Week Two: Progress and Insights

In the second week of my GSoC project, I've delved deeper into integrating OpenELIS with a FHIR-based open client registry. My primary focus has been on enhancing the user interface and improving the dictionary menu functionalities, as well as understanding the FHIR layer within OpenELIS. Here's a detailed look at my progress and learnings this week.

UI Enhancements and REST Controllers for the Dictionary Menu

This week, I tackled several issues to fully translate the dictionary menu into the new UI and RESTful services. The dictionary menu in OpenELIS is crucial for managing various entities and configurations. Here’s a breakdown of the tasks I completed:

Modification of Dictionary Menu

I successfully implemented the feature for modifying the dictionary menu items. This involved creating a dynamic interface where users can add, edit, and delete dictionary entries seamlessly. The new interface is more intuitive and responsive, making it easier for users to navigate and update the dictionary data.

Search Functionality Implementation

I also worked on the search functionality within the dictionary menu. This feature enables users to quickly find specific dictionary entries using keywords or phrases. By leveraging REST controllers, the search process is now efficient and returns results in real-time, significantly improving user experience.

Understanding the FHIR Layer of OpenELIS

As part of my project, I dedicated time to understanding the FHIR (Fast Healthcare Interoperability Resources) layer within OpenELIS. FHIR is essential for standardizing the exchange of healthcare information, and integrating it with OpenELIS is a key goal of this project. Here are some key insights:

Patient-to-FHIR Object Translation

I explored how patients in OpenELIS are translated into FHIR objects. This translation process is critical because it ensures that patient data is formatted and standardized according to FHIR specifications, making it interoperable with other healthcare systems.

Utilizing Existing Functionality for Patient Data Transmission

I studied how to utilize the existing functionality in OpenELIS to send the created patient data to OpenHIM (Open Health Information Mediator) once an event is triggered. This involves understanding the event-driven architecture in OpenELIS and how patient data is packaged and transmitted as a FHIR object to external systems through OpenHIM. This knowledge is pivotal for achieving seamless integration and data exchange between OpenELIS and the FHIR-based client registry.

This week has been immensely productive and insightful, laying a solid foundation for the subsequent phases of my project. I am looking forward to further refining these functionalities and ensuring robust integration between OpenELIS and the FHIR-based client registry.

List of Pull requests i worked on:

• Implement Search Functionality on DIctionary Menu
• Fix browser console errors in the ui
• Fix modification of a dictionary menu item
• Fix Barcode configuration

Stay tuned for more updates as the project progresses! Thank you for following along on my GSoC journey! Your support and feedback are greatly appreciated.

Week One: Kicking Off the GSoC Project with OpenCR | GSoC'24

 

Embarking on my Google Summer of Code (GSoC) journey, I've laid the groundwork for a project aimed at integrating OpenELIS with a FHIR-based Open Client Registry. Here's a recap of the first week and the initial steps I've taken.

Setting Up the Trello Board

To ensure organized progress tracking and issue management throughout this project, I created a Trello board. This board will serve as a hub for all tasks, issues, and milestones, facilitating efficient workflow and collaboration. You can follow along with the board here.

Transforming Match Results into FHIR Bundle Objects

The primary task I tackled this week involved transforming match results returned by Open Client Registry (OpenCR) into a FHIR Bundle object. This task is crucial as it sets the foundation for seamless data exchange and interoperability between OpenELIS and the client registry.

Pull Request Overview

I made significant progress by submitting a pull request, which is currently under review. This PR encapsulates the initial implementation of the transformation process.

Technical Approach

To achieve this transformation, I followed a structured approach involving two main functions: getPatientById and transformToFhirObject. 

The getPatientById function is responsible for fetching patient data from the FHIR server based on an array of match results. Here’s a detailed breakdown of how it works:  For each match result, the function creates a promise to fetch the corresponding patient data using the fhirWrapper.getResource method.  If the patient data contains any links, the function adjusts the URLs to ensure they conform to the required format. It appends a `search` object to the patient data, which includes the match-grade and score.The function resolves the promise with the patient data or rejects it if an error occurs during fetching.

The transformToFhirObject function handles the creation of a FHIR Bundle object by combining the fetched patient data.It first calls `getPatientById` for both "auto" and "potential" match results, fetching patient data with appropriate scores and match grades.  The fetched patient data is then combined into a single array.  A FHIR Bundle object is constructed with the combined entries, setting the `resourceType` to "Bundle", generating a unique ID, setting metadata with the current timestamp, specifying the bundle type as "searchset", and setting the total number of entries. The function logs the results and returns the combined FHIR Bundle.

Moving Forward

With the first week successfully behind me, I am eagerly looking forward to the upcoming challenges and learning opportunities. The next steps will involve refining the current implementation based on review feedback, addressing any issues that arise, and diving deeper into the integration process.

Stay tuned for more updates as I continue this exciting journey of integrating OpenELIS with a FHIR-based Open Client Registry.