented through a combination of interventions to improve the nutritional status of women and prevent infections (eg, malaria and STIs) during pregnancy. More recently, the potential of the prenatal period as an entry point for the prevention of HIV (Human Immunodeficiency Virus) and care, especially for the prevention of mother-to-child transmission of HIV, has lead to renewed interest in the access and use of prenatal care services. World Health Organization recommends a minimum of four antenatal visits based on an analysis of the effectiveness of different antenatal care models. WHO guidelines are specific to the content of prenatal consultations, including: measurement of blood pressure; Urine analysis for bacteriuria and proteinuria; Blood testing to detect syphilis and severe anemia; and weight/length measurement (optional). In this framework, we present the level of health care coverage in Table 2 and the type of staff providing prenatal care to women aged 15-49 who gave birth in the two years preceding the survey in Table 15 Appendix. This table shows that access to antenatal care is relatively high in the country as a whole with 97.83% of women receiving prenatal care at least one time during pregnancy (79.03% per doctor and 44.47% per auxiliary midwife). The highest levels of prenatal care are observed in the South East and South West regions (100%); while the lowest level is in the Sidi Bouzid region (89.36%). There are few differences among children following residence (98.50% in urban areas versus 96.94% in rural areas). This coverage is around 97.06% for boys and 98.64% for girls. It increases with women’s educational attainment (from 95.55 to 100%) and the level of economic well-being of households. Of the women surveyed and concerned with antenatal care, 79.03% were examined by a physician during pregnancy; this proportion is higher in urban areas (82.69%) than in rural areas (74.23%). It is higher among women residing in the Central East region (93.57%), women with university education (93.10%), and women in the richest household category (97.87%). The lowest proportions were found among women who had never attended school (67.04%) and those in the governorate of Kairouan (67.50%) and the South West region (68.57%). This level of coverage has been low in previous decades and is approaching an average of 25% throughout the study period. The distribution is similar for blood samples with a slight decrease in the level of coverage, which drops to 94.62% in 2012 and does not exceed 24% (23.86%) over the period from 1982 until the date of the survey always with a small advantage of the southern regions. Basic characteristics of children under 5 years according to selected characteristics (Health) The second value in the table corresponds to the percentage contribution in the corresponding sample In Tunisia, two postnatal consultations are recommended: on the eighth and fortieth day after childbirth [26].. However, no question on these two visits is included in the questionnaire. This survey revealed that 85.67% of newborns had no postnatal consultation during the first 6 days after birth between 1982 and 2012, while 43.15% born in the 2 years prior to the survey received no postnatal care (Table (Table2).2). This percentage is the highest in Sidi Bouzid (88.22% over the entire period and 56.38% in 2012) and it is the lowest in the Center East (81.80 and 20.18%). There are few differences on average between urban areas (86.64%) and rural areas (84.06%). This percentage decreases with the level of economic well-being and with the level of schooling of the mother. As indicated previously, we aim to study inequality in early childhood access to basic services. Otherwise, our variables of interest are binary meaning two possibilities either access or not. So, we follow De Barros [23], Son [27] to define a dichotomous variable zi which takes a value of 1 if the ith person of specific group has access to basic opportunity and takes a value of 0 if he lacks access to the considered opportunity. It can be readily proved that (zi) = pi = (zi), where pi is the average accomplishment related to the dichotomous outcome (zi) with respect to a specific group of sample. pi could be defined otherwise as the probability that the ith person has access to a given opportunity. It depends on a vector of exogenous variables indicating the socioeconomic circumstances (such as gender, age, area of residence…) of each group, the total characteristic being k. There can be as many probability gaps between individuals/groups as there are possible combinations of group-identifying circumstances (income groups, household-size groups, gender groups…). Given a set of k circumstance variables xi1, xi2… xik, we estimate the probability pi for each child (In this study we focus particularly on children as we assume that many of the differences in opportunities are generated during childhood and carried out the whole life) by means of a logit model. Accordingly, we have the following expression of: Secondly, we compute the overall coverage rate p¯ which is the proportion of the population with access to a given opportunity using the following formula: Where wi=1n and n is the size of sample considered. Then, the Dissimilarity Index D^ can be computed as follows: After calculating the penalty which is equal to P = C × D, we get the final formula of the HOI for each service or outcome: Human opportunity index specification provides an overview in the differences between regions in terms of percentage coverage by any service in addition to dissimilarity level but it is silent about origin of inequality. To overtake this limit, we refer to Shapley Decomposition methodology that consists in identifying how each circumstance “contributes” to Inequality in access to basic services [28, 29, 13].2 This approach extends the idea of the Shapley value of cooperative games into applications for decomposing inequality. The decomposition consists of calculating the marginal contributions of each circumstance as they are removed in sequence. Following Barros et al. [11], and [13], we can measure inequality of opportunities by the penalty (P) or by the dissimilarity index (D), as defined in expressions (4) and (5) above. The value of these two measures–where P is just a scalar transformation of D–is dependent on the set of circumstances considered. Moreover, they have the important property that adding more circumstances always increases the value of P and D. If we have two sets of circumstances A and B, and set A and B do not overlap, then HOI(A,B) ≤ HOI(A); and alternatively, D(A,B) ≥ D(A). The impact of adding a circumstance A is given by: Where N is the set of all circumstances, which includes n circumstances in total; S is a subset of N that does not contain the particular circumstance A. D(S) is the dissimilarity index estimated with the set of circumstances S. D (S U{A}) is the dissimilarity index calculated with set of circumstances S and the circumstance A. The contribution of circumstance A to the dissimilarity index can be defined as: We measure variations in HOI in Tunisia in the time period surveyed based on 2 main indicator categories: (i) Malnutrition Intake, and (ii) Healthcare utilization before, during pregnancy to healthcare services in early year using data from the 2011 and 2012 (MICS4) samples.

