Course Introduction
Community health programmes generate extensive data through household visits, community health worker activities, health promotion, disease prevention, referrals, maternal and child health services, immunization support, screening, treatment adherence, outreach, and community-based surveillance. Community Health Programme Data Analytics Training Course equips participants with practical capabilities to transform these datasets into actionable intelligence for programme planning, service monitoring, resource allocation, population engagement, and continuous improvement of community-based health services.
Effective community health analytics requires an understanding of how information is generated at household, community, outreach, facility, district, and programme levels. Participants will examine data from community health registers, mobile applications, household assessments, referral records, outreach reports, community surveillance systems, facility information systems, surveys, and population datasets. Particular attention is given to completeness, timeliness, accuracy, duplicate records, household identification, geographic information, reporting consistency, data aggregation, denominator quality, and integration between community and facility health information.
The course develops practical approaches for analysing community health service coverage, household engagement, community health worker productivity, referrals, health promotion activities, disease prevention, maternal and child health services, immunization support, and follow-up. Participants will learn how to calculate and interpret indicators relating to household coverage, community contacts, referral completion, outreach reach, service utilization, follow-up, community-level screening, and programme performance. They will explore how trends and disaggregated data can reveal underserved communities, service gaps, workload challenges, and changes in community health needs.
Modern community health programmes increasingly rely on digital data collection, mobile health applications, GIS, dashboards, automated reporting, and integrated community-facility information systems. The course therefore introduces spreadsheet analytics, databases, GIS, business intelligence, data visualization, mapping, cohort analysis, and performance dashboards relevant to community health management. Participants will learn how analytical outputs can support community microplanning, health worker deployment, outreach scheduling, referral strengthening, resource allocation, supervision, performance reviews, and integration of community services with primary healthcare.
Emerging technologies are expanding opportunities through artificial intelligence, predictive analytics, digital community health platforms, mobile decision-support systems, geospatial intelligence, remote monitoring, automated alerts, and connected devices. Participants will explore these technologies while considering data privacy, cybersecurity, digital inclusion, consent, interoperability, algorithmic bias, and responsible use of household and community information. The course also considers how population mobility, urbanization, climate-related events, emergencies, socioeconomic conditions, and changing disease patterns can affect community health needs and programme performance.
By the end of the course, participants will be equipped to transform community health programme data into practical planning and performance intelligence. They will be able to assess data quality, analyse service coverage and workload, evaluate community health worker performance, identify geographic and population-level gaps, develop dashboards, monitor referrals and outreach, and communicate evidence-based recommendations. The practical orientation enables participants to apply analytics to real-world community health challenges while strengthening data-driven planning, accountability, service integration, and equitable delivery of community-based health interventions.
Duration
5 days
Who Should Attend
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Community health programme managers and coordinators
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Community health strategy and planning officers
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Community health workers and supervisors
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Primary healthcare programme managers
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Public health officers and programme coordinators
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Monitoring and evaluation specialists
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Health information and data management officers
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Community health surveillance officers
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Maternal, newborn, and child health programme teams
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Immunization and disease prevention programme officers
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Health promotion and community engagement specialists
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District, county, and regional health management teams
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NGO and development-partner community health programme staff
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Health data analysts and business intelligence professionals
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Community health quality improvement and performance management professionals
Course Objectives
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Develop practical skills for collecting, cleaning, managing, analysing, and interpreting community health programme data from household, community, facility, outreach, and population sources.
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Apply appropriate analytical methods to assess community service coverage, household engagement, outreach reach, referrals, follow-up, health promotion, and programme performance.
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Analyse community health worker workload, productivity, geographic distribution, service activities, referrals, and follow-up patterns to support effective workforce planning.
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Strengthen the ability to assess community health data quality, completeness, timeliness, accuracy, consistency, household identification, denominators, and reporting reliability.
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Use spreadsheets, databases, GIS, dashboards, and business intelligence tools to transform community health datasets into practical programme management intelligence.
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Conduct geographic, demographic, and equity-focused analysis to identify underserved households, hard-to-reach communities, access barriers, and gaps in community health service coverage.
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Integrate community and facility data to assess referral completion, continuity of care, service utilization, disease prevention, and linkages between community-based and facility-based services.
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Explore artificial intelligence, predictive analytics, digital community health platforms, mobile technologies, geospatial tools, and other emerging technologies relevant to community health management.
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Strengthen responsible management of household and community information through privacy, consent, cybersecurity, data governance, ethical analytics, and appropriate information-sharing practices.
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Develop integrated community health analytics products that translate programme data into meaningful dashboards, performance insights, planning scenarios, and actionable recommendations.
Comprehensive Course Outline
Module 1: Foundations of Community Health Programme Data Analytics
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Understanding the role of data analytics in community health planning, service delivery, population engagement, disease prevention, resource allocation, and primary healthcare strengthening.
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Exploring community health indicators covering household coverage, service contacts, referrals, outreach, health promotion, surveillance, follow-up, and community programme performance.
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Mapping information flows across households, community health workers, outreach teams, health facilities, district structures, programme units, and population health systems.
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Examining how community health intelligence supports microplanning, workforce deployment, supervision, resource allocation, equity monitoring, and evidence-based programme improvement.
