An assessment to inform programming for antenatal care services in six health facilities in Geita Region, Tanzania: a cross-sectional baseline survey

An assessment to inform programming for antenatal care services in six health facilities in Geita Region, Tanzania: a cross-sectional baseline survey | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article An assessment to inform programming for antenatal care services in six health facilities in Geita Region, Tanzania: a cross-sectional baseline survey Augustino Hellar, Alen Kinyina, Phineas Sospeter, Yusuph Kulindwa, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4829306/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Globally, every two minutes, a woman dies during pregnancy or childbirth, and each day, about 6,300 newborns die. Most of these deaths are preventable. Despite global efforts to improve coverage and access to maternity care, mortality rates remain stubbornly high. The World Health Organization (WHO) recommends a minimum of eight antenatal care (ANC) contacts with early initiation during the first trimester (before 12 weeks). This baseline assessment aimed to determine the current status of ANC services in selected facilities before launching a pilot study. The pilot will focus on digital solutions, including the use of machine learning models, to facilitate prompt decision-making and early detection of maternal complications, ultimately helping to prevent complications during pregnancy. Methods This cross-sectional study involved an analysis of records from women attending ANC contacts at six selected health facilities from January to December 2022. Data were obtained from Health Management Information System (HMIS) registers—ANC and Labor and Delivery—and extracted from the District Health Information System 2 (DHIS2) to analyze ANC practices and maternal complications respectively. Descriptive analysis was performed using frequency/percentages A multivariate logistic analysis was conducted to identify factors associated with presence or absence of anaemia (> 11g/dl). Results Records from 657 women who received ANC and labour and delivery services across six health facilities were reviewed. 599 had a record of the number of contacts they had made. Only 34% of these women attended the WHO-recommended four or more ANC contacts (ANC4+), and just 19% initiated ANC during the first trimester. Additionally, 48.2% of the women with hemoglobin records (n = 440) were diagnosed with anaemia. While most women received two doses of supplemental iron for anaemia prevention, there was a notable decline in the administration of the third and fourth doses. In the multivariate analysis, women with four or more ANC visits were 2.7 times more likely to have normal haemoglobin levels than those with fewer visits. Coverage for Intermittent Preventive Treatment for Malaria (IPT) was 43.3%. Data extracted from DHIS2 showed a high proportion of postpartum haemorrhage (PPH) cases (n = 147). Conclusion These baseline findings highlight significant gaps in antenatal care practices and maternal health outcomes in the assessed facilities, underscoring the need for innovative approaches. Our proposed intervention, integrating artificial intelligence, group antenatal care (GANC), and community interventions, aims to enhance early ANC initiation, improve adherence to recommended visits, and predict and recognize maternal complications early, thereby improving maternal and fetal outcomes. Antenatal Care Antenatal Risk Stratification Digital Health in Maternal Care Baseline Assessment Group Antenatal Care Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction According to UNICEF, the number of maternal deaths declined by 35% between 2000 and 2017, However, over 800 women are still dying every day, majority of them in sub-Saharan Africa from preventable pregnancy or childbirth complications [ 1 ]. Despite continuous efforts to improve maternal health, Tanzania is still facing challenges in reducing maternal complications and fatalities to the desired levels. The current maternal mortality rate remains significantly high at 104 per 100,000 live births, which is still higher than the desired Sustainable Development Goal (SDG) target of 70 per 100,000 live births [ 2 ]. Maternal mortality in Tanzania has been reported to stem from a variety of causes, such as eclampsia, hemorrhage and sepsis [ 3 ]. Child mortality is similarly high, at 24 deaths per 1,000 livebirths (TDHS 2022) double the SDG Target of < 12 deaths per 1,000 livebirths [ 2 ] Antenatal care presents a unique opportunity for early detection and management of pregnancy-related complications, leading to improved pregnancy outcomes. WHO recommends a minimum of 8 contacts at the health facility during the antennal period [ 4 ]. Recent findings from the Tanzania Health and Demographic Survey (TDHS) show that about 65% of pregnant women had four or more ANC visits/contacts as recommended [ 2 ]. However, the high maternal mortality rate suggests that this improvement has not directly translated into reducing mortality. Worsening this situation is the fact that majority of the women, especially in rural settings in Tanzania, start ANC quite late [ 5 ]. This emphasizes the urgent need to promote ANC attendance and enhance the quality of care provided during pregnancy and childbirth, both at healthcare facilities and within communities and households. One significant contributing factor to the late identification of maternal complications during antenatal care is the inadequate health information systems in these settings [ 6 ]. Lack of proper maternal health information and poor data quality at the primary health care level hinders health care providers from identifying complications early [ 6 , 7 ]. Consequently, pregnant women face substantial risks of morbidity and mortality. In such a challenging environment, digital health solutions have been identified to have the potential of contributing to early identification of complications in pregnancy. [ 8 ]. A recent meta-analysis done in Africa and other LMICs showed a steady growth of digital innovations for maternal health in these countries, providing a unique opportunity to employ digital health systems for maternal and newborn mortality reduction [ 9 ]. However, there are also other limitations in the quality of the interventions provided in these settings due to weak health systems and other factors. One study in Rufiji, Tanzania [ 10 ] reported that although ANC participants received basic clinical evaluations such as blood pressure measurements and abdominal examinations, more targeted and thorough investigations such as testing for albumin, hemoglobin or blood glucose, were rarely done. Implementing digital solutions, complemented by innovative care models, provides a unique opportunity to improve maternal and fetal outcomes by helping health providers link danger signs and clinical conditions, thus preventing adverse outcomes during pregnancy. This is where digital solutions such as artificial intelligence (AI) can play a vital role. It has also been shown that early ANC attendance promotes utilization of preventive measures by pregnant mothers during the antenatal period [ 11 , 12 ]. Women who start ANC services early and frequently are more likely to use key interventions such as intermittent preventive treatment for malaria and iron supplementation to prevent anemia [ 4 ]. Improvement in maternal outcomes will be facilitated by innovative approaches that promote integrated, and high-impact interventions to address the high maternal mortality rate in Tanzania. Prime Health Initiative Tanzania is a local non-governmental organization (NGO) that has received funding by the Bill and Melinda Gates Foundation to implement a 2-years project aiming at piloting an antenatal risk stratification system using Artificial Intelligence (AI) technology. The primary objective is to promptly identify maternal risks among pregnant mothers in the Geita region of Tanzania. This will enable early interventions and management to prevent potential adverse maternal and fetal outcomes. If successful, this project has the potential to be scaled up in other health facilities in the region or elsewhere in Tanzania. The project will be implemented at six health facilities in two semi-urban/rural districts in Geita region. Prior to the implementation of the proposed project, a comprehensive baseline assessment was conducted on to establish the status of ANC services in the targeted facilities. This paper presents the key findings derived from the assessment, with a specific focus on facility capacity, ANC attendance rates and patterns, maternal complications and other key practices related to antenatal care in the region. The baseline assessment provides vital information on the strengths, weaknesses, and gaps in the current ANC services. This critical exercise serves as a foundation for planning, refining, and tailoring the project interventions' design. It also sets grounds for future comparison to understand the impact of the project after its implementation. The paper summarizes key baseline parameters for antenatal care in Geita region, including facility capacity, availability of electronic health management information systems (HMIS), ANC attendance and timing and the overall state of antenatal care in these facilities. Methods Study Design This was a cross-sectional study involving an analysis of records from women attending ANC visits in six selected health facilities during the assessment period (January to December 2022. We used data from HMIS registers – ANC and Labor and Delivery – to obtain information about pregnant mothers who attended ANC in the six facilities during the assessment period. Cutt-off points on ANC and labor parameters (birth weight, hemoglobin concentration and age group categories) were based on the World Health Organization standards and other