AI Digest

Study Justification:

– The early years of a child’s life are crucial for their development in terms of physical, cognitive, language, and socio-emotional skills.
– It is important to understand the factors that influence a child’s health during this period.
– This study aims to measure inequality of opportunities in access to nutritional and healthy services among Tunisian children.
– By identifying disparities and key factors, policymakers can develop targeted interventions to improve child development outcomes.

Highlights:

– Disparities between regions in Tunisia have been detected since 1982 until 2012.
– Tunisian children face unequal opportunities in terms of health, nutrition, cognitive, social, and emotional development.
– Parents’ education, wealth, age of household head, and geographic factors are key factors determining child development outcomes.
– Childhood unequal opportunities in Tunisia are explained by pension funds deficiency and structural problems in the labor market.

Recommendations:

– Increase investment in pension funds to address the deficiency and ensure adequate support for families.
– Implement policies to address structural problems in the labor market, such as improving job opportunities and reducing unemployment rates.
– Develop targeted interventions to improve access to nutritional and healthy services for children in regions with higher disparities.
– Improve access to education and economic opportunities for parents to enhance child development outcomes.

Key Role Players:

– Ministry of Development and Cooperation
– National Institute of Statistics of Tunisia
– United Nations Children’s Emergency Fund (UNICEF)
– United Nations Population Fund (UNFPA)
– Swiss Cooperation Office in Tunisia

Cost Items for Planning Recommendations:

– Investment in pension funds
– Implementation of labor market policies
– Development and implementation of targeted interventions
– Education and training programs for parents
– Monitoring and evaluation of interventions

Strength of Evidence

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 uses data from a recent survey conducted by reputable organizations, which adds credibility to the findings. The authors also provide a clear description of the methods used and present the results of their analysis. However, the abstract could be improved by providing more specific details about the sample size and characteristics of the participants. Additionally, the abstract could benefit from a clearer statement of the implications of the findings for public policy. To improve the evidence, the authors could consider providing more information about the limitations of the study and suggestions for future research.

