My presentation of MSc Business Intelligence project.

1. SMARTMRS
A BI solution for OpenMRS
Presented by V B Wickramasinghe (148245F)

2. ● Introduction
● OpenMRS data model
● SmartMRS technology stack
● Why not Pentaho?
● Easy OLAP
● Demo
Overview

3. ● OpenMRS is a widely used open source medical record system.
● SmartMRS is a business intelligence solution for OpenMRS.
● A typical OpenMRS installation accumulates large amounts of data.
● This combined with the complexity of the medical domain makes it a hard
task to extract intelligence from OpenMRS manually.
● But OpenMRS can provide very useful and critical insights for society if
used correctly.
Introduction

4. Introduction
Detect spread
of disease
Detect
environmental
issues
Predict
medicine
demand
Predict medical
staffing
requirements
Analyze social
health trends
Ensure medical
data availability
Ensure medical
staff efficiency
Ensure
implementation
of proper health
policy
+

5. OpenMRS data model is complex but centered around few main entities,
● Concept: Concepts are defined and used to support strongly coded data throughout the system
● Encounter: Contains the meta-data regarding health care providers interventions with a patient.
● Form: Essentially, the user interface description for the various components.
● Observation: This is where the actual health care information is stored. There are many
observations per Encounter.
● Order: Things/actions that have been requested to occur.
● Patient: Basic information about patients in this system.
● User: Basic information about the people that use this system.
● Person: Basic information about person in the system.
● Business: Non medical data used to administrate openmrs
● Groups/Workflow: Workflows and Cohort data
OpenMRS data model

6. OpenMRS data model

7. ● Python based - Because of simplicity, ad hoc style of
programming and great data analysis tools etc.
● Connects directly to backend MySQL db of OpenMRS for
now.
● Uses Cubes library for OLAP and data warehouse
functionality.
● Uses CubesViewer frontend for online user interface
● Can choose among the likes of ScikitLearn, Orange for
Data Mining.
SmartMRS technology stack

8. SmartMRS technology stack
Datamining
Reporting + dashboards
Data warehouse + OLAP Framework
Language + Data Integration framework
Database

9. Pentaho is the natural choice for open source BI solutions.
Which I also investigated for SmartMRS solution. But it has
some disadvantages compared to the Python/Cubes based
solution.
1. Complexity and sophistication of Pentaho makes it
harder to customize.
2. Pentaho documentation is lacking for solution
implementers(intentionally?).
3. Python vs Java
Why not Pentaho?

10. ● Start with Cubes model definition(check IDE),
● We use Observation(obs table) as fact table.
● Location(location table) as dimension table.
● Use country, province, area as drill down levels.
● Also define observation time as a dimension.
● Can drill down definitions of observations using concept
dimension.
● Many other cube definitions possible.
● With cubes you get a REST API for all cube queries as
well.
Easy OLAP

11. ● Cubes ad hoc analysis
● Cubes Viewer
Demo

12. Any Questions?

13. Thank You