peer reviewed studies. Data from the District Health Information System 2 (DHIS2) from the same period was used to make comparisons on the proportions of maternal complications, anaemia and maternal & neonatal deaths. Study Location The study facilities are located in 2 Districts and include Chato District Hospital, Bwanga Health Center, and Butengorumasa Dispensary (In Chato District Council) and, Nzera District Hospital, Katoro Health Center, and Nkome Dispensary (in Geita District Council) both within Geita region in Tanzania. The dispensary is the lowest level of health care delivery in the country with basic normal delivery services, while health centers and district hospitals are the subsequent level of care, with more infrastructure and human resources for labor and delivery, including Comprehensive Emergency Obstetric and Neonatal Care (CEmONC). Sample Size We employed convenience sampling to examine all available records from the registers at each health facility during the review period. This encompassed antenatal care (ANC) registers and labor and delivery registers. To gather data on maternal complications, we extracted information from the District Health Information System 2 (DHIS2) for these facilities, reported during the same period. Data Collection Methods We trained data enumerators on data collection methods and tools. The data collectors visited each facility in person to gather information from the following sources: 1) NOH ANC Registers at the Antenatal Clinics and 2) MOH Labor and Delivery Registers at labor wards. Data from 657 women was extracted during this period from the ANC and labor registers. Additionally, data from the DHIS2 was retrieved online for the same period (January to December 2022) to analyze maternal and newborn complications reported in each study facility. Data was extracted manually from the registers into pre-designed data collection forms for analysis later. Regular supervision visits by the study lead and the project staff ensured adherence to data collection protocols. Data analysis The final data set was transformed to excel 2019 and then to Stata (version 15.0) statistical software for analysis. Data was analyzed descriptively using frequency (percentages) and median (interquartile range [IQR]). Chi-square (χ2) used to test for significance of the associations between outcome indicators and the independent variables. All statistical inferences were set to significance level of 5% (α = 0.05). Data was presented in tables, cross-tabulations (demonstrating relationships between independent and dependent variables), pie charts and histograms. A further description of the analysis is given in Fig. 1 . Ethical Considerations: The study team submitted the baseline study proposal and all data collection tools to the National Health Research Ethics Committee (NatHREC) as assurance that the study team was committed to protect the study participants and the data that would be generated as part of the baseline implementation. This study was approved with Ethical Clearance Certificate reference number NIMR/HQ/R.8a/Vol.IX/4194. Results Records from 657 women with ANC and labor and delivery records were reviewed. The results are shown in the tables and figures below: Table 1 Facility Characteristics Facility Name Level # of Beds Monthly ANC Attendance No of Doctors (MD) Use of Electronic HMIS Nzera District Hospital 130 370 4 No Chato District Hospital 120 600 12 No Bwanga Health Center 100 1600 6 No Katoro Health Center 110 1400 3 No Nkome Dispensary 11 500 0 No Butengorumasa Dispensary 6 380 0 No Health Centers had the largest volume of women attending ANC services. None of the facilities was using an electronic health medical information system (HMIS) ANC Attendance We analyzed data from the 657 women who attended ANC services and described various parameters such as age distribution, number of visits throughout pregnancy and gestation age during ANC initiation. 599 of them had complete records on the number of ANC visits they had made throughout their pregnancy period (See Fig. 1 ). Only 34% of the women who had ANC contacts records were found to have attended 4 or more ANC visits (Fig. 2 ). Because the current Data registers at the facilities are still using the previous cut-off points for ANC visits, it was only possible to analyze those attending less than four contacts and those who has four contacts or more. Majority of women who attended ANC in these facilities were in the age group 18–28 years i.e. 65.4% (Fig. 3 ). Out of the 657 women who were reported in the study facilities, majority (54%) had initiated ANC between 13–24 weeks of gestation (Fig. 4 ). Very few (19%) had initiated ANC at 12 weeks or below. Majority of women (54%) initiated ANC visits during the second trimester of their pregnancy, with only 19% being seen during the first trimester. ANC Interventions Key ANC interventions provided to mothers during ANC were assessed. These included hemoglobin checks for presence of anemia, iron and folic acid supplementation and intermittent preventive therapy (IPT) for malaria. Table 2 Prevalence of anemia reported among mothers attending ANC (n = 440) Normal (> 11g/dl) Mild (10.0 -10.9 g/dl) Moderate (7.0–9.9 g/dl) Severe (< 7g/dl) Total 228 (51.8% 110 (25%) 98 (22.2%) 4 (1%) 440 (100%) Almost half (48.2%) of the women (with hemoglobin results recorded) were recorded to have anemia. 1% of them had severe anemia (Hb level below 7g/dl) Table 3 Multivariate Logistic Regression Analysis of Factors Associated with Hb levels > 11g/dl Variable Odds Ratio 95% Conf. Interval p = value ANC Visits 4+ 2.749114 5.977355 0.011 Mebendazole use 1.675982 4.100463 0.256 Iron Supplementation 0.998055 10.24644 0.999 IPT use 1.158734 3.564585 0.797 In the multivariate analysis, using logistic regression with hemoglobin level being a dependent variable, women with 4 or more ANC (4+) visits were 2.7 more likely to have normal Hb level above 11g/dl than those with less than 4 visits (p = 0.011). We also analyzed Iron and Folic acid supplementation as reported in the HMIS registers. Out of the 657 women attending ANC, majority received the first and second dose of Iron and Folic Acid supplementation at 87% and 67% respectively (Fig. 5 ). The trend shows a with a sharp decline in this proportion for the third and fourth doses. Regarding the use of Intermittent Preventive Therapy for Malaria Prevention (IPT), less than half of the women (43.3%) received at least 3 doses of Intermittent Preventive Therapy for Malaria. Coverage of those getting only one does was 14% and those getting only 2 doses was 16% (Fig. 6 ). Maternal and Fetal Complications during ANC, Labor, and Delivery All maternal and fetal complications reported in the DHIS2 during the analysis were analyzed and categorized by type and facility as shown in Fig. 7 . All facilities reported a significant number of post-partum hemorrhage cases. Chato DH has a particularly high number of stillbirths reported. One of the facilities (Chato District Hospital), had a very high number of reported stillbirths in DHIS2 during the reporting period. Discussion The current study aimed to assess facility capacity, ANC coverage, occurrence of maternal complications and key ANC interventions in six healthcare facilities within Geita region. We describe key capacity parameters such as facility level, bed capacity, monthly ANC attendance, and availability of HMIS systems. We note that none of the facilities used electronic medical records before this assessment, implying that our project will need to strengthen this component before starting implementation. Additional insights that will serve as a foundational understanding of the status of antenatal care in these facilities are further discussed below. ANC Attendance: Timing and Frequency: The proportion of women receiving 4 or more ANC visits in this study was 34%. This is much lower than the proportion reported in the 2022 TDHS (65%) and from other literature in Tanzania [ 11 ]. This assessment was conducted in a rural/semi-urban setting. Prior assessments have shown that the number of ANC visits tend to be lower in rural vs urban settings, as reported in the 2022 TDHS [ 2 ]. This finding is significant to our project, since it means that most women in the project area do not receive the WHO-recommended ANC contacts during pregnancy. Our intervention will therefore focus on exploring potential barriers to ANC attendance, such as accessibility, awareness, and cultural beliefs, and develop strategies to encourage and support regular ANC visits. The study also examined demographics and ANC utilization factors among women attending ANC services. Most women were in the age group of 18–28 years, suggesting that the project will need to tailor ANC services to address the specific health needs and preferences of this age group. Gestation Age at Initiation of ANC: The study found that most women, initiated ANC visits during the second trimester i.e., at 13–24 weeks of pregnancy. These findings are comparable to other studies that reported late initiation of ANC in Tanzania [ 12 , 13 , 14 ]. WHO recommends at least one contact with the pregnant woman during the first trimester, highlighting the need for early ANC initiation. From these findings, we recognize the need to analyze various barriers to early initiation of ANC in this community and thus tailor interventions to address them. Some of the barriers for late ANC initiation highlighted in other studies in Tanzania, include traditional and cultural beliefs, unpleasant experience in past pregnancies, shortage of health care workers and perceptions about inadequate quality of care [ 13 , 14 ]. One study conducted in a similar setting in Rwanda recommended replacing traditional approaches with innovative models to enhance ANC seeking behavior [ 15 ] and promote early initiation. ANC Interventions The prevalence of anaemia in pregnancy in this