Abstract

We use data from the Multiple Indicator Cluster Surveys (MICS4), this survey was executed in 2011-2012 by the Ministry of Development and Cooperation with the National Institute of Statistics of Tunisia (INS), financial and technical support was provided by the United Nations Children’s Emergency Fund (UNICEF), the United Nations Population Fund (UNFPA) and the Swiss Cooperation Office in Tunisia. It is the only recent database available until our day, which contains rich information on the situation of women and children in this country. We use also data concerning place of residence, socio-economic and demographic indicators for three governorates of the center (Kasserine, Kairouan and Zidi-Bouzid) and for six regions of the country (District Tunis, North East, North West, Center East, South East and South West). Otherwise, we use 8 variables of circumstances: residence, age of household’s head, family wealth index, sex of household head, gender, number of children per household, level of education of household head and household size. Firstly, to study nutrition situation of Tunisian children we are based on a sample of 9600 selected households where 2938 children under 5 years were identified through the household question sheet. This question sheet was filled for 2768 of these children, which corresponds to a 94.2% answer rate among households with children under 5 years interviewed [24]. Descriptive statistics containing demographic information about of this sample are presented in the Table 10 Appendix. Then, to analyze the development of babies’ health in Tunisia, we use crucial index measuring opportunity access to basic services using data provided by the INS (2011-2012). The database covers 9867 women interviewed, of whom 4204 gave birth and 1059 gave birth during the last 2 years before the interview. The first sample of women, that have had children since 1982 until 2012, allows us to see the disparities in terms of access to basic health services for children. The last database which contains 1059 women who gave birth in the last years preceding the questionnaire is important in the sense that it allows us to follow the evolution of inequalities of chances in relation to previous years. For the choice of our variables, we are based on important indicators and outcomes identified in previous literature, and as constrained by the data availability, we considered nutritional and health care utilization variables as our proxy for health services access. The nutritional status of children is a reflection of their overall health. When children have access to adequate food, are not exposed to repeated morbid episodes and are healthy, they reach their growth potential and are considered well fed. Malnutrition is responsible for more than half of all child deaths worldwide. Undernourished children are more likely to die from common childhood illnesses and those who survive have recurrent diseases and stunted growth. One of the main goals of World Health Organization is to reduce the proportion of people who suffer from hunger. A reduction in the prevalence of malnutrition will also help to reduce infant mortality. In a well-nourished population, there is a reference distribution of the size and weight of children under 5 years of age. Under-nutrition in a population can be measured by comparing children to the reference population. The reference population used in this work is based on the WHO growth standards. Each of the three indicators of nutritional status can be expressed in units of standard deviations (reduced deviation) from the median of the reference population (Tables 13 and 14 in the Appendix). Weight-for-age is a measure of both acute and chronic malnutrition. Children whose weight-for-age is more than two standard deviations below the median of the reference population are considered to be low or moderate underweight, while those whose weight-for-age is more than three standard deviations below the median are considered to be severely underweight(Table 13). The length-for-age is a measure of linear growth. Children whose height-for-age is more than two standard deviations below the median of the reference population are considered to be too small for their age and are classified as having moderate or severe growth retardation. Those whose height-for-age is more than three standard deviations below the median are classified as having severe growth retardation. Stunting is a reflection of chronic malnutrition resulting from lack of adequate nutrition over a long period of time and from recurrent or chronic diseases (Table 13). Finally, children whose weight-for-height is more than two standard deviations below the median of the reference population are classified as moderately or severely emaciated, while those with more than three standard deviations below the median are considered severely emaciated. Emaciation is generally the result of a recent nutritional deficiency. The indicator may have significant seasonal variations associated with changes in food availability or disease prevalence (Table 14). Table 1 shows the percentages of children in each of these categories, based on the anthropometric measurements taken during the fieldwork. Based on the new WHO growth standards,1 2.57% of children under 5 years old in Tunisia are underweight (moderate or severe). Approximately one of ten children (10.33%) suffers from moderate or severe stunting and 2.2% are moderately or severely emaciated. Basic characteristics of children under 5 years according to selected characteristics (Nutrition) The second value in the table corresponds to the percentage contribution in the corresponding sample There are also variations in anthropometric indicators according to socio-demographic characteristics; boys appear to be slightly more likely than girls to accuse underweight, stunting, and emaciation. Disparities by environment are characterized by a higher prevalence of moderate or severe growth retardation in rural areas (≈14%) than in urban areas (8%). In terms of geographical variations, we can see a higher prevalence of underweight in the South West, Sidi Bouzid, Kairouan and North West (4%), while the prevalence of moderate or severe growth problem is touched in Kasserine (13.83%), in south-west, sidi bouzid, kairouan and north-west (more than 13%). Children whose mothers/guardians with secondary or superior education are the least likely to be underweight and stunted compared to the children of mothers who have never attended school. As for the disparities according to the level of economic well-being, the prevalence of underweight and stunting are higher among the poorest. Similarly, the prenatal period offers important opportunities to provide services that may be essential to the health of pregnant women and their infants [25]. A better understanding of the growth and development of the fetus and its relationship to maternal health has led to increased attention to prenatal care, which has been widely demonstrated to have an impact on improving maternal and neonatal health. For example, if the prenatal period is used to inform women and families about warning signs, symptoms and risks related to labor and delivery, it can guide women to give birth in the best possible way with the assistance of qualified care personnel. The prenatal period also provides an opportunity to provide information on birth spacing, recognized as an important factor in improving infant survival. Tetanus vaccination during pregnancy can save both mother and infant life. Preventing and treating malaria in pregnant