Course Introduction
Maternal and child health programmes generate extensive data across antenatal care, skilled birth attendance, postnatal care, family planning, newborn care, immunization, child growth monitoring, nutrition, referrals, community health services, and disease prevention. Effective analytics enables health managers and programme teams to understand service utilization, coverage, continuity of care, geographic disparities, operational bottlenecks, and changing population needs while strengthening evidence-based planning and programme performance.
This course provides a practical framework for collecting, validating, integrating, analysing, and presenting maternal and child health programme data. Participants will examine information from facility registers, electronic health records, community health systems, immunization platforms, maternity records, child health registers, laboratory systems, referral databases, programme monitoring tools, and population-based sources. Particular emphasis is placed on data quality, indicator definitions, reporting completeness, timeliness, consistency, denominator management, and reconciliation between routine programme data and other information sources.
The programme explores analytical methods for monitoring the maternal and child health continuum of care, including antenatal attendance, skilled delivery, postnatal follow-up, newborn care, immunization, nutrition, child illness management, family planning, and referral services. Participants will learn to analyse service utilization, dropout, retention, coverage, timing, referral completion, and facility performance. These techniques help programme managers identify service gaps and understand where improvements may be required across different stages of the care pathway.
Participants will develop practical skills in maternal and child health dashboards, scorecards, geographic analysis, trend monitoring, performance comparisons, and programme reporting. The course demonstrates how to analyse maternal and newborn service indicators alongside child health, immunization, nutrition, workforce, commodity availability, and community outreach information. By integrating these datasets, participants can develop a more comprehensive understanding of programme performance and identify relationships between service readiness, access, utilization, and continuity of care.
Emerging technologies are increasingly influencing maternal and child health analytics through digital health platforms, mobile community health applications, electronic medical records, GIS, artificial intelligence, predictive analytics, remote monitoring, automated reporting, and decision-support systems. The course introduces these developments while addressing patient privacy, cybersecurity, responsible AI, interoperability, data governance, digital inclusion, and the importance of human oversight when analytics are used to inform maternal and child health planning and programme decisions.
By the end of the programme, participants will be equipped to improve maternal and child health data quality, analyse programme coverage and service utilization, identify geographic and operational gaps, build effective performance dashboards, monitor continuity of care, and translate findings into practical management intelligence. The course emphasizes applied learning so participants can use real programme data to strengthen planning, resource allocation, service coordination, monitoring, and continuous improvement across maternal, newborn, and child health programmes.
Duration
5 days
Who Should Attend
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Maternal and child health programme managers and coordinators
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Maternal, newborn, and child health specialists
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Reproductive, maternal, newborn, child, and adolescent health officers
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Public health programme managers and planners
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Health facility managers and maternity unit managers
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Nursing and midwifery managers
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Community health programme coordinators
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Immunization and child health programme officers
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Nutrition programme and child development professionals
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Monitoring, evaluation, and learning professionals
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Health information and medical records officers
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Healthcare data analysts and business intelligence specialists
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Digital health and health information systems professionals
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County, district, regional, or national health management teams
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Senior health managers responsible for maternal and child health performance
Course Objectives
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Develop practical knowledge of maternal and child health programme analytics and understand how data can strengthen planning, service delivery, coverage, continuity of care, and programme performance.
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Apply appropriate techniques for collecting, validating, cleaning, standardizing, integrating, and reconciling maternal, newborn, child health, community, and programme data.
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Analyse antenatal care, skilled birth attendance, postnatal care, newborn care, immunization, nutrition, child health, family planning, and referral indicators across facilities and populations.
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Evaluate service coverage, utilization, retention, dropout, timeliness, referral completion, and continuity of care to identify gaps across the maternal and child health service pathway.
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Build practical dashboards, scorecards, maps, trend charts, and management reports that transform routine maternal and child health data into actionable programme intelligence.
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Apply geographic and comparative analytics to identify disparities in maternal and child health service coverage, facility performance, community access, and programme reach.
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Integrate maternal and child health service data with information on staffing, medicines, vaccines, diagnostics, infrastructure, community outreach, and other factors affecting programme performance.
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Explore artificial intelligence, predictive analytics, GIS, mobile health, digital reporting, electronic health records, and other emerging technologies relevant to maternal and child health programme management.
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Strengthen understanding of health data governance, patient privacy, cybersecurity, interoperability, responsible analytics, data protection, and ethical use of maternal and child health information.
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Develop an integrated maternal and child health analytics project that converts programme data into actionable intelligence for service improvement, resource allocation, performance monitoring, and evidence-based planning.
Comprehensive Course Outline
Module 1: Foundations of Maternal and Child Health Programme Analytics
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Understanding the strategic role of analytics in maternal, newborn, and child health planning, programme management, service improvement, accountability, and population health.
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Mapping the continuum of maternal and child health services from reproductive care and antenatal services through delivery, postnatal care, newborn care, immunization, nutrition, and child health.
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Defining key maternal and child health indicators covering service utilization, coverage, continuity, quality, timeliness, referrals, outcomes, and programme reach.
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Understanding analytical challenges such as incomplete reporting, inconsistent indicator definitions, denominator uncertainty, duplicate records, reporting delays, and variations in data quality.
Module 2: Maternal and Child Health Data Collection, Quality, Integration, and Management
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Designing reliable data collection processes for maternity, antenatal, postnatal, newborn, child health, immunization, nutrition, family planning, and community health services.