study was found to be 48.2%. This is comparable to studies done elsewhere in Tanzania and elsewhere in Africa [ 16 , 17 , 18 ]. A study in a rural setting in Tanzania reported a much higher prevalence of anaemia in pregnancy, signifying the need for anaemia prevention measures in our setting [ 19 ]. There is a need to find innovative approaches to enhance Iron and folic acid supplementation uptake, as recommended by WHO. The multivariate analysis using logistic regression demonstrated that attending four or more ANC visits (OR = 2.74, p = 0.011) significantly increases the likelihood of having higher Hb levels (above 11). Other variables, including mebendazole use (OR -1.67, p = 0.256), iron supplementation (OR = 0.99, p-value = 0.99), and IPT use (OR = 1.15, p = 0797), did not show a statistically significant association with Hb levels in this analysis. These findings are comparable to a study in Ghana that showed a similar association [ 20 ] During this baseline assessment, we observed a decline in the proportion of women receiving the third and fourth doses of Iron and Folic Acid supplementation. This signifies that there are potential barriers to consistent care. We plan to explore additional community level interventions, that can be implemented in the project facilities and promoted through peer-support and community health workers who will be part of our planned GANC model. The coverage of 3 doses Intermittent Preventive Therapy for Malaria (IPTp3+) was reported 43.3%. This was comparable to other studies done elsewhere in Africa [ 21 , 22 ]. It will be critical to analyze and address factors that may influence acceptability and uptake of IPTp3 + as outlined elsewhere in Tanzania [ 23 ]. Maternal Complications: Maternal complications are a significant concern and were evident across all facilities during the assessment period. The assessment of maternal complications revealed important patterns across the project facilities. Postpartum hemorrhage (PPH) was the most frequently reported complication, affecting women across all facilities. This picture is similar to the findings from a 10-year mortality by Bwana et al in 24 public hospitals in the country [ 3 ]. The finding highlights the need for targeted interventions to improve the management of PPH and its prevention through appropriate antenatal and postnatal care. Chato District Hospital reported a notably high number of stillbirths, signaling the necessity of focused efforts to address this issue. Limitations: Several limitations are acknowledged in this study. Firstly, the data collected were based on the assessment period (January – December 2022), which may not fully represent the long-term performance of the facilities. Secondly, the study focused on a rural and semi-urban geographic area, that may limit the generalizability of the findings to urban settings. Lastly, the reliance on reported maternal complications may be subject to underreporting or poor documentation in these health facilities. Conclusion Our findings shed light on the strengths and areas for improvement in the provision of ANC services in the project facilities. Efforts should be made to address common maternal complications such as PPH, and strategies to improve ANC attendance and early initiation of ANC should be prioritized. Targeted interventions, capacity-building, and quality improvement initiatives can collectively contribute to enhancing maternal and child health outcomes in the project area. The proposed AI-powered antenatal risk stratification system holds promise in addressing these challenges. By leveraging advanced algorithms to analyze health data, this system can identify high-risk pregnancies promptly, enabling healthcare providers to intervene early and provide targeted care. Integration with the Group Antenatal Care (GANC) model presents a unique opportunity to facilitate peer support and education among pregnant women, potentially enhancing their engagement in care and health-seeking behaviors. This study sets the stage for a transformative initiative that could reshape maternal healthcare in Geita region. By understanding the current state of antenatal care, the project can tailor interventions to address specific gaps and needs. The integration of digital health technology and innovative care models aligns with global efforts to leverage technology for improved healthcare outcomes. This initiative's success could serve as a model for other regions facing similar challenges, reducing maternal morbidity and mortality. As the project progresses, ongoing monitoring and evaluation will be critical to assess the impact and effectiveness of the AI-powered risk stratification system in improving maternal health outcomes. Abbreviations ANC: Antenatal care DHIS2: District Health Management System (Version 2) GANC: Group Antenatal Care Hb: Haemoglobin HMIS: Health Medical Information System IPTp3+: Intermittent Presumptive Therapy for Malaria (3 doses) LMICs: Low- and Middle-Income Countries MOH: Ministry of Health PPH: Postpartum Hemorrhage SDGs: Sustainable Development Goals TDHS: Tanzania Demographic Health Survey WHO: World Health Organization Declarations Ethics approval As part of the larger Antenatal Risk Stratification Pilot Project in the Geita region, we obtained ethical clearance from the National Health Research Ethics Committee (NatREC), with the Ethical Clearance Certificate reference number NIMR/HQ/R.8a/Vol.IX/4194. Since this study was not a clinical trial, it did not require a clinical trial registration number. This study was conducted according to CIOMS Guidelines on use of retrospective data and NatREC guidelines, the local ethical review board in Tanzania. Consent to Participate This study was a cross-sectional survey that utilized anonymous data from MOH HMIS registers and DHIS2 systems., hence obtaining individual consent from participants was not feasible since the data is anonymized. However, we obtained ethical clearance to conduct this study from the local ethical review board, NatREC, with reference certificate number NIMR/HQ/R.8a/Vol.IX/4194. Consent for publication “Not applicable” Availability of data and materials The datasets generated during this baseline assessment are not publicly available due privacy and data protection reasons as guided by the Ministry of Health in Tanzania and the National Institute for Medical Research (NIMR) but are available from the corresponding author on request. Any requests for data access should be directed to the corresponding author (Dr. Augustino M. Hellar, email: [email protected] ) Anyone who wishes to use the data must ensure confidentiality and appropriate use of this study data. The authors will determine and decide to share any additional materials related to this assessment upon request. Competing interests We declare no financial or non-financial competing interests must be declared in this section. Funding The baseline survey that collected data used for this study was funded as part of the Mlinde Mama project, implemented by the Prime Health Initiative Tanzania in partnership with the Tanzania Ministry of Health and President's Office, Regional Administration and Local Government with funding from the Bill and Melinda Gates Foundation. Anyone who wishes to use the data must ensure confidentiality and appropriate use of this study data. The authors will determine and decide to share any additional materials related to this assessment upon request. Authors’ contributions AH, AK, and FP drafted the initial manuscript. FP, JH, and AK worked on the data analysis. AH, AK, PS, FP, RB, YK, IL, HM, AM, EK, PS, FM, WK, CM, JT, OS, HA and NK provided inputs on the discussion and overall write-up. All authors read and critically reviewed the drafts of the manuscript for important intellectual content and approved the final version. Acknowledgements This baseline assessment was conducted as part of the preparation for an upcoming project in the Geita region of Tanzania. We extend our deepest gratitude and appreciation to the Ministry of Health and the President's Office of Regional Authorities and Local Governments for their unwavering support and contributions to this initiative. We also commend the leadership and dedication of the district and regional authorities and health facility leaders in the Geita region. This project is generously funded by the Bill and Melinda Gates Foundation through the Grand Challenges Global Call-to-Action, Digital Health Services. The contents of this publication are the sole responsibility of the authors and do not necessarily represent the views of the Bill and Melinda Gates Foundation. The funders played no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. References United Nations Children’s Fund, Delivering for Women: Improving maternal health services to save lives. New York: UNICEF; 2022 Ministry of Health (MoH) [Tanzania Mainland], Ministry of Health (MoH) [Zanzibar], National Bureau of Statistics (NBS), Office of the Chief Government Statistician (OCGS), and ICF. 2023 Tanzania Demographic and Health Survey and Malaria Indicator Survey 2022 Key Indicators Report. Dodoma, Tanzania, and Rockville, Maryland, USA: MoH, NBS, OCGS, and ICF. Bwana VM, Rumisha SF, Mremi IR, Lyimo EP, Mboera LEG (2019) Patterns and causes of hospital maternal mortality in Tanzania: A 10-year retrospective analysis. 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González R, Manun'Ebo MF, Meremikwu M, Rabeza VR, Sacoor C, Figueroa-Romero A, Arikpo I, Macete E, Mbombo Ndombe D, Ramananjato R, LIach M, Pons-Duran C, Sanz S, Ramírez M, Cirera L, Maly C, Roman E, Pagnoni F, Menéndez C. The impact of community delivery of intermittent preventive treatment of malaria in pregnancy on its coverage in four sub-Saharan African countries (Democratic Republic of Congo, Madagascar, Mozambique, and Nigeria): a quasi-experimental multicentre evaluation. Lancet Glob Health. 