Click here to learn more about the Master Data Management Service, and configure it.

Sync

1. Server should be responsible to handle or offer a mechanism to handle errors once data reaches it. (Error handling mechanism being designed by Platform).

2. Sync will be manually triggered by user (except for automatically syncing configuration down on first login).

3. Sync down of data is not required to supported (good to have) for first roll out.

4. Sync will be done through bulk APIs

5. Sync will send each save action performed by the field user while offline to the server to preserve an audit of actions performed by the field user.

   1. Eg: If a field user registers an individual and saves the record and then goes back to update the individual, this will result in 2 API calls to the server (one create and one update).

6. API Response compression Gzip will be turned on for all the endpoints

7. Unique identifier to be used between client and server

   1. Client will create a unique (client generated) identifier per entity (clientReferenceId) to relate entities while operations are being performed offline and send this id to the server for create operations.

   2. Any subsequent operations (like update, delete) will be on server gen id, so client has to get server gen id by searching using client generated id. Client will call search API with clientReferenceId and will get server generated id.

   3. Client will update the server generated id into the records on the client and use the server generated id for subsequent updates for those entities

8. Processing on the backend will continue to be asynchronous and not changed for the health use case.

Configurability

Backend

1. Search API max limit and default limit

2. Service details and endpoints

Frontend

1. Service details and endpoints

2. Number of entities sent to server in bulk API calls

3. Additional fields per entity in the app

4. The drop-down values or select options to be presented in the app for field users

5. Configuration changes are expected to be additive in order for the data captured against such configuration to continue being usable.

6. Number of retries on API call failure after which app should stop retrying

7. Timeout for API calls

Access Control

1. Access to data will be defined by the linkages of staff to project and the corresponding boundary while respecting role-action mappings instead of the tenant based approach.

Data

1. All deletes are soft deletes

2. Server is responsible to delete nested/child entities if applicable when the parent entity is deleted

3. Undeletion is not permitted

4. Duplicate updates do not need to be detected or filtered out. Client is responsible to send duplicate updates on entity as separate requests to server.

5. Since persistence in DIGIT is asynchronous but the sync process from the field worker app is likely to send dependent data in a short span of time, a cache is to be introduced against which dependent data can be validated if required while it is in the process of being persisted to the DB. This cache is exposed via the search API of the corresponding service and the caller is agnostic to whether the result was returned from cache or database.

6. For v1, we can maintain sequence of updates only for requests on a single entity by a single user. i.e. Updates on the same entity by multiple users will result in last caller's updates going through.

7. In order to maintain sequence of updates, a rowVersion field is introduced in every entity. Callers pass the rowVersion as received from the server. The server can detect if any out of sequence updates have come in and reject it / pass it to the error handling mechanism.

8. Search APIs will not return (soft) deleted data by default. If deleted data is required the includeDeleted param can be passed to the search APIs.

Limitations

1. From the Product requirement perspective, there is no unique identification identifier, so Platform is unable to check uniqueness of registry entities.

DIGIT is India’s largest open-source platform for digital governance. The health services are built on top of DIGIT. It is built on OpenAPI (OAS 2.0) and provides API-based access to a variety of services, enabling governments to provide health campaign services with relevant new ones. It also facilitates integration with the existing system into the platform and runs seamlessly on any commercial/on-prem cloud infrastructure with scale and speed.

Key Architecture Highlights

• Health DIGIT is a micro-services-based platform that is built to scale. Micro-services are small, autonomous, and developer-friendly services that work together.

• It facilitates decentralised control between teams so that its developers strive to produce useful tools that can then be used by others to solve the same problems.

• Micro-services have smart endpoints that process information and apply logic. They receive requests, process them, and generate a response accordingly.

• Parallelism in development: Micro-services architectures are mainly business-centric.

• A big software or system can be broken down into multiple small components or services. These components can be designed, developed, and deployed independently without compromising the integrity of the application.

Multi-layer Architecture

DIGIT Health follows a multi-layer or n-tiered distributed architecture pattern. As seen in the illustration above, there are different horizontal layers with some set of components such as Services, Registries and DIGIT Core Services. Every layer consists of a set of micro-services. Each layer of the layered architecture pattern has a specific role and responsibility within the application. The following are the advantages:

• Layered architecture increases flexibility, maintainability, and scalability.

