In the era of "Data and Information", data became the key to save lives. With the rapid growth in Information & Communication Technology (ICT), the power of Technology has strongly impacted our lives.Storing complex medical data of people become easier, but not easy enough to access to this information and understand it without the right technology solution, which make limits to patients from actively managing their own healthcare.
The project is built on prior efforts to re-design a new and efficient approach of interacting with large amounts of complex medical data through a «Timeline». It describes visually the when, for whom, and what has been done to describe patient's health care situation.
...
Index.html : The main page
/Doc : contains presentation slides about the project.
/JS : contains different Java Script files
FakedData.js ; contains model of medical data classifier .
OpenMRSRestCalls.js : REST call functions to retrieve data using OpenMRS API.
VisualizeDataElements.js : contains algorithms that visualize data gotten in a timeline.
/css : contains different CSS Files
/fancybox : JQuery Fancybox plugin
/fonts : contains fonts files.
...
Test: Cholesterol / Blood Glucose /Lipid Panel /Triglyceride/LDL/HDL
Date :
Document : #Link
- Status : Good / Normal / Low
...
9.Medical Images Timeline:
- Name :
- Date :
- Provider :
- IMAGES :
Sketching Up the Timeline :
We worked to make the user experience meet the exact needs of the patient, without any fuss or bother, we developed a timeline to make the information access faster and visualizing different medical data easier.
We preferred to make “One Side” timeline to make the UI scalable in the both browser or on Smart Devices .
[IMAGE 1]: Sketching the UI on Paper
Building Openmrs REST call :
...
Then we started getting different data elements by consuming data from Raxa Server
OPENMRS_REST_HOST = 'http://raxaemr.elasticbeanstalk.com';
We consume data by using REST calls, for example : if we want fetching observation resource
var REST_OBS = '/ws/rest/v1/obs?patient=65ea509b-1f90-461f-9879-62004cc8a3b6';
More information about the consumed Data : https://raxaemr.atlassian.net/wiki/display/RAXAJSS/Raxacore+REST+resources
Once we get data using OpenMRS Rest call, we built JavaScript Script to visualize these data after classifying it in a timeline .
Mentors :
Acknowledgements :
This project is developed for Raxa , as part of Google Summer of Code Program.