2023 Apr;11(4): e566-e574. doi: 10.1016/S2214-109X(23)00051-7. PMID: 36925177. Amoakoh-Coleman, M., Arhinful, D.K., Klipstein-Grobusch, K. et al. Coverage of intermittent preventive treatment of malaria in pregnancy (IPTp) influences delivery outcomes among women with obstetric referrals at the district level in Ghana. Malar J 19 , 222 (2020). https://doi.org/10.1186/s12936-020-03288-4 Tesha GE, Makwaruzi S, Haws R, Mostel J, Lusasi A, Lazaro S, Mwaikambo S, Chacky F, Reaves E, Kitojo C, Serbantez N, Tetteh G, Wolf K, Oseni L. Understanding Antenatal Care Service Quality for Malaria in Pregnancy through Supportive Supervision Data in Tanzania. Am J Trop Med Hyg. 2024 Feb 6;110(3_Suppl):56-65. doi: 10.4269/ajtmh.23-0399. PMID: 38320309; PMCID: PMC10919228. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4829306","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":336159680,"identity":"4c453d0f-0085-45cb-9b86-ed282600d7d6","order_by":0,"name":"Augustino Hellar","email":"data:image/png;base64,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","orcid":"","institution":"Prime Health Initiative Tanzania","correspondingAuthor":true,"prefix":"","firstName":"Augustino","middleName":"","lastName":"Hellar","suffix":""},{"id":336159681,"identity":"8653da9d-0dc4-4fb8-820f-25dcdce2d1eb","order_by":1,"name":"Alen Kinyina","email":"","orcid":"","institution":"Prime Health Initiative 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Region","correspondingAuthor":false,"prefix":"","firstName":"Omari","middleName":"","lastName":"Sukari","suffix":""},{"id":336159697,"identity":"a0209fe7-52af-4b43-9c3d-5cd7795c4ab4","order_by":17,"name":"Husna Athumani","email":"","orcid":"","institution":"Prime Health Initiative Tanzania","correspondingAuthor":false,"prefix":"","firstName":"Husna","middleName":"","lastName":"Athumani","suffix":""},{"id":336159698,"identity":"238dcf85-066b-4285-9c09-7a5113964a4d","order_by":18,"name":"Ntuli Kapologwe","email":"","orcid":"","institution":"Prime Health Initiative Tanzania","correspondingAuthor":false,"prefix":"","firstName":"Ntuli","middleName":"","lastName":"Kapologwe","suffix":""}],"badges":[],"createdAt":"2024-07-30 13:53:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4829306/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4829306/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":64190682,"identity":"04463fc7-0ba1-420d-ba86-c507c08e77df","added_by":"auto","created_at":"2024-09-09 18:30:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":52109,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of women who attended ANC services at the 6 Health Facilities. Those with missing records were excluded in the final analysis.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4829306/v1/fa4a32076484f7764d87659e.png"},{"id":64190678,"identity":"5af7951c-d4d9-4a40-996d-4c6509a0ce9a","added_by":"auto","created_at":"2024-09-09 18:30:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":34599,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNumber of ANC visits among women who attended ANC in the 6 Project Facilities from January to December 2022 (n=599)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eOnly 34% of the women were recorded to have attended 4 or more ANC visits\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4829306/v1/802357ee30fc670a039462bf.png"},{"id":64190679,"identity":"de31948b-0e30-4dea-83df-16d6de5d7f43","added_by":"auto","created_at":"2024-09-09 18:30:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":29020,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAge Distribution of Women Attending ANC services in the 6 Project Facilities from January to December 2022 (n=657)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eMajority of women (65.4%) were in the age group 18-28 years.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4829306/v1/ada9d548532227657d4b1396.png"},{"id":64190677,"identity":"f235c11f-5e61-47b9-90ba-894920d98f89","added_by":"auto","created_at":"2024-09-09 18:30:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":26313,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGestation Age at Initiation of ANC at the 6 Project Facilities from January to December 2022 (n=657)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eMajority of women (54%) initiated ANC visits during the second trimester of their pregnancy, with only 19% being seen during the first trimester.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4829306/v1/d279b19bffe184291c57ba0c.png"},{"id":64190681,"identity":"dce58e84-0540-49d3-a485-ce8faa62add2","added_by":"auto","created_at":"2024-09-09 18:30:04","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":25545,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIron and Folic acid Supplementation among women attending ANC in the 6 Project Facilities from January to December 2022 (n=657)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eMost women received the first and second dose of Iron and Folic Acid supplementation, with a sharp decline in this proportion for the third and fourth doses.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4829306/v1/2164b5ee64b9ae85b29c60b6.png"},{"id":64190680,"identity":"aee795b8-e9b3-45fd-878b-2fd202ca43a3","added_by":"auto","created_at":"2024-09-09 18:30:04","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":28906,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUse of Intermittent Preventive Therapy for Malaria Prevention (IPT) from January to December 2022\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eLess than half of the women (43.3%) received at least 3 doses of Intermittent Preventive Therapy for Malaria\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4829306/v1/f0ac157262d1ad01b3de8bc4.png"},{"id":64190676,"identity":"55570ea4-e4c4-421c-ba3f-ae138cfd2266","added_by":"auto","created_at":"2024-09-09 18:30:03","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":35677,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNumber of Maternal Complications reported in the project facilities during assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eAll facilities reported a significant number of post-partum hemorrhage cases. Chato DH has a particularly high number of stillbirths reported.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4829306/v1/003aff6a6dbeaa4bf3f8aee9.png"},{"id":79736323,"identity":"59e2caad-7bde-4de8-9c33-15f5f7631a59","added_by":"auto","created_at":"2025-04-02 07:09:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1296313,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4829306/v1/57f15dac-5c3b-4da3-b23a-19c55127b6d3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"An assessment to inform programming for antenatal care services in six health facilities in Geita Region, Tanzania: a cross-sectional baseline survey","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAccording to UNICEF, the number of maternal deaths declined by 35% between 2000 and 2017, However, over 800 women are still dying every day, majority of them in sub-Saharan Africa from preventable pregnancy or childbirth complications [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Despite continuous efforts to improve maternal health, Tanzania is still facing challenges in reducing maternal complications and fatalities to the desired levels. The current maternal mortality rate remains significantly high at 104 per 100,000 live births, which is still higher than the desired Sustainable Development Goal (SDG) target of 70 per 100,000 live births [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Maternal mortality in Tanzania has been reported to stem from a variety of causes, such as eclampsia, hemorrhage and sepsis [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Child mortality is similarly high, at 24 deaths per 1,000 livebirths (TDHS 2022) double the SDG Target of \u0026lt;\u0026thinsp;12 deaths per 1,000 livebirths [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eAntenatal care presents a unique opportunity for early detection and management of pregnancy-related complications, leading to improved pregnancy outcomes. WHO recommends a minimum of 8 contacts at the health facility during the antennal period [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Recent findings from the Tanzania Health and Demographic Survey (TDHS) show that about 65% of pregnant women had four or more ANC visits/contacts as recommended [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, the high maternal mortality rate suggests that this improvement has not directly translated into reducing mortality. Worsening this situation is the fact that majority of the women, especially in rural settings in Tanzania, start ANC quite late [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This emphasizes the urgent need to promote ANC attendance and enhance the quality of care provided during pregnancy and childbirth, both at healthcare facilities and within communities and households.\u003c/p\u003e \u003cp\u003eOne significant contributing factor to the late identification of maternal complications during antenatal care is the inadequate health information systems in these settings [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Lack of proper maternal health information and poor data quality at the primary health care level hinders health care providers from identifying complications early [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Consequently, pregnant women face substantial risks of morbidity and mortality.\u003c/p\u003e \u003cp\u003eIn such a challenging environment, digital health solutions have been identified to have the potential of contributing to early identification of complications in pregnancy. