Sources of Health Care Among Under-5 Malawian Children With Diarrhea Episodes: An Analysis of the 2017 Demographic and Health Survey

listen audio

Study Justification:
– Diarrhea is a leading cause of morbidity and mortality, especially in Sub-Saharan Africa.
– Implementing universal coverage of available interventions can prevent diarrhea-related illnesses.
– This study aimed to identify factors associated with the choice of health care source for under-5 children with diarrhea.
Study Highlights:
– The study used data from the 2017 Demographic and Health Survey in Malawi.
– Factors associated with the choice of health care source included education, income, and rural living.
– Public health facilities were the main source of health care service (79.9%).
– Reducing under-5 mortality due to diarrhea requires addressing inequalities in accessing and utilizing health care services.
Study Recommendations:
– Increase access to education to reduce self-medication of children with diarrhea.
– Improve income opportunities to encourage seeking care from private facilities like pharmacies.
– Address rural-urban disparities to ensure equal access to health care services.
Key Role Players:
– Ministry of Health: Responsible for implementing policies and interventions to improve health care access and quality.
– Health care providers: Including doctors, nurses, and pharmacists, who deliver care to children with diarrhea.
– Community health workers: Play a crucial role in educating caregivers and promoting health-seeking behaviors.
– Non-governmental organizations (NGOs): Provide support and resources to improve health care services.
Cost Items for Planning Recommendations:
– Education programs: Budget for initiatives to increase access to education, including awareness campaigns and school infrastructure.
– Income generation programs: Allocate funds for income-generating activities and job creation to improve household income.
– Health facility improvement: Invest in infrastructure, equipment, and training to enhance the quality of health care services.
– Community health worker training and support: Provide resources for training, supervision, and incentives for community health workers.
– NGO support: Allocate funds for partnerships and collaborations with NGOs to implement interventions and programs.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study utilized data from the 2017 Demographic and Health Survey, which provides a comprehensive picture of the key social demographic and health challenges facing the Malawian population. The study used a multinomial logistic regression model to identify factors associated with the choice of health care source among caretakers seeking treatment for under-5 children with diarrhea illness. However, there are some areas for improvement. The abstract does not provide information on the sample size or representativeness of the study population, which could affect the generalizability of the findings. Additionally, the abstract does not mention any limitations of the study, such as potential biases or confounding factors. To improve the evidence, it would be helpful to include these details and address any limitations in future research.

Diarrhea is a leading cause of morbidity and mortality in the world but mostly in Sub-Saharan Africa. These could be prevented if universal coverage of current available interventions were implemented. The study aimed to identify factors associated with the choice of health care source among caretakers seeking treatment for under-5 children with diarrhea illness. Using women’s questionnaire we extracted a subset of data of children aged 0 to 59 months from the 2017 Demographic & Health Survey. Questions regarding history of childhood diarrhea for the past 24 hours or last 2 weeks prior to the survey were key in data extraction. Caregivers were asked to report the place where they sought treatment. In this study, 4 types of health facilities were defined: public, private, pharmacies, and other unspecified sources. A multinomial logistic regression model was used to identify sources of health facility used and corresponding factors associated with the choice. Factors associated with choice of health care source included education (educated women were less likely to self-medicate their children [relative risk ration (RRR) = 0.46; 95% confidence interval (CI) = 0.22-0.94]), income (better income earning families were more likely to seek care from private facility such as pharmacy [RRR = 1.87; 95% CI = 1.14-3.09]), and rural living (those in rural areas were more likely to seek treatment from other unspecified sources [RRR = 7.33, 95% CI = 1.40-38.36]). Public health facilities (79.9%) were the main source of health care service; however, reducing under-5 mortality due to diarrhea illness would require significant efforts to address other inequalities in accessing and utilizing health care services.