• Multiple applications can reuse the components.

• Parallelism.

• Different components of the application can be independently deployed, maintained, and updated, on different time schedules.

• Layered architecture also makes it possible to configure different levels of security to different components.

• Layered architecture also helps users test the components independent of each other.

Note: Check the master promotion guide for more details.

The articles in this section includes:

DIGIT is an open-source platform licensed under the MIT license () compliant with the NUIS digital blueprint.

The detailed mapping of DIGIT’s capabilities with the core requirements mentioned in the NUIS digital blueprint has been done below:

Interoperability

Data specifications/models are available for domain entities. DIGIT is designed as an API-first platform wherein data specs/models are created for all key entities, thus ensuring interoperability through open APIs and open standards. Taxonomies are available for the key domain entities/registries. These can later be harmonised with standard taxonomies in the domain as and when they are made available. DIGIT data models and APIs are published as open APIs freely available to everyone in the ecosystem. Currently, DIGIT provides at least 3 key distinct APIs for all domain entities: create, update and search. Deactivation/cancellation of key entities in DIGIT is achieved through updating their status to inactive as per their defined specification/API contracts. Given the API-first and micro-services-driven nature of DIGIT, current APIs and models can be quickly harmonised with national standards as and when they are made available. DIGIT strives to leverage established domain standards (national/international), wherever available.

Data Privacy And Security By Design

Data Privacy

Data privacy capabilities are available to mark and protect sensitive data. The core service layer of DIGIT includes signing and encryption service as one of the core services that provide capabilities to sign/encrypt/mask sensitive data. It is designed such that it can work against software key stores and can be extended to integrate with any kind of hardware key store to store and protect signing and encryption keys. Encryption requirements can be defined and adhered to for the storage of sensitive data. DIGIT requires the user PII data to be stored in its user service, which is, by default, enabled for encryption of sensitive data as User Data Vault. All other services in DIGIT are required to access PII data by explicitly calling the user service, which, in turn, audits all access to PII. In addition, individual services in DIGIT can leverage DIGIT’s signing and encryption service (this is what the user service leverages to create User Data Vault) to further protect additional sensitive data available with the services. DIGIT provides the capability to define workflows for data modification that can be configured to have approval steps to get the needed consent for any data modification activities. DIGIT currently provides RBAC (Role-Based Access Control)-based access control for access (search) to data.

Security

Appropriate access controls can be defined in the APIs to ensure authorised access to sensitive data. DIGIT is designed to handle authentication and authorisation as perimeter control at its API gateway layer to ensure that unauthorised calls are not allowed to even contact the respective micro-services. DIGIT provides an RBAC mechanism where users are explicitly provided access to relevant resources by assigning them appropriate roles. By default, DIGIT supports OAUTH-based authentication for individual users and APIs. However, the authentication and authorisation filter in DIGIT is designed to be easily extendable to support any further authorisation and authentication needs. The perimeter security mechanism in DIGIT also helps developers in focusing on the functional developments for further services and offloading the access control requirements for new resources and their APIs to the API gateway using simple configurations. DIGIT also ensures that risks like the following are taken care of:

• Privilege escalation – form field manipulation

• Failure to restrict URL access

• Insecure direct object references (IDOR)

• Malicious file upload leads to cross-site scripting

• Improper authentication

• Missing account lockout

• Request throttling attack

• Weak encoding mechanism

• Sensitive information in URL

• Lack of automatic session expiration

• Insecure banner implementation

• Concurrent session

• Clickjacking

• Improper error handling

Transparency And Accountability Through Data

DIGIT has the capability to define key registries in OpenAPI 3.0 specs formats. It can easily achieve key APIs like create/update/search using its building blocks in core services, mainly through configurations and using lightweight extensions on a needs basis. DIGIT has the capability to protect person-specific sensitive data by encrypting them in the user data vault (user registry), which allows configuration-based protection of sensitive PII. DIGIT requires additional registries to reference PII using this mechanism. In addition, registries in DIGIT can leverage its data protection (signing and encryption) core service to provide additional protection to registry-specific attributes. The registry data in DIGIT can be signed for tamper-proofing, using its signing and encryption core service. A proof-of-concept for this has already been done on the ePass module that was built on the DIGT platform. All key data modifications in DIGIT are access logged to provide an audit trail, which can be accessed through APIs. The upcoming version of DIGIT is planning to bring in the concept of immutable event logs to further strengthen this capability. DIGIT leverages open-source telemetry to provide the ability to gather telemetry data and extends it for the DIGIT-specific processing pipeline. This framework allows for additional event definitions and contextual extension of the telemetry processing pipeline thereby future-proofing this capability in DIGIT.