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. A recent meta-analysis done in Africa and other LMICs showed a steady growth of digital innovations for maternal health in these countries, providing a unique opportunity to employ digital health systems for maternal and newborn mortality reduction [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, there are also other limitations in the quality of the interventions provided in these settings due to weak health systems and other factors. One study in Rufiji, Tanzania [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] reported that although ANC participants received basic clinical evaluations such as blood pressure measurements and abdominal examinations, more targeted and thorough investigations such as testing for albumin, hemoglobin or blood glucose, were rarely done. Implementing digital solutions, complemented by innovative care models, provides a unique opportunity to improve maternal and fetal outcomes by helping health providers link danger signs and clinical conditions, thus preventing adverse outcomes during pregnancy. This is where digital solutions such as artificial intelligence (AI) can play a vital role.\u003c/p\u003e \u003cp\u003eIt has also been shown that early ANC attendance promotes utilization of preventive measures by pregnant mothers during the antenatal period [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Women who start ANC services early and frequently are more likely to use key interventions such as intermittent preventive treatment for malaria and iron supplementation to prevent anemia [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Improvement in maternal outcomes will be facilitated by innovative approaches that promote integrated, and high-impact interventions to address the high maternal mortality rate in Tanzania.\u003c/p\u003e \u003cp\u003ePrime Health Initiative Tanzania is a local non-governmental organization (NGO) that has received funding by the Bill and Melinda Gates Foundation to implement a 2-years project aiming at piloting an antenatal risk stratification system using Artificial Intelligence (AI) technology. The primary objective is to promptly identify maternal risks among pregnant mothers in the Geita region of Tanzania. This will enable early interventions and management to prevent potential adverse maternal and fetal outcomes. If successful, this project has the potential to be scaled up in other health facilities in the region or elsewhere in Tanzania. The project will be implemented at six health facilities in two semi-urban/rural districts in Geita region.\u003c/p\u003e \u003cp\u003ePrior to the implementation of the proposed project, a comprehensive baseline assessment was conducted on to establish the status of ANC services in the targeted facilities. This paper presents the key findings derived from the assessment, with a specific focus on facility capacity, ANC attendance rates and patterns, maternal complications and other key practices related to antenatal care in the region. The baseline assessment provides vital information on the strengths, weaknesses, and gaps in the current ANC services. This critical exercise serves as a foundation for planning, refining, and tailoring the project interventions' design. It also sets grounds for future comparison to understand the impact of the project after its implementation.\u003c/p\u003e \u003cp\u003eThe paper summarizes key baseline parameters for antenatal care in Geita region, including facility capacity, availability of electronic health management information systems (HMIS), ANC attendance and timing and the overall state of antenatal care in these facilities.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThis was a cross-sectional study involving an analysis of records from women attending ANC visits in six selected health facilities during the assessment period (January to December 2022. We used data from HMIS registers \u0026ndash; ANC and Labor and Delivery \u0026ndash; to obtain information about pregnant mothers who attended ANC in the six facilities during the assessment period. Cutt-off points on ANC and labor parameters (birth weight, hemoglobin concentration and age group categories) were based on the World Health Organization standards and other peer reviewed studies. Data from the District Health Information System 2 (DHIS2) from the same period was used to make comparisons on the proportions of maternal complications, anaemia and maternal \u0026amp; neonatal deaths.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy Location\u003c/h2\u003e \u003cp\u003eThe study facilities are located in 2 Districts and include Chato District Hospital, Bwanga Health Center, and Butengorumasa Dispensary (In Chato District Council) and, Nzera District Hospital, Katoro Health Center, and Nkome Dispensary (in Geita District Council) both within Geita region in Tanzania. The dispensary is the lowest level of health care delivery in the country with basic normal delivery services, while health centers and district hospitals are the subsequent level of care, with more infrastructure and human resources for labor and delivery, including Comprehensive Emergency Obstetric and Neonatal Care (CEmONC).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSample Size\u003c/h2\u003e \u003cp\u003eWe employed convenience sampling to examine all available records from the registers at each health facility during the review period. This encompassed antenatal care (ANC) registers and labor and delivery registers. To gather data on maternal complications, we extracted information from the District Health Information System 2 (DHIS2) for these facilities, reported during the same period.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData Collection Methods\u003c/h2\u003e \u003cp\u003eWe trained data enumerators on data collection methods and tools. The data collectors visited each facility in person to gather information from the following sources: 1) NOH ANC Registers at the Antenatal Clinics and 2) MOH Labor and Delivery Registers at labor wards. Data from 657 women was extracted during this period from the ANC and labor registers. Additionally, data from the DHIS2 was retrieved online for the same period (January to December 2022) to analyze maternal and newborn complications reported in each study facility. Data was extracted manually from the registers into pre-designed data collection forms for analysis later. Regular supervision visits by the study lead and the project staff ensured adherence to data collection protocols.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eThe final data set was transformed to excel 2019 and then to Stata (version 15.0) statistical software for analysis. Data was analyzed descriptively using frequency (percentages) and median (interquartile range [IQR]). Chi-square (χ2) used to test for significance of the associations between outcome indicators and the independent variables. All statistical inferences were set to significance level of 5% (α\u0026thinsp;=\u0026thinsp;0.05). Data was presented in tables, cross-tabulations (demonstrating relationships between independent and dependent variables), pie charts and histograms. A further description of the analysis is given in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEthical Considerations:\u003c/h2\u003e \u003cp\u003eThe study team submitted the baseline study proposal and all data collection tools to the National Health Research Ethics Committee (NatHREC) as assurance that the study team was committed to protect the study participants and the data that would be generated as part of the baseline implementation. This study was approved with Ethical Clearance Certificate reference number NIMR/HQ/R.8a/Vol.IX/4194.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eRecords from 657 women with ANC and labor and delivery records were reviewed. The results are shown in the tables and figures below:\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFacility Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLevel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e# of Beds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMonthly ANC Attendance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo of Doctors (MD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUse of Electronic HMIS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNzera\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistrict Hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChato\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistrict Hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBwanga\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealth Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKatoro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealth Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNkome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDispensary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eButengorumasa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDispensary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eHealth Centers had the largest volume of women attending ANC services. None of the facilities was using an electronic health medical information system (HMIS)\u003c/p\u003e \u003cp\u003eANC Attendance\u003c/p\u003e \u003cp\u003eWe analyzed data from the 657 women who attended ANC services and described various parameters such as age distribution, number of visits throughout pregnancy and gestation age during ANC initiation. 599 of them had complete records on the number of ANC visits they had made throughout their pregnancy period (See Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOnly 34% of the women who had ANC contacts records were found to have attended 4 or more ANC visits (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Because the current Data registers at the facilities are still using the previous cut-off points for ANC visits, it was only possible to analyze those attending less than four contacts and those who has four contacts or more. Majority of women who attended ANC in these facilities were in the age group 18\u0026ndash;28 years i.e. 65.4% (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOut of the 657 women who were reported in the study facilities, majority (54%) had initiated ANC between 13\u0026ndash;24 weeks of gestation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Very few (19%) had initiated ANC at 12 weeks or below.