women, managing anemia during pregnancy and treating STIs (sexually transmitted infections) can greatly improve the chances of survival of the fetus and the health of the mother. Adverse outcomes such as low birth weight can be prevented through a combination of interventions to improve the nutritional status of women and prevent infections (eg, malaria and STIs) during pregnancy. More recently, the potential of the prenatal period as an entry point for the prevention of HIV (Human Immunodeficiency Virus) and care, especially for the prevention of mother-to-child transmission of HIV, has lead to renewed interest in the access and use of prenatal care services. World Health Organization recommends a minimum of four antenatal visits based on an analysis of the effectiveness of different antenatal care models. WHO guidelines are specific to the content of prenatal consultations, including: measurement of blood pressure; Urine analysis for bacteriuria and proteinuria; Blood testing to detect syphilis and severe anemia; and weight/length measurement (optional). In this framework, we present the level of health care coverage in Table 2 and the type of staff providing prenatal care to women aged 15-49 who gave birth in the two years preceding the survey in Table 15 Appendix. This table shows that access to antenatal care is relatively high in the country as a whole with 97.83% of women receiving prenatal care at least one time during pregnancy (79.03% per doctor and 44.47% per auxiliary midwife). The highest levels of prenatal care are observed in the South East and South West regions (100%); while the lowest level is in the Sidi Bouzid region (89.36%). There are few differences among children following residence (98.50% in urban areas versus 96.94% in rural areas). This coverage is around 97.06% for boys and 98.64% for girls. It increases with women’s educational attainment (from 95.55 to 100%) and the level of economic well-being of households. Of the women surveyed and concerned with antenatal care, 79.03% were examined by a physician during pregnancy; this proportion is higher in urban areas (82.69%) than in rural areas (74.23%). It is higher among women residing in the Central East region (93.57%), women with university education (93.10%), and women in the richest household category (97.87%). The lowest proportions were found among women who had never attended school (67.04%) and those in the governorate of Kairouan (67.50%) and the South West region (68.57%). This level of coverage has been low in previous decades and is approaching an average of 25% throughout the study period. The distribution is similar for blood samples with a slight decrease in the level of coverage, which drops to 94.62% in 2012 and does not exceed 24% (23.86%) over the period from 1982 until the date of the survey always with a small advantage of the southern regions. Basic characteristics of children under 5 years according to selected characteristics (Health) The second value in the table corresponds to the percentage contribution in the corresponding sample In Tunisia, two postnatal consultations are recommended: on the eighth and fortieth day after childbirth [26].. However, no question on these two visits is included in the questionnaire. This survey revealed that 85.67% of newborns had no postnatal consultation during the first 6 days after birth between 1982 and 2012, while 43.15% born in the 2 years prior to the survey received no postnatal care (Table (Table2).2). This percentage is the highest in Sidi Bouzid (88.22% over the entire period and 56.38% in 2012) and it is the lowest in the Center East (81.80 and 20.18%). There are few differences on average between urban areas (86.64%) and rural areas (84.06%). This percentage decreases with the level of economic well-being and with the level of schooling of the mother. As indicated previously, we aim to study inequality in early childhood access to basic services. Otherwise, our variables of interest are binary meaning two possibilities either access or not. So, we follow De Barros [23], Son [27] to define a dichotomous variable zi which takes a value of 1 if the ith person of specific group has access to basic opportunity and takes a value of 0 if he lacks access to the considered opportunity. It can be readily proved that (zi) = pi = (zi), where pi is the average accomplishment related to the dichotomous outcome (zi) with respect to a specific group of sample. pi could be defined otherwise as the probability that the ith person has access to a given opportunity. It depends on a vector of exogenous variables indicating the socioeconomic circumstances (such as gender, age, area of residence…) of each group, the total characteristic being k. There can be as many probability gaps between individuals/groups as there are possible combinations of group-identifying circumstances (income groups, household-size groups, gender groups…). Given a set of k circumstance variables xi1, xi2… xik, we estimate the probability pi for each child (In this study we focus particularly on children as we assume that many of the differences in opportunities are generated during childhood and carried out the whole life) by means of a logit model. Accordingly, we have the following expression of: Secondly, we compute the overall coverage rate p¯ which is the proportion of the population with access to a given opportunity using the following formula: Where wi=1n and n is the size of sample considered. Then, the Dissimilarity Index D^ can be computed as follows: After calculating the penalty which is equal to P = C × D, we get the final formula of the HOI for each service or outcome: Human opportunity index specification provides an overview in the differences between regions in terms of percentage coverage by any service in addition to dissimilarity level but it is silent about origin of inequality. To overtake this limit, we refer to Shapley Decomposition methodology that consists in identifying how each circumstance “contributes” to Inequality in access to basic services [28, 29, 13].2 This approach extends the idea of the Shapley value of cooperative games into applications for decomposing inequality. The decomposition consists of calculating the marginal contributions of each circumstance as they are removed in sequence. Following Barros et al. [11], and [13], we can measure inequality of opportunities by the penalty (P) or by the dissimilarity index (D), as defined in expressions (4) and (5) above. The value of these two measures–where P is just a scalar transformation of D–is dependent on the set of circumstances considered. Moreover, they have the important property that adding more circumstances always increases the value of P and D. If we have two sets of circumstances A and B, and set A and B do not overlap, then HOI(A,B) ≤ HOI(A); and alternatively, D(A,B) ≥ D(A). The impact of adding a circumstance A is given by: Where N is the set of all circumstances, which includes n circumstances in total; S is a subset of N that does not contain the particular circumstance A. D(S) is the dissimilarity index estimated with the set of circumstances S. D (S U{A}) is the dissimilarity index calculated with set of circumstances S and the circumstance A. The contribution of circumstance A to the dissimilarity index can be defined as: We measure variations in HOI in Tunisia in the time period surveyed based on 2 main indicator categories: (i) Malnutrition Intake, and (ii) Healthcare utilization before, during pregnancy to healthcare services in early year using data from the 2011 and 2012 (MICS4) samples.

