Health Information Systems Data Management Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends Health Information Managers, Monitoring and Evaluation Officers and others
Fee from USD 1,100 KSh 95,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 9 Nov 2026 Course code SD-HSM-023

Before you join: Participants should understand routine health-service reporting, including common terms such as facility, indicator, numerator, denominator, reporting period and disaggregation.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Health services depend on reliable routine data to plan supplies, monitor programme coverage, identify service gaps and account for results. Yet many reporting systems contain duplicated facility records, unclear indicator definitions, late submissions, incomplete fields and dashboards that do not answer management questions. Health information staff need to manage the full path from source registers and facility reporting through metadata configuration, validation, analysis and action.

This course develops the working knowledge needed to manage health information in DHIS2-style health management information systems. Participants examine system architecture, organisational units, data elements, indicator formulas, datasets, category combinations and reporting periods. They learn to configure data-entry structures, import data, apply validation rules, assess data quality, manage user access and produce meaningful pivot tables, dashboards, maps and routine reports. The course also addresses governance, privacy, interoperability and operational support for national, regional and facility-level reporting.

Teaching combines short instructor briefings with health programme cases, guided system configuration, data-quality investigations, reporting simulations and peer review. Cases reflect common public-health uses such as immunisation, maternal health, HIV services, disease surveillance and district performance management. Participants leave with a reusable DHIS2 configuration workbook, indicator reference sheet, data-quality review plan, validation-rule register, dashboard specification and 90-day system improvement plan.

The course suits professionals responsible for routine health information systems rather than software developers. It is particularly useful for staff supporting ministries of health, hospitals, donor-funded programmes, NGOs, health insurers and implementing partners that need consistent reporting and defensible management information.

What you will be able to do

  • Configure organisational units, datasets, data elements and reporting periods in a DHIS2-style system
  • Define indicator formulas using numerators, denominators, disaggregation and target values
  • Build validation rules and completeness checks to identify reporting errors
  • Assess routine data quality using the WHO Data Quality Review framework
  • Produce pivot tables, charts, maps and dashboards for programme management decisions
  • Apply role-based access controls, data-sharing rules and audit-trail procedures
  • Map source-to-report data flows and identify duplication, delay and reconciliation risks
  • Create a 90-day health information system improvement plan with ownership and milestones

Benefits of attending

For you

  • Configure routine reporting structures with clearer metadata and indicator definitions
  • Diagnose incomplete, inconsistent and implausible facility submissions systematically
  • Produce management dashboards that answer programme and district review questions
  • Document data flows, governance responsibilities and reporting controls credibly
  • Lead practical health information system improvement actions with measurable milestones

For your organisation

  • More consistent facility reporting through standardised datasets, periods and validation rules
  • Earlier detection of missing reports, duplicate records and implausible values
  • Stronger evidence for programme reviews, donor reports and resource allocation decisions
  • Reduced dependence on ad hoc spreadsheets for routine health-service reporting
  • Clearer accountability for metadata changes, user access and data-quality follow-up

Course modules

10 modules over 5 days

Participants can explain routine health information flows and identify the DHIS2 components supporting them.

  • Routine health information system purposes, data flows, reporting cycles and decisions
  • DHIS2 architecture: metadata layer, transaction data, analytics services and applications
  • Facility-to-national reporting pathways mapped using source-to-report data flow diagrams
  • Aggregate, event and tracker data models distinguished by reporting use
  • Health programme indicators linked to planning, supervision and resource allocation
  • Data governance roles assigned through RACI matrices and reporting calendars

Participants can configure core metadata structures that support consistent reporting across health facilities.

  • Organisation unit hierarchies designed for national, district, facility and community reporting
  • Organisation unit groups classify facility ownership, service level and geographic attributes
  • Data elements specified with value type, aggregation operator and domain type
  • Category combinations define sex, age, service point and other disaggregations
  • Datasets assembled from related data elements, sections and compulsory fields
  • Reporting periods matched to weekly, monthly, quarterly and annual programme cycles
  • Metadata naming conventions prevent duplicate objects and ambiguous reporting definitions

Participants can define and document indicators suitable for routine health programme monitoring.

  • Indicator reference sheets document purpose, formula, source, frequency and interpretation
  • Numerator and denominator definitions tested against service registers and reporting forms
  • Annualised values, reporting rates and coverage measures calculated correctly
  • Disaggregated indicators reveal equity gaps by sex, age, geography and facility
  • Targets, baselines and thresholds set for programme performance monitoring
  • WHO indicator metadata standards applied to reduce inconsistent interpretation
  • Duplicate counting risks identified within referrals, repeat visits and outreach services

Participants can manage routine data capture and import processes with traceable controls.

  • Data-entry forms structured for facility workflows and mandatory reporting fields
  • Bulk data imports prepared using DHIS2 import templates and identifier matching
  • CSV import errors resolved through mapping, validation feedback and exception logs
  • Data approval workflows distinguish submitted, reviewed, approved and locked values
  • Source-document reconciliation compares registers, tally sheets and reported totals
  • Event capture records individual service encounters without exposing unnecessary identifiers
  • Import audit logs retained for correction tracking and accountability

Participants can detect, investigate and document common routine health data-quality issues.

  • Validation rules compare related values using arithmetic expressions and thresholds
  • Completeness rates measure expected reports received from reporting units
  • Timeliness analysis identifies late submissions against reporting calendar deadlines
  • Outlier detection uses historical ranges, z-scores and programme thresholds
  • WHO Data Quality Review dimensions assess accuracy, completeness and consistency
  • Plausibility checks compare service volumes, stocks, staffing and target populations
  • Data-quality issue registers assign corrective actions, owners and due dates

Participants can create reporting outputs that support programme and operational decisions.

