- Work in progress
Connected health care system centred around patients, families and caregivers is fast emerging as a popular model. Ontario Health Teams (OHT) are typical examples. As disparate healthcare and public health teams move towards a unified structure, there is a growing need to reconsider our information system strategy. This is a demo project to showcase a potential alternative for a scalable public health data warehouse for health information system integration. Read this article for more information.
Public health databases are vital for the community for efficient planning, surveillance and effective interventions. PHIS-DW adopts FHIR as the data model for storage with the integrated Elasticsearch stack. Kibana provides the visualization engine. 👀 Drishti is our framework for FHIR based behavioural intervention repository. PHIS-DW can support complex algorithms for disease surveillance such as machine learning methods, hidden Markov models, and Bayesian to multivariate analytics. PHIS-DW is work in progress and code contributions are welcome. We intend to use Bunsen to integrate PHIS-DW with Apache Spark for big data applications.
- Checkout or download this repository
- change the server url in docker-compose.yml
- sudo sysctl -w vm.max_map_count=524288
docker-compose up -d -f docker-compose-prebuilt.yml
- Access FHIR server at http://localhost:8092
- Access Kibana at http://localhost:8093
mvn clean package
- change the server url in docker-compose.yml
docker-compose up -d
- Access FHIR server at http://localhost:8092
- Access Kibana at http://localhost:8093
Bell Eapen (McMaster U)