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMajority of women (54%) initiated ANC visits during the second trimester of their pregnancy, with only 19% being seen during the first trimester.\u003c/p\u003e \u003cp\u003eANC Interventions\u003c/p\u003e \u003cp\u003eKey ANC interventions provided to mothers during ANC were assessed. These included hemoglobin checks for presence of anemia, iron and folic acid supplementation and intermittent preventive therapy (IPT) for malaria.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of anemia reported among mothers attending ANC (n\u0026thinsp;=\u0026thinsp;440)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (\u0026gt;\u0026thinsp;11g/dl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild (10.0 -10.9 g/dl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerate (7.0\u0026ndash;9.9 g/dl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSevere (\u0026lt;\u0026thinsp;7g/dl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e228 (51.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e440 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAlmost half (48.2%) of the women (with hemoglobin results recorded) were recorded to have anemia. 1% of them had severe anemia (Hb level below 7g/dl)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate Logistic Regression Analysis of Factors Associated with Hb levels\u0026thinsp;\u0026gt;\u0026thinsp;11g/dl\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds Ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% Conf. Interval\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eANC Visits 4+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.749114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.977355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMebendazole use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.675982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.100463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIron Supplementation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.998055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.24644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIPT use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.158734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.564585\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the multivariate analysis, using logistic regression with hemoglobin level being a dependent variable, women with 4 or more ANC (4+) visits were 2.7 more likely to have normal Hb level above 11g/dl than those with less than 4 visits (p\u0026thinsp;=\u0026thinsp;0.011).\u003c/p\u003e \u003cp\u003eWe also analyzed Iron and Folic acid supplementation as reported in the HMIS registers. Out of the 657 women attending ANC, majority received the first and second dose of Iron and Folic Acid supplementation at 87% and 67% respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The trend shows a with a sharp decline in this proportion for the third and fourth doses.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eRegarding the use of Intermittent Preventive Therapy for Malaria Prevention (IPT), less than half of the women (43.3%) received at least 3 doses of Intermittent Preventive Therapy for Malaria. Coverage of those getting only one does was 14% and those getting only 2 doses was 16% (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMaternal and Fetal Complications during ANC, Labor, and Delivery\u003c/p\u003e \u003cp\u003eAll maternal and fetal complications reported in the DHIS2 during the analysis were analyzed and categorized by type and facility as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. All facilities reported a significant number of post-partum hemorrhage cases. Chato DH has a particularly high number of stillbirths reported. One of the facilities (Chato District Hospital), had a very high number of reported stillbirths in DHIS2 during the reporting period.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe current study aimed to assess facility capacity, ANC coverage, occurrence of maternal complications and key ANC interventions in six healthcare facilities within Geita region. We describe key capacity parameters such as facility level, bed capacity, monthly ANC attendance, and availability of HMIS systems. We note that none of the facilities used electronic medical records before this assessment, implying that our project will need to strengthen this component before starting implementation.\u003c/p\u003e \u003cp\u003eAdditional insights that will serve as a foundational understanding of the status of antenatal care in these facilities are further discussed below.\u003c/p\u003e \u003cp\u003eANC Attendance: Timing and Frequency:\u003c/p\u003e \u003cp\u003eThe proportion of women receiving 4 or more ANC visits in this study was 34%. This is much lower than the proportion reported in the 2022 TDHS (65%) and from other literature in Tanzania [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This assessment was conducted in a rural/semi-urban setting. Prior assessments have shown that the number of ANC visits tend to be lower in rural vs urban settings, as reported in the 2022 TDHS [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This finding is significant to our project, since it means that most women in the project area do not receive the WHO-recommended ANC contacts during pregnancy. Our intervention will therefore focus on exploring potential barriers to ANC attendance, such as accessibility, awareness, and cultural beliefs, and develop strategies to encourage and support regular ANC visits.\u003c/p\u003e \u003cp\u003eThe study also examined demographics and ANC utilization factors among women attending ANC services. Most women were in the age group of 18\u0026ndash;28 years, suggesting that the project will need to tailor ANC services to address the specific health needs and preferences of this age group.\u003c/p\u003e \u003cp\u003eGestation Age at Initiation of ANC:\u003c/p\u003e \u003cp\u003eThe study found that most women, initiated ANC visits during the second trimester i.e., at 13\u0026ndash;24 weeks of pregnancy. These findings are comparable to other studies that reported late initiation of ANC in Tanzania [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. WHO recommends at least one contact with the pregnant woman during the first trimester, highlighting the need for early ANC initiation.\u003c/p\u003e \u003cp\u003eFrom these findings, we recognize the need to analyze various barriers to early initiation of ANC in this community and thus tailor interventions to address them. Some of the barriers for late ANC initiation highlighted in other studies in Tanzania, include traditional and cultural beliefs, unpleasant experience in past pregnancies, shortage of health care workers and perceptions about inadequate quality of care [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. One study conducted in a similar setting in Rwanda recommended replacing traditional approaches with innovative models to enhance ANC seeking behavior [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and promote early initiation.\u003c/p\u003e \u003cp\u003eANC Interventions\u003c/p\u003e \u003cp\u003eThe prevalence of anaemia in pregnancy in this study was found to be 48.2%. This is comparable to studies done elsewhere in Tanzania and elsewhere in Africa [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. A study in a rural setting in Tanzania reported a much higher prevalence of anaemia in pregnancy, signifying the need for anaemia prevention measures in our setting [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. There is a need to find innovative approaches to enhance Iron and folic acid supplementation uptake, as recommended by WHO.\u003c/p\u003e \u003cp\u003eThe multivariate analysis using logistic regression demonstrated that attending four or more ANC visits (OR\u0026thinsp;=\u0026thinsp;2.74, p\u0026thinsp;=\u0026thinsp;0.011) significantly increases the likelihood of having higher Hb levels (above 11). Other variables, including mebendazole use (OR -1.67, p\u0026thinsp;=\u0026thinsp;0.256), iron supplementation (OR\u0026thinsp;=\u0026thinsp;0.99, p-value\u0026thinsp;=\u0026thinsp;0.99), and IPT use (OR\u0026thinsp;=\u0026thinsp;1.15, p\u0026thinsp;=\u0026thinsp;0797), did not show a statistically significant association with Hb levels in this analysis. These findings are comparable to a study in Ghana that showed a similar association [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eDuring this baseline assessment, we observed a decline in the proportion of women receiving the third and fourth doses of Iron and Folic Acid supplementation. This signifies that there are potential barriers to consistent care. We plan to explore additional community level interventions, that can be implemented in the project facilities and promoted through peer-support and community health workers who will be part of our planned GANC model.