Reusability and Extensibility

The DIGIT platform is designed as a collection of more than 50-plus atomic micro-services which are bundled together in a given context to provide end solutions. The micro-services in DIGIT can be divided into three main categories: data services (registries, reference master data management, etc.), tech infrastructure services (authentication, authorisation, notification engine, etc.) and domain services (assessment, NOC, etc.). Citizen, employee and administrative interfaces in DIGIT use these micro-services to achieve the needed functionality. Data models and APIs in DIGIT are defined as OpenAPI 3.0 specifications and can be extended by using a combination of configuration and extension techniques. For example, if the additional attributes are only needed to be stored with format validation, it can be a simple schema extension, while if the additional business checks/functionality need to be implemented using the extended attributes, then it can be achieved using pre/post request filters or extending underlying micro-services. DIGIT allows the extension of existing capabilities without needing architectural interventions. As described above, the extension of existing functionality on DIGIT can be achieved using additional configurations, additional extension services, or request/response filters. Several partners have extended DIGIT modules to cater to new use cases. For instance, DIGIT mCollect module caters to the collection of fees for over 50 services on the counter, but it does not have a citizen interface for the payment of these services online. The Directorate General Defence Estates (DGDE) wanted to introduce this interface for the citizen’s of cantonment boards in India, and were able to easily enhance the mCollect module to include this capability. DIGIT supports single-instance multi-tenancy to enable sharing of the underlying infrastructure. All DIGIT data models and services are designed to be multi-tenanted. DIGIT uses an API-first approach in its design and development to ensure loose coupling between its various components. These APIs are clearly defined using OpenAPI 3.0 specifications to ensure clear documentation.

Evolvability and Scale

A new functionality can be added by rebundling existing building blocks in the context of new use cases and implementing only additionally-required services without requiring any architectural overhaul. Additionally, due to its loosely coupled API-driven design, DIGIT allows for new components to be implemented in the technology that is most useful for that use case. The API-driven, micro-services-based architecture of DIGIT enables its components to evolve separately. On DIGIT, individual components can evolve separately to enable the heterogeneous evolution of the system. DIGIT uses SemVer 2.0 for the versioning of its micro-services and interfaces. Semantic versioning is a formal convention for specifying compatibility using a three-part version number: major version; minor version; and patch. More details on this can be found on this link: https://semver.org/. DIGIT is designed to be horizontally scalable. The microservices-based architecture of DIGIT also enables it to scale only needed components/services, thereby providing resource efficiency. For example, the billing and collection services can be scaled separately during a financial year closing if the load pattern indicates increasing volume of bill payments during that period. DIGIT is designed to be hardwarec agnostic and can be run on any hardware. It has been tested on multiple commercial clouds and state-sponsored bare metal infrastructure. Components of DIGIT that need to use underlying hardware have been carefully chosen (in case where DIGIT is using other open source components) or designed (DIGIT’s own components) to provide a layer of abstraction that can be extended for any types of hardware.

Multi-channel Access

DIGIT is designed using an API-first approach, therefore enabling any user interface channel to leverage it. DIGIT’s own user interfaces (web/mobile app, WhatsApp, Chatbot) are implemented using its APIs to ensure that the offered platform capabilities and data are accessible to any delivery channel based on configured policies. DIGIT’s access control mechanism can be configured to provide different levels of access based on channels and roles.

Ecosystem-driven

The DIGIT platform and its user interfaces are completely open source. All external components used in DIGIT are also open source. Due to its API-based and event-driven architecture, DIGIT can be integrated with any existing stack. Wherever appropriate, DIGIT also provides out-of-the-box integrations with crucial stacks/platforms. The most common integrations are to payment gateways, SMS providers and SMTP email servers for a typical implementation. More than 14 organisations have already partnered with us to implement DIGIT across multiple implementations in India, and have built over 20 new solutions on top of the platform. DIGIT also provides the capability to gather feedback from the ecosystem in a digital manner. The feedback capability in DIGIT can be looked at the following levels:

• Service delivery feedback on services offered through DIGIT: DIGIT provides a highly configurable and extensible public grievance module to enable this kind of feedback/redressal for functional users (such as citizens, and employees).