Materials

N/A

Innovations

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

1. Telemedicine: Implementing telemedicine services can provide remote access to healthcare professionals, allowing pregnant women in remote or underserved areas to receive prenatal care and consultations without having to travel long distances.

2. Mobile health (mHealth) applications: Developing mobile applications that provide information and resources on prenatal care, nutrition, and maternal health can empower women to take control of their health and access important information at their fingertips.

3. Community health workers: Training and deploying community health workers who can provide basic prenatal care, education, and support to pregnant women in their communities can help bridge the gap in access to healthcare services, especially in rural or marginalized areas.

4. Maternal health clinics: Establishing dedicated maternal health clinics that offer comprehensive prenatal care, including regular check-ups, screenings, and counseling, can ensure that pregnant women have access to specialized care and support throughout their pregnancy.

5. Financial incentives: Implementing financial incentives, such as cash transfers or subsidies, for pregnant women to seek and receive prenatal care can help overcome financial barriers and improve access to essential healthcare services.

6. Public-private partnerships: Collaborating with private healthcare providers and organizations can help expand access to maternal health services by leveraging their resources, expertise, and infrastructure.

7. Health education campaigns: Conducting targeted health education campaigns to raise awareness about the importance of prenatal care, nutrition, and maternal health can help dispel myths and misconceptions and encourage women to seek timely and appropriate healthcare services.

8. Integration of services: Integrating maternal health services with other healthcare services, such as family planning, immunization, and HIV/AIDS prevention and treatment, can ensure comprehensive care for women throughout their reproductive journey.