  • Pivot tables combine indicators, organisation units, periods and disaggregations
  • Charts selected using comparison, trend, composition and distribution purposes
  • Thematic maps display geographic variation using appropriate classification intervals
  • Dashboard layouts prioritise exceptions, targets, trends and management actions
  • Data interpretation separates reporting artefacts from plausible service-delivery changes
  • Drill-down analysis investigates district, facility and period-level performance gaps
  • Standard report templates align narrative findings with tables, charts and actions

Participants can administer access and apply practical controls for sensitive health information.

  • User roles assign minimum necessary permissions through role-based access control
  • Organisation unit access restricts data entry and viewing by assigned scope
  • User groups simplify permission management for facilities, districts and programmes
  • Audit trails record data changes, approvals, imports and administrative actions
  • Data-sharing agreements define permitted use, retention, disclosure and accountability
  • Privacy impact assessments identify risks involving personal and sensitive health data
  • ISO/IEC 27001 control concepts applied to access, logging and incident handling

Participants can assess integration requirements between routine reporting systems and related applications.

  • Interoperability use cases define source systems, recipients, triggers and required data
  • HL7 FHIR resources distinguish patient, encounter, observation and organisation information
  • Master facility lists reconcile identifiers across reporting, laboratory and logistics systems
  • Data exchange mapping aligns field names, code sets, formats and update frequencies
  • API authentication methods protect system-to-system data transfers and service accounts
  • Aggregate reporting interfaces separate summary indicators from individual health records
  • Interface monitoring tracks failed messages, duplicates, latency and reconciliation outcomes

Participants can organise routine administration tasks and resolve common user support issues.

  • Administration calendars schedule metadata releases, reporting deadlines and user reviews
  • Change-control registers document requests, approvals, testing and release decisions
  • Metadata maintenance checks identify inactive units, duplicate elements and obsolete datasets
  • Help-desk triage classifies access, configuration, data-entry and analytics incidents
  • Root-cause analysis uses five whys for recurring reporting and system problems
  • Standard operating procedures document escalation routes, response times and issue closure
  • Backup and recovery requirements distinguished from routine metadata export procedures

Participants can convert data-quality findings into prioritised health information system improvements.

  • Data review meetings convert dashboard findings into documented management actions
  • Problem statements separate data-quality symptoms from process and capacity causes
  • Prioritisation matrices score improvement actions by impact, effort, risk and urgency
  • SMART milestones assign owners, dates, evidence and escalation requirements
  • Supportive supervision plans link facility feedback to recurring reporting deficiencies
  • 90-day improvement plans sequence metadata, process, training and governance actions
  • Progress indicators monitor completion, adoption and sustained reporting quality

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. DHIS2 metadata configuration workbook
  2. Health indicator reference sheet
  3. Validation-rule and data-quality register
  4. Routine reporting dashboard specification
  5. Data governance RACI matrix
  6. 90-day health information improvement plan

Who should attend

  • Health Information Managers — responsible for routine reporting structures, quality controls and information use
  • Monitoring and Evaluation Officers — need consistent indicators, disaggregation and reporting outputs
  • DHIS2 Administrators — configure metadata, users, validation rules and reporting applications
  • Ministry of Health Programme Officers — use service data to monitor coverage and district performance
  • NGO and Donor Programme Managers — require credible reporting from implementing facilities and partners
  • Hospital Data Officers — manage facility submissions, reconciliation and management reporting

Skills and tools covered

DHIS2 metadata configurationHealth indicator designRoutine data qualityDashboard reportingData governanceInteroperability planning

Tools and standards

DHIS2, WHO Data Quality Review Toolkit, HL7 FHIR, ISO/IEC 27001

How the course runs

Training methodology

The course uses short technical briefings followed by guided configuration and analysis tasks in a DHIS2-style environment. Participants work through health programme cases involving facility reporting, indicator calculation, data-quality investigation and district performance review. Small-group exercises test metadata choices, validation rules, dashboards and access permissions. Reporting simulations require participants to interpret incomplete or inconsistent submissions and recommend corrective action. Each participant develops an application plan linked to a current reporting or information-use issue.

Requirements and prerequisites

Participants should understand routine health-service reporting, including common terms such as facility, indicator, numerator, denominator, reporting period and disaggregation. Experience entering, reviewing or using health programme data is helpful. Familiarity with spreadsheets, basic tables and simple calculations is assumed. Participants should be comfortable working with browser-based systems and interpreting service-delivery reports. Prior DHIS2 administration experience is not required, and no programming, database administration, server installation or advanced statistical knowledge is expected.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

You should understand basic routine health reporting and be able to work with spreadsheets and simple calculations. Previous DHIS2 configuration or programming experience is not required.

Bring a laptop suitable for browser-based work and, if permitted, an example of a reporting form, indicator list or anonymised data-quality issue from your workplace. Training system access and course materials are provided.

It is designed for health information managers, M&E staff, programme officers, DHIS2 administrators and data officers. It is also suitable for managers who oversee routine reporting and need to challenge data quality constructively.

This course focuses on reporting design, metadata, data quality, analytics, governance and operational administration. It does not teach server deployment, database tuning, custom application development or advanced programming.

Participants can review an indicator definition, build validation rules, assess reporting completeness, improve a dashboard or clarify user permissions. The final improvement plan provides a structured starting point for a current system issue.

Training runs from 08:30 to 16:30 each day, with about 6.5 contact hours daily. Time is divided between technical instruction, guided system work, case analysis, group discussion and improvement planning across the ten modules.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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