The 2015-2016 Demographic and Health Survey (MDHS) was conducted from October 2015 through February 2016 and sought to provide current estimates of basic health and demographic indicators of the population. The survey provided a comprehensive picture of the key social demographic and health challenges facing the Malawian population specifically focusing on maternal and child health. The Malawian Population and Housing Census conducted in 2008 served as the sampling frame for the 2015-2016 MDHS. This consisted of a complete list of all census standard enumeration areas (SEAs) defined as a geographic area that covers an average of 235 households. Hence, the census frame contained information about the location of the SEAs, the type of residence (rural vs urban), and the estimated number of residential households. In addition, Malawi has 3 main regions (North, Central, and South) divided into 28 districts. Using information from the sampling frame, each district was stratified into rural and urban denomination, which yielded 56 sampling strata. A 2-stage sampling approach was used for the 2015-2016 MDHS. The first stage of the survey involved a selection of 850 SEAs, including 173 SEAs in urban areas and 677 SEAs in rural areas with a probability proportional to the SEA size with independent selection in each of the sampling stratum. Within each of the selected SEAs, all households were listed; this listing served as a sampling frame for the selection of households at the second stage of the sampling process. In the second stage of selection, a fixed number of 30 households per urban cluster and 33 per rural cluster were selected with an equal probability systematic selection from the newly created household listing. All women aged 15 to 49 years, who were either permanent residents of the selected households or visitors who stayed in the households the night before the survey, were eligible to be interviewed. In about one third of all sampled households, all men aged 15 to 54 years, including those who were usual residents and others who stayed in the household the night before the interview, were eligible for individual interview. The women’s questionnaire gathered data from all eligible women, pertaining to their background characteristics, reproductive history, family planning, maternal and child health, breastfeeding and nutrition, marriage and sexual activity, fertility preferences, husbands, and background among others. Data obtained from the women’s questionnaire were used to extract a subset of data on children between ages 0 and 59 months. Women were asked whether any of their child had diarrhea in the last 24 hours or within the last 2 weeks prior to the survey. For each child with a known diarrheal episode within this timeframe, women were requested to report the place at which medical treatment or advice was sought for the last episode of diarrhea that the child had. Type of health care facility sought by the caregivers as the dependent variable was defined as follows: We isolated pharmacies, shops, and market as a single group because research has shown that in many Sub-Saharan African countries, informal pharmacies, drug shops, and markets are important channels for health care treatment.18,19 We wanted to test whether such assumption would hold true for children with diarrhea episode in the context of Malawi, yet we also strove to document the profile of children that were seeking care through those channels for diarrhea episode. Therefore, our dependent variable consists of 4 categories: (1) public, (2) private–non-pharmacy, (3) pharmacy, and (4) other (traditional healers, MACRO, etc). Independent variables included the following: Sources of drinking water was categorized into “improved” (piped into dwelling, piped into yard/plot, piped to neighbor, public tap/standpipe, or tube to well or borehole), “unimproved” (unprotected well, unprotected spring, and river or dam or lake or ponds), other sources (rainwater, cart with small tank, and other unspecified sources), and not de jure residents. Not de jure resident children were excluded from the final model because data were collected at the household level and assigned to individuals in the data. Therefore, most of the information regarding those children were missing. Summary measures including weighted frequencies and percentages for categorical variables were derived from the baseline characteristics of the study population. Univariate analysis was performed to document the association between socioeconomic and demographic characteristics of the study participants with the dependent variable, health care source. A bivariate and multivariate multinomial logistic regression models were fitted and relative risk ratio (RRR) with the associated 95% confidence interval (CI) were reported to investigate the relationship between dependent variable, health care source, and covariates. Besides, with regard to P value, as stated by the American Statistical Association (https://amstat.tandfonline.com/doi/pdf/10.1080/00031305.2016.1154108?needAccess=true), practice that reduce data analysis or scientific inference to mechanical “bright-line” rules (such as P < .05) for justifying scientific claims or conclusion can lead to erroneous beliefs and poor decision making. It is recommended that researchers should bring many contextual factors into play to derive scientific inference including the study design, the quality of measurements, the external evidence, and the validity of the assumption that underlines data analysis. Given the fact that we did not control for many contextual factors (road infrastructures for ease of access to health facilities, level of health professional training across different health facility types, etc) we reported also any P value <.10). This allowed us to consider any such factors that could be further investigated, while controlling for more contextual factors and external evidence. This was not required as data were extracted directly online from the National Demographic Health Survey of Malawi.

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

1. Mobile Health (mHealth) Solutions: Develop and implement mobile applications or text messaging services that provide pregnant women and new mothers with important health information, reminders for prenatal and postnatal care appointments, and access to teleconsultations with healthcare providers.

2. Community Health Workers: Train and deploy community health workers to provide maternal health education, support, and referrals in rural and underserved areas. These workers can conduct home visits, organize community health events, and serve as a bridge between the community and formal healthcare facilities.

3. Telemedicine: Establish telemedicine networks to connect remote healthcare facilities with specialist doctors in urban areas. This would enable healthcare providers in rural areas to consult with specialists and receive guidance on complicated maternal health cases, improving the quality of care available locally.

4. Maternal Waiting Homes: Set up maternal waiting homes near healthcare facilities in remote areas. These homes would provide accommodation for pregnant women in the weeks leading up to their due dates, ensuring they have timely access to skilled birth attendants and emergency obstetric care.

5. Transportation Solutions: Improve transportation infrastructure and services to facilitate access to healthcare facilities for pregnant women, especially in rural areas. This could involve providing ambulances or other means of transportation for emergency obstetric referrals and organizing community transportation systems for routine antenatal care visits.

6. Financial Incentives: Implement financial incentives, such as conditional cash transfers or vouchers, to encourage pregnant women to seek and utilize maternal health services. This could help alleviate financial barriers and increase demand for quality care.