• Service usage feedback: The DIGIT user interfaces include a telemetry SDK which is backed by telemetry infrastructure in DIGIT platform. Coupled with API access logs, this enables DIGIT to gather usage feedback through live action and can be used for fine tuning interfaces and APIs

• Design/Feature feedback - As an open source project on Github, DIGIT provides a mechanism to provide comments/feedback on its various components using github. This feedback can be leveraged to create a Point of View on the future roadmap for the platform.

The articles in this section include:

Here are the articles in this section:

API Spec

Sequence Diagrams

The articles in this section include:

API Spec

Sequence Diagrams

API Spec

Sequence Diagrams

Here are the articles in this section:

• Overview and Key Capabilities

• Tech Enablement Training - Essential Skills and Pre-requisites

• DevOps Skills Requirements

• Infra Requirements

• Infra Best Practices

• Operational Best Practices

• Why Kubernetes For DIGIT

This section discusses the supported cloud environment for DIGIT services. It provides information on where and how DIGIT is deployed. Further, it offers guidelines for estimating the infrastructural requirements for cloud support.

• Google Cloud

• Azure

• AWS

• VSphere

• SDC

Here are the articles in this section:

• Setup requirements

• Supported clouds

Click here to know more about our data setup guide.

Click here to know more more.

Health Campaign - High Level Design

The high level design is divided into:

1. Master Data

2. Registries / Entities

3. Reusable DIGIT Services

4. Form engine support

5. Multi tenancy

6. Android offline first app

7. Web app - Campaign planning + dashboard

8. External integration - DHIS2

Base Health Campaign on DIGIT Core 2.8.

Master Data

Master data categorized on the complexity required to maintain them from the technical perspective.

1. Simple Masters

   1. Roles

   2. Additional Field schemas for different entities

   3. Project Task configurations

   4. Project Type

   5. Role-Actions

   6. Actions

2. Hierarchical Masters

   1. Administrative Boundary and Hierarchy

3. Inter linking Masters

   1. Field app config

   2. Service Registry

Services/Registries

Individual Registry

• New service

• As users are registered to campaigns, populate the individual registry with basic information about them.

• This registry is the first step towards the long term plans in DIGIT to move non users of the system away from the User service. However, due to the current dependency on User service for authN and authZ among other things, this registry will be a wrapper over the User service.

Household Registry

• New service

• Collection of Individuals living together (potentially receiving shared campaign intervention)

Facility Registry

• New service

• Needed to model storage Warehouses through which stock moves.

Product Registry

• New service

• Needed to model the resources that are distributed as part of projects both as part of stock movement and actual distribution to beneficiaries.

Project Service

• New service

• Models how services and benefits are typically distributed to citizens by governments

• Contains multiple endpoints within the service to map other entities such as beneficiaries, staff, facilities, resources to the projects.

Stock Service

• New service

• Track inflow and outflow of stock resources

Reusable DIGIT Services

Many of the DIGIT-Core services can be reused without any changes. Some of them could be extended and enhanced to support the required features.

DIGIT Services reused as-is

• digit-mdms-service

• Digit-location / boundary service

• digit-access-control

• Zuul API Gateway

• digit-idgen

• digit-persister

• digit-indexer

• digit-localization

• DSS

• Signed Audit

DIGIT Services reused with enhancements

No existing services being enhanced.

Workflow

The Health Campaign system does not make heavy use of workflows. Most flows in v1 are single actor and end after a single step (i.e. submitting collected data).

High Level Design Diagram

ER Diagram

Form Engine support

Form engine support was pushing out timelines and has been dropped from v1 scope.

Multi tenancy

The proposal is to have a single installation to support multiple countries and multiple health campaigns within these countries. Different campaigns will need to share registries.

Leveraging multi tenancy support in DIGIT for this.

Android App

Offline First

Android app is proposed to be modeled on mGramSeva app and will be built in Flutter.