\u003c/p\u003e \u003cp\u003eThe coverage of 3 doses Intermittent Preventive Therapy for Malaria (IPTp3+) was reported 43.3%. This was comparable to other studies done elsewhere in Africa [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. It will be critical to analyze and address factors that may influence acceptability and uptake of IPTp3\u0026thinsp;+\u0026thinsp;as outlined elsewhere in Tanzania [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMaternal Complications:\u003c/p\u003e \u003cp\u003eMaternal complications are a significant concern and were evident across all facilities during the assessment period. The assessment of maternal complications revealed important patterns across the project facilities. Postpartum hemorrhage (PPH) was the most frequently reported complication, affecting women across all facilities. This picture is similar to the findings from a 10-year mortality by Bwana et al in 24 public hospitals in the country [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The finding highlights the need for targeted interventions to improve the management of PPH and its prevention through appropriate antenatal and postnatal care. Chato District Hospital reported a notably high number of stillbirths, signaling the necessity of focused efforts to address this issue.\u003c/p\u003e \u003cp\u003eLimitations:\u003c/p\u003e \u003cp\u003eSeveral limitations are acknowledged in this study. Firstly, the data collected were based on the assessment period (January \u0026ndash; December 2022), which may not fully represent the long-term performance of the facilities. Secondly, the study focused on a rural and semi-urban geographic area, that may limit the generalizability of the findings to urban settings. Lastly, the reliance on reported maternal complications may be subject to underreporting or poor documentation in these health facilities.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur findings shed light on the strengths and areas for improvement in the provision of ANC services in the project facilities. Efforts should be made to address common maternal complications such as PPH, and strategies to improve ANC attendance and early initiation of ANC should be prioritized. Targeted interventions, capacity-building, and quality improvement initiatives can collectively contribute to enhancing maternal and child health outcomes in the project area.\u003c/p\u003e \u003cp\u003eThe proposed AI-powered antenatal risk stratification system holds promise in addressing these challenges. By leveraging advanced algorithms to analyze health data, this system can identify high-risk pregnancies promptly, enabling healthcare providers to intervene early and provide targeted care. Integration with the Group Antenatal Care (GANC) model presents a unique opportunity to facilitate peer support and education among pregnant women, potentially enhancing their engagement in care and health-seeking behaviors.\u003c/p\u003e \u003cp\u003eThis study sets the stage for a transformative initiative that could reshape maternal healthcare in Geita region. By understanding the current state of antenatal care, the project can tailor interventions to address specific gaps and needs. The integration of digital health technology and innovative care models aligns with global efforts to leverage technology for improved healthcare outcomes. This initiative's success could serve as a model for other regions facing similar challenges, reducing maternal morbidity and mortality. As the project progresses, ongoing monitoring and evaluation will be critical to assess the impact and effectiveness of the AI-powered risk stratification system in improving maternal health outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eANC: Antenatal care\u003c/p\u003e\n\u003cp\u003eDHIS2: District Health Management System (Version 2)\u003c/p\u003e\n\u003cp\u003eGANC: Group Antenatal Care\u003c/p\u003e\n\u003cp\u003eHb: Haemoglobin\u003c/p\u003e\n\u003cp\u003eHMIS: Health Medical Information System\u003c/p\u003e\n\u003cp\u003eIPTp3+: Intermittent Presumptive Therapy for Malaria (3 doses)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLMICs:\u0026nbsp;Low- and Middle-Income Countries\u003c/p\u003e\n\u003cp\u003eMOH:\u0026nbsp; \u0026nbsp;\u0026nbsp;Ministry of Health\u003c/p\u003e\n\u003cp\u003ePPH: Postpartum\u0026nbsp;Hemorrhage\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSDGs: Sustainable Development Goals\u003c/p\u003e\n\u003cp\u003eTDHS: Tanzania Demographic Health Survey\u003c/p\u003e\n\u003cp\u003eWHO: World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs part of the larger Antenatal Risk Stratification Pilot Project in the Geita region, we obtained ethical clearance from the National Health Research Ethics Committee (NatREC), with the Ethical Clearance Certificate reference number NIMR/HQ/R.8a/Vol.IX/4194. Since this study was not a clinical trial, it did not require a clinical trial registration number.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study was conducted according to CIOMS Guidelines on use of retrospective data and NatREC guidelines, the local ethical review board in Tanzania.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent to Participate\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was a cross-sectional survey that utilized anonymous data from MOH HMIS registers and DHIS2 systems., hence obtaining individual consent from participants was not feasible since the data is anonymized. However, we obtained ethical clearance to conduct this study from the local ethical review board, NatREC, with reference certificate number NIMR/HQ/R.8a/Vol.IX/4194.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026ldquo;Not applicable\u0026rdquo;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during this baseline assessment are not publicly available due privacy and data protection reasons as guided by the Ministry of Health in Tanzania and the National Institute for Medical Research (NIMR) but are available from the corresponding author on request. Any requests for data access should be directed to the corresponding author (Dr. Augustino M. Hellar, email:\u0026nbsp;\u003ca href=\"mailto:[email protected]\"\[email protected]\u003c/a\u003e)\u003c/p\u003e\n\u003cp\u003eAnyone who wishes to use the data must ensure confidentiality and appropriate use of this study data. The authors will determine and decide to share any additional materials related to this assessment upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe declare no financial or non-financial competing interests must be declared in this section.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe baseline survey that collected data used for this study was funded as part of the Mlinde Mama project, implemented by the Prime Health Initiative Tanzania in partnership with the Tanzania Ministry of Health and President\u0026apos;s Office, Regional Administration and Local Government with funding from the Bill and Melinda Gates Foundation.\u003c/p\u003e\n\u003cp\u003eAnyone who wishes to use the data must ensure confidentiality and appropriate use of this study data. The authors will determine and decide to share any additional materials related to this assessment upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors\u0026rsquo; contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAH, AK, and FP drafted the initial manuscript. FP, JH, and AK worked on the data analysis. AH, AK, PS, FP, RB, YK, IL, HM, AM, EK, PS, FM, WK, CM, JT, OS, HA and NK provided inputs on the discussion and overall write-up. All authors read and critically reviewed the drafts of the manuscript for important intellectual content and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis baseline assessment was conducted as part of the preparation for an upcoming project in the Geita region of Tanzania. We extend our deepest gratitude and appreciation to the Ministry of Health and the President\u0026apos;s Office of Regional Authorities and Local Governments for their unwavering support and contributions to this initiative. We also commend the leadership and dedication of the district and regional authorities and health facility leaders in the Geita region.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis project is generously funded by the Bill and Melinda Gates Foundation through the Grand Challenges Global Call-to-Action, Digital Health Services. The contents of this publication are the sole responsibility of the authors and do not necessarily represent the views of the Bill and Melinda Gates Foundation. The funders played no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eUnited Nations Children\u0026rsquo;s Fund, Delivering for Women: Improving maternal health services to save lives. New York: UNICEF; 2022\u003c/li\u003e\n \u003cli\u003eMinistry of Health (MoH) [Tanzania Mainland], Ministry of Health (MoH) [Zanzibar], National Bureau of Statistics (NBS), Office of the Chief Government Statistician (OCGS), and ICF. 2023 Tanzania Demographic and Health Survey and Malaria Indicator Survey 2022 Key Indicators Report. Dodoma, Tanzania, and Rockville, Maryland, USA: MoH, NBS, OCGS, and ICF.\u003c/li\u003e\n \u003cli\u003eBwana VM, Rumisha SF, Mremi IR, Lyimo EP, Mboera LEG (2019) Patterns and causes of hospital maternal mortality in Tanzania: A 10-year retrospective analysis. PLoS ONE 14(4): e0214807. https://doi.org/10.1371/journal.pone.0214807WHO ANC recommendations\u003c/li\u003e\n \u003cli\u003eWHO Recommendations on Antenatal Care for a Positive Pregnancy Experience: Summary Highlights and Key Messages from the World Health Organization\u0026rsquo;s 2016 Global Recommendations for Routine Antenatal Care; cited on 8th July 2024; Available from:\u0026nbsp;\u003ca href=\"https://iris.who.int/bitstream/handle/10665/259947/WHO-RHR-18.02-eng.pdf\"\u003ehttps://iris.who.int/bitstream/handle/10665/259947/WHO-RHR-18.02-eng.pdf\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eKisaka, L., Leshabari, S. (2020). Factors Associated with First Antenatal Care Booking among Pregnant Women at a Reproductive Health Clinic in Tanzania: A Cross-Sectional Study. EC Gynaecology, 9(3), 1-12\u003c/li\u003e\n \u003cli\u003eMwangakala, H.A., 2021, \u0026lsquo;Accessibility of maternal health information and its influence on maternal health preferences in rural Tanzania: A case study of Chamwino District\u0026rsquo;, South African Journal of Information Management 23(1), a1353. https://doi.org/10.4102/ sajim. v23i1.1353\u003c/li\u003e\n \u003cli\u003eRumisha, S.F., Lyimo, E.P., Mremi, I.R. \u003cem\u003eet al.