DHIS2

DHIS2

DHIS2 is an open source health management information system used for data collection, management, analysis and visualization. It supports aggregate data as well as patient and event-level data across health programs.
DHIS2 image
data-collection data-management data-analysis data-visualization health-programs

DHIS2: Open Source Health Management Information System

DHIS2 is an open source health management information system used for data collection, management, analysis and visualization. It supports aggregate data as well as patient and event-level data across health programs.

What is DHIS2?

DHIS2 is an open source, web-based health management information system used for data collection, management, analysis and visualization. It supports aggregate data as well as patient and event-level data across health programs.

Some key features of DHIS2 include:

  • Flexible data model and metadata structure to capture a variety of health data
  • Inbuilt analytics with pivot tables, charts, maps and dashboards
  • User and organizational unit management for access control
  • Event capture and tracking with analytics
  • Support for both online and offline data collection using mobile devices
  • Interoperability using international standards like FHIR and GDPR compliance

DHIS2 is used by governments and organizations across Africa, Asia, Europe and Americas for monitoring and improvement of health programs. With a strong developer community and network of implementation partners, DHIS2 provides localized solutions for various public health requirements.

DHIS2 Features

Features

  1. Data collection
  2. Data management
  3. Data analysis
  4. Data visualization
  5. Aggregate data support
  6. Patient-level data support
  7. Event-level data support
  8. Support for multiple health programs

Pricing

  • Open Source

Pros

Open source

Flexible and customizable

Scalable

Built-in data analytics tools

Web-based platform

Large user community

Cons

Steep learning curve

Requires IT infrastructure

Limited built-in support for some statistical methods

Can be complex for basic use cases


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