This app will be used in areas with limited or no internet connectivity and hence will need to work while offline. Users will sync the data collected offline when they are in an area with network connectivity.

SQLite will be used to model structured data and ISAR will be used for unstructured data.

Form Renderer

Out of scope for v1.

Offline Dashboards

The field workers will need to see dashboards based on the data stored in the offline database. Library - TBD

Web App

Campaign Planning App

Out of scope for v1.

Dashboards App

The app will have some custom screens to capture information around the campaign plan.

DSS dashboards are planned to be leveraged for reporting dashboards.

External Integration

DHIS2

This will be added to implementation scope.

Release Summary

HCM 1.0 is a base version release that has functional and non-functional requirements:

• Functional: Built new registries: Individual, Household, Facility and Product. The release also has services: Project and Stock

• Non-functional: The services support bulk and non-bulk APIs which can be used in online and offline modes for the HCM app.

Features

Document Resources and Links

Integration & Interoperability with DHIS2:

https://dhis2.org/integration/

Basic features

Data Capture

Validation

Analysis

Presentation

Points to explore

SDMX-HD and ADX standards for interoperability

SDMX: https://ec.europa.eu/eurostat/web/sdmx-infospace/trainings-tutorials

SDMX-HD:https://wiki.openmrs.org/display/docs/SDMX-HD#:~:text=SDMX%2DHD%20(Health%20Domain),and%20metadata%20between%20medical%20organizations.

ADX: Aggregate Data Exchange

Modules of concern

DHIS2 Web API

DHIS2 Core

How can we use it?

It exposes REST API(s) over DHIS2 Core which we can utilise.

Web API Integration

https://docs.dhis2.org/en/full/develop/dhis-core-version-master/developer-manual.html

Authentication

DHIS2 provides Basic Auth, Two Factor Auth, Personal Access Token(PAT) and OAuth2. Basic Auth is the least secure and Two Factor Auth is for direct DHIS2 users.

PAT

By default PAT will have all the authorizations that the user has. This can be configured or a special user can be created having only the required permissions.

The token is configurable via API and only the constraints can be modified after a token is created.

Token key is returned only once when the token is generated.

Expiry of the token can be configured via Web API along with other constraints.

OAuth2

We can go with grant_type as password. This can be configured via Web API too. Grant_type password would involve sharing username and password. However, this will be in a POST call body.

Login Credentials

http://43.205.92.152/dhis-web-commons/security/login.action

User: admin

Pass: district

DHIS2 Fields and Mappings

DHIS2 Fields Extract

List of the metadata which are required and there attributes

Note this data is extracted from the schemas endpoint of DHIS2

DHIS2 is District Health Information Software 2.

Some Details

The DHIS 2 is a routine data based health information system which allows for:

• data capture,

• aggregation,

• analysis, and

• reporting of data.

Data Model

The data model is generic in all dimensions in order to allow for capture of any item of data.

The model is based on the notion of a DataValue.

A DataValue can be captured for

• any DataElement (which represents the captured item, occurrence or phenomena),

• Period (which represents the time dimension), and

• Source (which represents the space dimension, i.e. an organisational unit in a hierarchy).

METADATA Diagram taken from the DHIS2 technical documentation

The diagram is taken from the core technical documentation for understanding the relationships between the DHIS2:

While adding dhis2 client https://github.com/dhis2/dhis2-java-client

Master Data

The following data is needed for DIGIT ecosystem

Boundary Hierarchy

Boundary and Boundary Hierarchy is part of one time setup. All the fields cannot be fetched from the DHIS2 directly. Some manual intervention is needed.

Projects/Boundaries

Clubbing projects and boundaries because both of these can be populated from same set of master data. These are directly correlated to Organisational Units. Targets to be fetched from forms. The forms of interest are “RTIs Metas Macroplano” and “RTIs Metas Microplano”. They are available at village level only. Projects and relevant targets can be fetched from the following boundary information.

Users

Product

Product and Product variant are one time config

ration for a campaign. Unable to find equivalent in DHIS2. Will need to double check.

For Mozambique, the following are being tracked on DHIS2 at a team level.

• Red Sticker

• Green Sticker

• Bednet

At the district and community warehouses only bed nets are being tracked.