9. Quality improvement initiatives: Implementing quality improvement initiatives in healthcare facilities to enhance the quality of care provided to pregnant women can help increase trust and confidence in the healthcare system, leading to improved access and utilization of maternal health services.

10. Policy reforms: Advocating for policy reforms that prioritize maternal health, such as increasing healthcare funding, improving healthcare infrastructure, and strengthening healthcare workforce capacity, can create an enabling environment for improved access to maternal health services.

AI Innovations Description

Based on the provided description, here is a recommendation that can be developed into an innovation to improve access to maternal health:

1. Strengthening Prenatal Care Services: Enhance the coverage and quality of prenatal care services to ensure that pregnant women receive comprehensive and timely healthcare. This can be achieved by:
– Increasing the number of antenatal visits: Encourage pregnant women to attend the recommended minimum of four antenatal visits, as suggested by the World Health Organization.
– Improving access to skilled healthcare providers: Ensure that pregnant women have access to qualified doctors and auxiliary midwives during their antenatal care visits.
– Providing essential information and education: Use the prenatal period to educate women and families about warning signs, symptoms, and risks related to labor and delivery, as well as birth spacing and other important factors for infant survival.
– Offering necessary vaccinations and treatments: Provide vaccinations for tetanus and prevent and treat malaria, anemia, and sexually transmitted infections during pregnancy to improve the health of both the mother and the fetus.

By implementing these recommendations, pregnant women will have better access to essential healthcare services, leading to improved maternal and neonatal health outcomes.

AI Innovations Methodology

To improve access to maternal health, here are some potential recommendations:

1. Strengthening healthcare infrastructure: Investing in healthcare facilities, equipment, and trained healthcare professionals in areas with limited access to maternal health services can help improve access and quality of care.

2. Mobile health clinics: Implementing mobile health clinics that can reach remote and underserved areas can provide essential maternal health services, including prenatal care, vaccinations, and postnatal care.

3. Telemedicine: Utilizing telemedicine technologies can enable pregnant women to access healthcare services remotely, reducing the need for travel and improving access to medical advice and consultations.

4. Community health workers: Training and deploying community health workers who can provide basic maternal health services, education, and support in local communities can help bridge the gap in access to healthcare.

5. Financial incentives: Implementing financial incentives, such as cash transfers or subsidies, for pregnant women to seek and receive maternal health services can help overcome financial barriers and improve access.

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

1. Define the indicators: Identify specific indicators that measure access to maternal health, such as the percentage of pregnant women receiving prenatal care, the percentage of births attended by skilled health personnel, or the percentage of women receiving postnatal care.

2. Collect baseline data: Gather data on the current status of the selected indicators in the target population or region.

3. Define the intervention scenarios: Develop different scenarios based on the recommendations mentioned above, specifying the extent and coverage of each intervention.

4. Simulate the impact: Use statistical or mathematical models to simulate the impact of each intervention scenario on the selected indicators. This can involve analyzing the potential increase in the percentage of pregnant women receiving prenatal care, the reduction in maternal mortality rates, or other relevant outcomes.

5. Compare and evaluate the scenarios: Compare the simulated results of each intervention scenario to assess their potential impact on improving access to maternal health. Evaluate the feasibility, cost-effectiveness, and sustainability of each scenario.

6. Refine and adjust: Based on the simulation results, refine and adjust the intervention scenarios as needed to optimize their impact on improving access to maternal health.

7. Implement and monitor: Once the most promising intervention scenarios are identified, implement them in real-world settings and closely monitor their implementation and impact. Continuously collect data to assess the actual changes in access to maternal health and adjust the interventions accordingly.

By following this methodology, policymakers and healthcare providers can gain insights into the potential impact of different innovations and interventions on improving access to maternal health and make informed decisions on implementing the most effective strategies.

Author

Dima Health

Statistics:

Citations: 13

Identifiers:

DOI: 10.1186/s12955-017-0777-7

Research Areas:

Community Interventions, Disparities, Food Security, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Noncommunicable Diseases, Quality of Care, Sexual and Reproductive Health, Social Determinants, Technology and Innovations

Study Countries:

Tunisia

Study Design:

Cross Sectional Study, Phenomenological Study, randomised-control-trial

Study Approach:

Quantitative

Participants Gender:

Male & Female