Module 2: Community Health Data Collection, Quality, Integration, and Management
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Identifying data sources including household registers, community health worker records, mobile applications, outreach tools, referral forms, surveillance systems, surveys, and facility information systems.
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Assessing completeness, accuracy, timeliness, consistency, duplicate households, missing information, geographic identifiers, denominator quality, and aggregation errors.
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Applying data cleaning, validation, standardization, deduplication, reconciliation, coding, aggregation, disaggregation, and documentation techniques to community datasets.
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Exploring integration and interoperability between community health platforms, facility information systems, population databases, referral systems, and broader health information architectures.
Module 3: Spreadsheet, Database, GIS, and Business Intelligence Analytics
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Using spreadsheets for community health data preparation, indicator calculation, pivot analysis, trend analysis, quality checks, and routine programme reporting.
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Developing structured databases and analytical datasets for households, community health workers, service contacts, referrals, outreach activities, and population information.
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Applying GIS and spatial analysis to map households, service coverage, community health worker workloads, outreach locations, referrals, and underserved areas.
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Designing business intelligence dashboards that communicate community coverage, workload, service activity, referrals, geographic gaps, and programme performance.
Module 4: Community Health Coverage, Household Engagement, and Service Utilization Analytics
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Analysing household registration, household visits, community contacts, health education, screening, preventive services, and other measures of community programme reach.
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Examining service utilization patterns across communities, demographic groups, geographic areas, programme activities, and different periods.
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Assessing household engagement, missed contacts, follow-up, referral uptake, community participation, and other factors influencing continuity of community health services.
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Developing coverage and utilization indicators to support outreach planning, community mobilization, service targeting, supervision, and resource allocation.
Module 5: Community Health Worker Productivity, Workload, and Performance Analytics
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Analysing community health worker activities, household workloads, service contacts, referrals, follow-up, reporting frequency, and geographic distribution.
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Assessing workload balance, travel requirements, population-to-worker ratios, service intensity, productivity, and differences in performance across communities.
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Linking community health worker activity data with population and service-demand information to identify workload pressures, coverage gaps, and staffing needs.
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Developing performance scorecards and dashboards that support supportive supervision, coaching, workload planning, recognition, and programme improvement.
Module 6: Referral, Maternal and Child Health, Disease Prevention, and Community Programme Analytics
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Analysing community-to-facility referrals, referral completion, delays, feedback mechanisms, and continuity of care across different service pathways.
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Examining community-level maternal, newborn, child health, immunization, nutrition, family planning, and other preventive and promotive service activities.
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Integrating community surveillance and disease prevention information to identify emerging health concerns, service gaps, and opportunities for early intervention.
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Developing integrated programme performance measures that connect community activities with facility services, health outcomes, follow-up, and population needs.
Module 7: Geographic, Equity, Population, and Community Health Needs Analytics
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Applying GIS and geographic analysis to identify hard-to-reach communities, underserved households, service gaps, travel barriers, and areas requiring intensified outreach.
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Conducting equity analysis across age, sex, disability, socioeconomic circumstances, geography, population mobility, and other relevant community characteristics.
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Integrating population estimates, household information, service data, and community profiles to understand changing health needs and programme reach.
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Developing community health needs assessments and priority maps that support microplanning, resource allocation, outreach targeting, and equitable service delivery.
Module 8: AI, Predictive Analytics, Digital Community Health, and Emerging Technologies
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Exploring artificial intelligence and machine learning applications for community demand forecasting, risk identification, workload planning, referral prediction, and programme targeting.
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Examining digital community health platforms, mobile applications, electronic household records, decision-support tools, automated reminders, and digital supervision systems.
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Applying predictive and geospatial analytics to anticipate service needs, identify missed households, optimize outreach schedules, and strengthen community-facility linkages.
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Assessing emerging technologies while considering privacy, consent, algorithmic bias, digital exclusion, interoperability, cybersecurity, data quality, and responsible implementation.
Module 9: Community Health Data Governance, Privacy, Cybersecurity, and Responsible Analytics
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Understanding governance requirements for household and community information covering data ownership, stewardship, access rights, retention, documentation, accountability, and responsible information sharing.
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Applying privacy and confidentiality principles when handling household identifiers, personal information, health records, vulnerability information, and community profiles.
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Identifying cybersecurity risks affecting mobile devices, community health applications, cloud platforms, electronic registers, dashboards, and health information exchanges.
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Promoting responsible analytics through consent, data minimization, de-identification, appropriate aggregation, bias awareness, transparent methods, and careful communication of findings.
Module 10: Integrated Community Health Programme Analytics Project
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Developing an end-to-end community health analytics workflow covering data preparation, quality assessment, indicator calculation, geographic analysis, visualization, interpretation, and reporting.
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Building a practical dashboard covering household coverage, community health worker activity, service utilization, referrals, outreach, geographic gaps, workload, and programme performance.
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Conducting an integrated community health performance assessment to identify priority populations, underserved locations, workforce pressures, referral gaps, and evidence-based improvement opportunities.
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Presenting analytical findings and recommendations to community health managers and health-system decision-makers using clear visualizations, concise narratives, and actionable programme intelligence.
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.