Shapefile

OrgUnits have shapes (geometry) associated with them. Granularity is available only till district level. If we have to generate the shapefile dynamically, it will be tedious. Would be better to check with the CHAI team about how they are downloading the shapefiles from DHIS2 and replicate.

Facility

Unable to find on DHIS2. Will need to check with Mrunal and CHAI team.

Transactional Data

Types of Data

There are two types of transactional data that we need to ingest into DIGIT from DHIS2.

• Beneficiary - In the case of Moz it is Household data.

• Service Delivery - In the case of Moz, this is the bed net being distributed.

• Inventory management

• Supervisor checklist - Forms are available in DHIS2, need to understand DIGIT models before this mapping can be done.

DHIS2 Forms

The following forms contain transactional data in DHIS2

Beneficiary

This data is extracted from the form called “Ficha de Registo dos Agregados Familiares”. The only Beneficiary field available is the Head of household’s name and memberCount of the household. The rest of the required fields will be empty.

Service Delivery

This data is extracted from the form called “Ficha de Registo dos Agregados Familiares”.

Inventory Management

At the start of the campaign we will need to ingest data from the physical count form. Entry and Exits are tracked through the entry and exit form mentioned above. We will need to do this for District and Community warehouses. The fields remain the same only the forms are changing. Which means the appropriate IDs will also change. The following are the forms:

Supervisor Checklist

The spec of the survey service is being worked on at the product side. Once the design is completed, this section will be addressed.

DHIS2 Service Delivery form

On DHIS2 there is a single form that captures Bednet distribution as well as household registration (Both the required transactional data fields). This form is called “Ficha de Registo dos Agregados Familiares”. We will have to convert this single form data into two DIGIT payloads - Beneficiary and Benefit (or Service Delivery or Task).

All data is collected at a village level only in DHIS2. This form has the following fields.

DHIS2 Warehouse Inventory Tracking forms

Introduction

This document lists the technical skillset required for someone to build and support the Health Campaign Management platform. There are distinct skills required to customise the application, and set up and run the infrastructure for this. The basic hardware configuration required for the developer machine is part of this document.

Technical Skillset

The technical skill sets that are required to work on the DIGIT HCM stack are listed below. It is expected the team has satisfactory knowledge of the below technologies before they take up DIGIT training.

Development Team Skillset

• Open API Contract - Swagger2.0

• YAML/JSON

• Postman

• Postgres

• Java and REST APIS

• Basics of Elasticsearch

• Maven

• Springboot

• Kafka

• Zuul

• ReactJS

• Flutter

DevOps Team Skillset

• Understanding of the micro-service architecture.

• Experience with AWS, Azure, GCP, and NIC Cloud.

• Strong working knowledge of Linux, command, VM Instances, networking and storage.

• To create Kubernetes cluster on AWS, Azure, and GCP on NIC Cloud.

• Kubectl installation & commands (apply, get, edit, describe k8s objects)

• Terraform for infra-as-code for cluster or VM provisioning.

• Understanding of VM types, Linux OS types, LoadBalancer, VPC, Subnets, Security Groups, Firewall, Routing, DNS)

• Experience setting up CI like Jenkins and creating pipelines.

• Deployment strategies - Rolling updates, Canary, Blue/Green.

• Artifactory - Nexus, Verdaccio, DockerHub, etc.

• Experience with Kubernetes ingress, setting up SSL certificates and renewal

• Understanding of Zuul gateway

• Gitops, Git branching, PR review process. Rules, Hooks, etc.

• Experience in Helm, packaging and deploying.

• Apache, Nginx, Redis and Postgres.

Hardware Pre-requisites

Teams are expected to have laptops/desktops configured as mentioned below with all the software required to run the DIGIT application:

• Laptop for hands-on training with 16GB RAM and OS preferably Ubuntu

• All developers need to have Git ids

• Install VSCode/IntelliJ/Eclipse

• Postman

Software Assets

There are the knowledge assets available on the net for general items and eGov assets for DIGIT services. Here you can find references to each of the topics of importance. It is mandated the trainees do a self-study of all the software mentioned in the pre-requisites using the reference materials shared.

API Spec

Sequence Diagrams

API Spec

Sequence Diagrams

Here are the articles in this section:

API Spec

Sequence Diagrams