A practical consulting service for organisations that want to turn fragmented routine health data into validated indicators, analytical databases, dashboards and repeatable decision-ready reports.
epiGuider designs reporting workflows around the client’s actual decisions, data sources, reporting obligations and team capacity. Tools are selected to fit the context and may include Excel, R, Power BI, Epi Info, EpiData, KoboToolbox, XLSForm, DHIS2, QGIS, ArcGIS, Word, PowerPoint and PDF workflows.
The client problem
- Fragmented spreadsheets and disconnected data sources
- Manual indicator calculations and repeated copying and pasting
- Inconsistent tables, charts and reporting formats
- Delayed reporting and limited time for interpretation
- High risk of manual error and weak reproducibility
- Systems that depend on one person and are difficult to hand over
Who the service is for
NGOs, Ministries of Health, public-health programmes, hospitals, research organisations, development partners, humanitarian projects and disease-control programmes with recurring analytical or reporting needs.
The proposed solution
An integrated analytical and reporting workflow that standardises source data, applies documented quality controls, calculates agreed indicators, produces reusable visual outputs and generates consistent reports with clear user guidance.
Typical inputs
- Routine service databases
- Aggregated health data
- Facility or programme datasets
- Geographic reference data
- Indicator frameworks and logframes
- Data dictionaries
- Existing dashboards
- Reporting templates and requirements
Only the minimum data necessary for the agreed work should be shared. De-identification and controlled access are applied where appropriate.
Implementation process
- Discovery: clarify users, decisions, reporting cycles, source systems and constraints.
- Assessment: review data sources, reporting requirements and data quality.
- Standardisation: define variables, dictionaries, indicators and validation rules.
- Development: create analytical workflows, tables, charts, dashboards and automated outputs.
- Testing: reconcile indicators, test repeatability, review exceptions and obtain client feedback.
- Documentation: prepare user guidance, methods notes, quality checks and maintenance instructions.
- Training and handover: train users, transfer approved files and confirm responsibilities.
Potential deliverables
Deliverables vary by engagement and may include:
- Data-system assessment
- Clean analytical dataset
- Data dictionary
- Indicator-reference framework
- Automated calculations
- Dashboard and visual outputs
- Automated Word or PDF report
- Automated PowerPoint presentation
- User guide and methods note
- Training and handover session
- Quality-assurance checklist
- Maintenance recommendations
Data-quality controls
- Validation and range rules
- Missing-data and duplicate checks
- Internal consistency checks
- Indicator verification and reconciliation
- Documented exception handling
- Reproducibility checks
Dashboards and visualisations
Depending on needs, outputs may use Excel, Power BI, R or GIS tools such as QGIS and ArcGIS to present indicators, trends, maps, scorecards and operational exceptions.
Reporting outputs
Possible outputs include Word, PDF and PowerPoint reports, Excel dashboards, static analytical reports and web-ready tables or visualisations. The format is selected for the intended users and reporting context.
Training and handover
Systems should be documented, maintainable, transferable and adapted to user capacity. Handover may include training, guided practice, user documentation, quality checks and maintenance recommendations.
Optional maintenance support
Post-delivery technical assistance may be agreed for monitoring, troubleshooting, revisions or controlled expansion. Availability, response times and responsibilities must be defined separately; long-term support is not automatic.
Confidentiality and data protection
Engagements should use the minimum necessary data, de-identification where appropriate, controlled access, secure handling, clear ownership and client approval before any output is shared. Confidential data are never used as public examples without explicit authorisation.
Exclusions
The service does not automatically include clinical decision-making, hosting of sensitive databases, unapproved access to patient data, legal data-protection certification, software licences, long-term support unless agreed, or recovery of information that is irreparably incomplete in the source data.
Scope and responsibilities are confirmed during discovery before implementation begins.
Start with a discovery discussion
Discuss your organisation’s current data sources, recurring reports, quality concerns, decision needs and internal capacity. epiGuider can then recommend a proportionate scope without assuming a particular tool or solution.