\u003c/em\u003e Data quality of the routine health management information system at the primary healthcare facility and district levels in Tanzania. \u003cem\u003eBMC Med Inform Decis Mak\u003c/em\u003e\u003cstrong\u003e20\u003c/strong\u003e, 340 (2020). https://doi.org/10.1186/s12911-020-01366-w\u003c/li\u003e\n \u003cli\u003eVan Den Heuvel JF, Groenhof TK, Veerbeek JH, Van Solinge WW, Lely AT, Franx A, Bekker MN. eHealth as the next-generation perinatal care: an overview of the literature. Journal of medical Internet research. 2018 Jun 5;20(6): e202.\u003c/li\u003e\n \u003cli\u003eTill S, Mkhize M, Farao J, Shandu LD, Muthelo L, Coleman TL, Mbombi M, Bopape M, Klingberg S, van Heerden A, Mothiba T, Densmore M, Verdezoto Dias NX; CoMaCH Network. Digital Health Technologies for Maternal and Child Health in Africa and Other Low- and Middle-Income Countries: Cross-disciplinary Scoping Review with Stakeholder Consultation. J Med Internet Res. 2023 Apr 7;25: e42161. doi: 10.2196/42161. PMID: 37027199; PMCID: PMC10131761.\u003c/li\u003e\n \u003cli\u003eSarker M, Schmid G, Larsson E, Kirenga S, De Allegri M, Neuhann F, Mbunda T, Lekule I, M\u0026uuml;ller O. Quality of antenatal care in rural southern Tanzania: a reality check. BMC Res Notes. 2010 Jul 27; 3:209. doi: 10.1186/1756-0500-3-209. PMID: 20663202; PMCID: PMC3161364.\u003c/li\u003e\n \u003cli\u003eMushi V, Mbotwa CH, Zacharia A, Ambrose T, Moshi FV. Predictors for the uptake of optimal doses of sulfadoxine-pyrimethamine for intermittent preventive treatment of malaria during pregnancy in Tanzania: further analysis of the data of the 2015\u0026ndash;2016 Tanzania demographic and health survey and malaria indicator survey. Malaria Journal. 2021 Dec; 20:1\u003c/li\u003e\n \u003cli\u003eKonje, E.T., Magoma, M.T.N., Hatfield, J. et al.\u0026nbsp;Missed opportunities in antenatal care for improving the health of pregnant women and newborns in Geita district, Northwest Tanzania. BMC Pregnancy Childbirth 18, 394 (2018). https://doi.org/10.1186/s12884-018-2014-8\u003c/li\u003e\n \u003cli\u003eMgata S, Maluka SO. Factors for late initiation of antenatal care in Dar es Salaam, Tanzania: A qualitative study. BMC Pregnancy Childbirth. 2019 Nov 12;19(1):415. doi: 10.1186/s12884-019-2576-0. PMID: 31718586; PMCID: PMC6849280.\u003c/li\u003e\n \u003cli\u003eMaluka S, Joseph C, Fitzgerald S et al; Why do pregnant women in Iringa regionin Tanzania start antenatal care late? A qualitative analysis; Maluka et al. BMC Pregnancy and Childbirth (2020) 20:126; https://doi.org/10.1186/s12884-020-2823-4\u003c/li\u003e\n \u003cli\u003eDusingizimana T, Ramilan T, Weber JL et al; Predictors for achieving adequate antenatal care visits during pregnancy: a cross‑sectional study in rural Northwest Rwanda; BMC Pregnancy and Childbirth (2023) 23:69; https://doi.org/10.1186/s12884-023-05384-0\u003c/li\u003e\n \u003cli\u003eSunguya B, Ge Y, Mlunde L, Mpembeni R et al; High burden of anemia among pregnant women in Tanzania: a call to address its determinants; Nutr J (2021) 20:65; https://doi.org/10.1186/s12937-021-00726-0\u003c/li\u003e\n \u003cli\u003eTibambuya BA, Ganle JK, Ibrahim M. Anaemia at antenatal care initiation and associated factors among pregnant women in West Gonja District, Ghana: a cross-sectional study. Pan Afr Med J. 2019 Aug 27; 33:325. doi: 10.11604/pamj.2019.33.325.17924. PMID: 31692871; PMCID: PMC6815505.Overview of iron deficiency and iron deficiency anaemia in women of reproductive age; Derman R, Patted A;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDerman RJ, Patted A. Overview of iron deficiency and iron deficiency anemia in women and girls of reproductive age. Int J Gynecol Obstet.2023;162(Suppl. 2):78-82. doi:10.1002/ijgo.14950\u003c/li\u003e\n \u003cli\u003eNgimbudzi EB, Massawe SN, Sunguya BF. The Burden of Anemia in Pregnancy Among Women Attending the Antenatal Clinics in Mkuranga District, Tanzania. Front Public Health. 2021 Dec 2; 9:724562. doi: 10.3389/fpubh.2021.724562. PMID: 34926366; PMCID: PMC8674738.\u003c/li\u003e\n \u003cli\u003eSaapiire\u0026nbsp;F, Dogoli R, Mahama S. Adequacy of antenatal care services utilization and its effect on anaemia in pregnancy. J Nutr Sci. 2022 Sep 21;11: e80. doi: 10.1017/jns.2022.80. PMID: 36304821; PMCID: PMC9554427.\u003c/li\u003e\n \u003cli\u003eGonz\u0026aacute;lez R, Manun\u0026apos;Ebo MF, Meremikwu M, Rabeza VR, Sacoor C, Figueroa-Romero A, Arikpo I, Macete E, Mbombo Ndombe D, Ramananjato R, LIach M, Pons-Duran C, Sanz S, Ram\u0026iacute;rez M, Cirera L, Maly C, Roman E, Pagnoni F, Men\u0026eacute;ndez C. The impact of community delivery of intermittent preventive treatment of malaria in pregnancy on its coverage in four sub-Saharan African countries (Democratic Republic of Congo, Madagascar, Mozambique, and Nigeria): a quasi-experimental multicentre evaluation. Lancet Glob Health. 2023 Apr;11(4): e566-e574. doi: 10.1016/S2214-109X(23)00051-7. PMID: 36925177.\u003c/li\u003e\n \u003cli\u003eAmoakoh-Coleman, M., Arhinful, D.K., Klipstein-Grobusch, K. \u003cem\u003eet al.\u003c/em\u003e Coverage of intermittent preventive treatment of malaria in pregnancy (IPTp) influences delivery outcomes among women with obstetric referrals at the district level in Ghana. \u003cem\u003eMalar J\u003c/em\u003e\u003cstrong\u003e19\u003c/strong\u003e, 222 (2020). https://doi.org/10.1186/s12936-020-03288-4\u003c/li\u003e\n \u003cli\u003eTesha GE, Makwaruzi S, Haws R, Mostel J, Lusasi A, Lazaro S, Mwaikambo S, Chacky F, Reaves E, Kitojo C, Serbantez N, Tetteh G, Wolf K, Oseni L. Understanding Antenatal Care Service Quality for Malaria in Pregnancy through Supportive Supervision Data in Tanzania. Am J Trop Med Hyg. 2024 Feb 6;110(3_Suppl):56-65. doi: 10.4269/ajtmh.23-0399. PMID: 38320309; PMCID: PMC10919228.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Antenatal Care, Antenatal Risk Stratification, Digital Health in Maternal Care, Baseline Assessment, Group Antenatal Care","lastPublishedDoi":"10.21203/rs.3.rs-4829306/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4829306/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eGlobally, every two minutes, a woman dies during pregnancy or childbirth, and each day, about 6,300 newborns die. Most of these deaths are preventable. Despite global efforts to improve coverage and access to maternity care, mortality rates remain stubbornly high. The World Health Organization (WHO) recommends a minimum of eight antenatal care (ANC) contacts with early initiation during the first trimester (before 12 weeks). This baseline assessment aimed to determine the current status of ANC services in selected facilities before launching a pilot study. The pilot will focus on digital solutions, including the use of machine learning models, to facilitate prompt decision-making and early detection of maternal complications, ultimately helping to prevent complications during pregnancy.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross-sectional study involved an analysis of records from women attending ANC contacts at six selected health facilities from January to December 2022. Data were obtained from Health Management Information System (HMIS) registers\u0026mdash;ANC and Labor and Delivery\u0026mdash;and extracted from the District Health Information System 2 (DHIS2) to analyze ANC practices and maternal complications respectively. Descriptive analysis was performed using frequency/percentages A multivariate logistic analysis was conducted to identify factors associated with presence or absence of anaemia (\u0026gt;\u0026thinsp;11g/dl).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eRecords from 657 women who received ANC and labour and delivery services across six health facilities were reviewed. 599 had a record of the number of contacts they had made. Only 34% of these women attended the WHO-recommended four or more ANC contacts (ANC4+), and just 19% initiated ANC during the first trimester. Additionally, 48.2% of the women with hemoglobin records (n\u0026thinsp;=\u0026thinsp;440) were diagnosed with anaemia. While most women received two doses of supplemental iron for anaemia prevention, there was a notable decline in the administration of the third and fourth doses. In the multivariate analysis, women with four or more ANC visits were 2.7 times more likely to have normal haemoglobin levels than those with fewer visits. Coverage for Intermittent Preventive Treatment for Malaria (IPT) was 43.3%. Data extracted from DHIS2 showed a high proportion of postpartum haemorrhage (PPH) cases (n\u0026thinsp;=\u0026thinsp;147).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThese baseline findings highlight significant gaps in antenatal care practices and maternal health outcomes in the assessed facilities, underscoring the need for innovative approaches. Our proposed intervention, integrating artificial intelligence, group antenatal care (GANC), and community interventions, aims to enhance early ANC initiation, improve adherence to recommended visits, and predict and recognize maternal complications early, thereby improving maternal and fetal outcomes.\u003c/p\u003e","manuscriptTitle":"An assessment to inform programming for antenatal care services in six health facilities in Geita Region, Tanzania: a cross-sectional baseline survey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-09 18:29:57","doi":"10.21203/rs.3.rs-4829306/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7f1f4c89-ae85-4250-b72b-d8fb6d1357d3","owner":[],"postedDate":"September 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-02T07:09:06+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-09 18:29:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4829306","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4829306","identity":"rs-4829306","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}