7. Public-Private Partnerships: Foster collaborations between public and private healthcare providers to expand access to maternal health services. This could involve contracting private facilities to provide subsidized or free maternal health services, leveraging their resources and expertise to reach more women.

8. Health Information Systems: Strengthen health information systems to collect and analyze data on maternal health indicators. This would enable policymakers and healthcare providers to identify gaps in access and quality of care, and make evidence-based decisions to improve maternal health outcomes.

These are just a few examples of innovations that could be considered to improve access to maternal health. It is important to assess the local context and engage stakeholders to determine the most appropriate and effective strategies for each specific setting.
AI Innovations Description
Based on the information provided, the recommendation to improve access to maternal health would be to focus on addressing the factors associated with the choice of health care source among caretakers seeking treatment for under-5 children with diarrhea illness.

The study identified several factors that influenced the choice of health care source, including education, income, and rural living. Educated women were less likely to self-medicate their children, indicating a need for increased health education and awareness. Families with better income were more likely to seek care from private facilities such as pharmacies, suggesting the importance of making healthcare services more affordable and accessible. Additionally, those in rural areas were more likely to seek treatment from other unspecified sources, highlighting the need for improved healthcare infrastructure and services in rural areas.

To develop this recommendation into an innovation, the following steps can be taken:

1. Education and Awareness Campaigns: Implement targeted education and awareness campaigns to educate caretakers, especially women, about the importance of seeking proper medical care for their children’s diarrhea illness. This can include providing information on the potential risks of self-medication and the benefits of seeking professional healthcare.

2. Affordable Healthcare Services: Work towards making healthcare services, particularly in private facilities such as pharmacies, more affordable for families with lower incomes. This can be achieved through subsidies, insurance coverage, or partnerships with pharmaceutical companies to provide discounted medications.

3. Improving Healthcare Infrastructure: Invest in improving healthcare infrastructure in rural areas to ensure that there are adequate facilities and resources available for the treatment of diarrhea illness in children. This can include building new healthcare centers, improving transportation networks to facilitate access to healthcare facilities, and training healthcare professionals to provide quality care.

4. Community Engagement: Engage with local communities to understand their specific healthcare needs and preferences. This can involve collaborating with community leaders, conducting community health assessments, and involving community members in the planning and implementation of healthcare initiatives.

5. Data Collection and Analysis: Continuously collect and analyze data on healthcare utilization and outcomes to monitor the effectiveness of the implemented interventions. This will help identify any gaps or areas for improvement and inform future decision-making.

By implementing these recommendations, it is possible to improve access to maternal health and reduce under-5 mortality due to diarrhea illness in Malawi.
AI Innovations Methodology
To improve access to maternal health, here are some potential recommendations:

1. Mobile health clinics: Implementing mobile health clinics that travel to remote areas can provide essential maternal health services to underserved populations. These clinics can offer prenatal care, postnatal care, and family planning services.

2. Telemedicine: Utilizing telemedicine technologies can connect pregnant women in remote areas with healthcare professionals who can provide virtual consultations, monitor pregnancies, and offer guidance and support.

3. Community health workers: Training and deploying community health workers can help bridge the gap between healthcare facilities and communities. These workers can provide education, counseling, and basic healthcare services to pregnant women in their own communities.

4. Maternal waiting homes: Establishing maternal waiting homes near healthcare facilities can provide a safe and comfortable place for pregnant women to stay as they approach their due dates. This reduces the distance and time required to reach a healthcare facility when labor begins.

5. Financial incentives: Implementing financial incentives, such as cash transfers or subsidies, can help reduce the financial barriers that prevent pregnant women from seeking maternal healthcare services.

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

1. Define the target population: Identify the specific population group that would benefit from the recommendations, such as pregnant women in rural areas.

2. Collect baseline data: Gather data on the current access to maternal health services in the target population, including factors such as distance to healthcare facilities, utilization rates, and health outcomes.

3. Model the interventions: Use mathematical modeling techniques to simulate the implementation of the recommended interventions. This could involve estimating the coverage and effectiveness of each intervention and how they interact with each other.

4. Simulate outcomes: Run simulations to estimate the potential impact of the interventions on access to maternal health services. This could include measures such as increased utilization rates, reduced travel distances, and improved health outcomes.

5. Sensitivity analysis: Conduct sensitivity analysis to assess the robustness of the results and explore the potential impact of variations in key parameters, such as intervention coverage or effectiveness.

6. Interpret and communicate results: Analyze the simulation results and interpret the findings in terms of the potential improvements in access to maternal health services. Communicate the results to stakeholders and policymakers to inform decision-making and prioritize interventions.

It is important to note that the methodology described above is a general framework and the specific details may vary depending on the context and available data.

Partagez ceci :
Facebook
Twitter
LinkedIn
WhatsApp
Email