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Applying data-quality assessment methods to identify missing values, duplicate records, inconsistent classifications, implausible figures, incomplete reporting, and discrepancies between source documents and routine reports.
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Integrating facility registers, electronic health records, community health systems, immunization platforms, referral databases, laboratory systems, and programme monitoring tools.
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Developing indicator reference sheets, data dictionaries, validation rules, metadata, reporting calendars, quality assurance processes, and data reconciliation procedures.
Module 3: Spreadsheet, Database, GIS, and Business Intelligence Analytics
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Using spreadsheet techniques to clean, summarize, analyse, compare, and visualize maternal and child health programme datasets for routine monitoring and management.
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Understanding database structures, queries, relationships, calculated fields, event records, and analytical models for integrated maternal and child health information.
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Applying GIS and spatial analysis to visualize service coverage, facility performance, referral patterns, community outreach, population access, and geographic disparities.
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Designing dashboards and scorecards that combine maternal, newborn, child health, immunization, nutrition, and programme performance indicators for different management audiences.
Module 4: Antenatal, Delivery, Postnatal, and Maternal Health Analytics
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Analysing antenatal care attendance, timing, completion, skilled birth attendance, facility delivery, postnatal care, and other maternal health service indicators.
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Evaluating continuity across antenatal, delivery, and postnatal services to identify dropout patterns, delayed care, missed opportunities, and gaps in the maternal care pathway.
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Examining referrals, emergency transfers, service utilization, maternity workload, waiting times, and other operational factors affecting maternal healthcare access and continuity.
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Developing maternal health dashboards that support monitoring of coverage, service utilization, facility performance, geographic variation, and priority programme improvement areas.
Module 5: Newborn, Child Health, Immunization, and Nutrition Analytics
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Analysing essential newborn care, neonatal service utilization, newborn follow-up, child illness management, growth monitoring, and other child health indicators.
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Evaluating immunization coverage, vaccination schedules, dropout rates, missed opportunities, outreach performance, vaccine availability, and differences between geographic areas.
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Monitoring child nutrition indicators, screening, supplementation, treatment, referral, follow-up, and programme coverage to identify service and population gaps.
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Integrating newborn, child health, immunization, and nutrition information to understand continuity of services and identify opportunities for coordinated programme improvement.
Module 6: Family Planning, Community Health, Referral, and Service Delivery Analytics
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Analysing family planning utilization, method mix, continuation, counselling, commodity availability, and service access across maternal and reproductive health programmes.
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Evaluating community health activities such as household visits, pregnancy identification, referrals, health education, immunization mobilization, nutrition screening, and follow-up.
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Analysing referral volumes, referral completion, transfer times, counter-referrals, service destinations, and coordination between community, primary, and higher-level health facilities.
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Integrating community, facility, referral, and programme information to assess access, continuity, service responsiveness, and population reach.
Module 7: Geographic, Equity, Risk, and Programme Performance Analytics
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Applying GIS and spatial analysis to identify underserved communities, geographic concentrations of maternal and child health needs, facility access gaps, and service coverage differences.
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Analysing programme performance across geographic areas, facilities, population groups, service categories, and time periods to identify variations requiring further investigation.
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Examining relationships between service utilization and factors such as distance, facility readiness, staffing, commodity availability, community outreach, and referral capacity.
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Developing equity-focused dashboards and risk profiles to support targeted interventions, resource allocation, outreach planning, service expansion, and programme prioritization.
Module 8: AI, Predictive Analytics, Digital Health, and Emerging MCH Technologies
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Exploring artificial intelligence and machine learning applications for maternal and child health demand forecasting, risk identification, service planning, anomaly detection, and decision support.
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Applying predictive analytics concepts to service utilization, follow-up needs, immunization demand, maternal care continuity, staffing requirements, and other programme planning challenges.
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Examining electronic medical records, mobile maternal health platforms, community health applications, digital referral tools, remote monitoring, automated reporting, and integrated health information systems.
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Evaluating responsible adoption of emerging technologies, including patient privacy, cybersecurity, interoperability, digital inclusion, data quality, algorithmic transparency, and human oversight.
Module 9: Maternal and Child Health Data Governance, Privacy, Cybersecurity, and Responsible Analytics
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Establishing governance frameworks covering ownership, access controls, quality standards, retention, documentation, reporting responsibilities, and appropriate sharing of maternal and child health information.
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Protecting sensitive information concerning mothers, newborns, children, families, clinical services, referrals, diagnoses, and programme participation during data analysis and reporting.
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Identifying cybersecurity risks affecting maternal and child health information systems, electronic records, mobile applications, cloud platforms, connected devices, and digital reporting tools.
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Applying responsible analytics principles to ensure that programme findings are accurately interpreted, vulnerable populations are protected, and decisions are based on reliable and ethically managed evidence.
Module 10: Integrated Maternal and Child Health Programme Analytics Project
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Developing an end-to-end maternal and child health analytics project using antenatal, delivery, postnatal, newborn, immunization, nutrition, family planning, referral, or community health data.
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Cleaning, analysing, and interpreting the selected dataset while documenting indicator definitions, data limitations, quality issues, assumptions, and analytical methods.
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Creating an integrated dashboard or management report showing coverage, utilization, continuity, geographic variation, service gaps, trends, and priority areas for programme improvement.
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Presenting analytical findings to a simulated maternal and child health management team and demonstrating how evidence can support planning, resource allocation, service coordination, outreach, and continuous programme improvement.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
