Project Overview:

The Clinical Staff Master Data Management (CSMDM) system is a full-stack healthcare integration application built on InterSystems IRIS for Health. It centralizes and standardizes clinical staff metadata into a single authoritative repository, exposed through RESTful CRUD APIs and reusable backend methods.

The platform eliminates fragmented lookup tables and hardcoded mappings that commonly cause errors in HL7 and FHIR integration workflows, ensuring data consistency and interface reliability.

Introduction

My guess is that most IRIS developers create their applications using its native ObjectScript language or, if using an external language, then most likely using either Java, Python or perhaps C++.

I suspect that only a minority have considered using JavaScript as their language of choice, which, if true, is a great shame, because, In my opinion and experience, JavaScript is the closest equivalent to ObjectScript in terms of its ability to integrate with the IRIS's underlying multi-dimensional database.

While working with external languages for IRIS (such as Python and Node.js), one of the first things you must accomplish is making a connection to an IRIS instance.

For instance, to make a connection in python (from https://pypi.org/project/intersystems-irispython/):

import iris

# Open a connection to the server
args = {
	'hostname':'127.0.0.1', 
	'port': 1972,
	'namespace':'USER', 
	'username':'username', 
	'password':'password'
}
conn = iris.connect(**args)

# Create an iris object
irispy = iris.createIRIS(conn)

# Create a global array in the USER namespace on the server
irispy.

Overview

The typeorm-iris project provides experimental support for integrating TypeORM with InterSystems IRIS, enabling developers to interact with IRIS using TypeORM’s well-known decorators and repository abstractions. This allows a more familiar development experience for JavaScript and TypeScript developers building Node.js applications with IRIS as the backend database.

While the project implements key integration points with TypeORM and supports basic entity operations, it’s not yet battle-tested or suitable for production environments.

Working in healthcare IT as a young developer, especially on InterSystems TrakCare, you quickly realize one thing: it’s not just about HL7 messages or backend integrations. A hugepart of making TrakCare work smoothly for hospitals comes down to how it’s configured, customized, and supported on the application side.

That’s where people like me come in—techno-functional developers who understand both the tech and how it impacts actual hospital workflows.

We’re Not Just Techies (or Functional Consultants)

Our role sits right in the middle.

For a long time I have wanted to learn the Django framework, but another more pressing project has always taken priority. Like many developers, I use python when it comes to machine learning, but when I first learned web programming PHP was still enjoying primacy, and so when it was time for me to pick up a new complicated framework for creating web applications to publish my machine learning work, I still turned to PHP.

Introduction

Managing databases and performing CRUD operations are fundamental tasks for developers building data-driven applications. While many database management systems (DBMS) exist, they can be complex and cumbersome to interact with, especially when it comes to creating databases and tables, handling constraints, and performing real-time data operations through an API.

This web-based Database Management Tool simplifies the entire process, offering an intuitive UI for managing databases and tables, alongside a powerful REST API for interacting with the data.

In this article, we’ll dive into the inner workings of the database management tool, exploring the architecture and technologies that power it. Understanding how the application functions behind the scenes will give you insight into its design, how it manages databases, tables, and how the API interacts with data.

We will discuss the core technologies used, including InterSystems IRIS as the primary database and Redis for caching. Additionally, we’ll break down the structure of the tables used and explain how the system handles data creation, retrieval, and manipulation through the REST API.

I received some really excellent feedback from a community member on my submission to the Python 2024 contest. I hope its okay if I repost it here:

you build a container more than 5 times the size of pure IRIS

and this takes time

container start is also slow but completes

backend is accessible as described

a production is hanging around

frontend reacts

I fail to understand what is intended to show

the explanation is meant for experts other than me

The submission is here: https://openexchange.intersystems.

Intro

Most server-client communication on the web is based on a request and response structure. The client sends a request to the server and the server responds to this request. The WebSocket protocol provides a two-way channel of communication between a server and client, allowing servers to send messages to clients without first receiving a request. For more information on the WebSocket protocol and its implementation in InterSystems IRIS, see the links below.

Developing a Full-Stack JavaScript web app with Caché requires you to bring together the right building blocks. In the previous part, we created a basic front-end React application. In the second part of this article series I will show how to choose the right back-end technology for your application. You will see Caché allows you to use many different approaches to link your front-end to your Caché server, depending on your application's needs. In this part we will set up a back-end with Node.js/QEWD and CSP/REST. In the next part we will enhance our basic web app and connect it to Caché using these technologies.

Previous post - Using AI to Simplify Clinical Documents Storage, Retrieval and Search

This post explores the potential of OpenAI's advanced language models to revolutionize healthcare through AI-powered transcription and summarization. We will delve into the process of leveraging OpenAI's cutting-edge APIs to convert audio recordings into written transcripts and employ natural language processing algorithms to extract crucial insights for generating concise summaries.

Idea sourced from InterSystems Ideas Portal

Previous Posts:

Using AI to Simplify Clinical Documents Storage, Retrieval, and Search

Doctor-Patient Conversations: AI-Powered Transcription and Summarization

Introduction

The healthcare industry is continuously evolving, and the need for efficient document management and patient data management is more critical than ever. In this article, we will focus on the specific aspects of integrating Google Docs and Google Sheets with FHIR data in the context of healthcare data interoperability.

Hi Community,

This article is a continuation of my article about  Getting to know Python Flask Web Framework   

In this article, we will cover the basics of topics listed below:

1. Routing in Flask Framework
2. Folder structure for a Flask app (Static and Template)
3. Getting and displaying data in the Flask application from IRIS.

So, let's begin.

Hi Community,
In this article I will demonstrate below steps to add Interactive map and visualize geographic data to web application:

• Step1 : Install Application
• Step2 : Create CSP Page
• Step3 : Extend dc.IrisGeoMap.Folium class
• Step4 : Invoke DrawGeoDetails() Method

So Let us start.
 

Step1 : Install Application

First of all we need to install iris-geo-map application by using ZPM

zpm "install iris-geo-map"

Hi Community
In this article, I will demonstrate the functionality of my app iris-geo-map
 

IRIS Geo Map application is a tool to visualize geographic data by generating interactive maps by using Embedded Python functionality. Application is using Folium Python library

folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the leaflet.js library. Manipulate your data in Python, then visualize it in on a Leaflet map via folium. folium makes it easy to visualize data that’s been manipulated in Python on an interactive leaflet map.

Hi everyone!

Just wanted to share here a quick post about my project for the Grand Prix :)

FHIR Patient Viewer is a single-page, reactive rendering tool built on Vue.js that displays in a human-friendly way the data returned from a /Patient/{id}/$everything call made to an InterSystems FHIR server. In the readme, I've included 3 main things: 1. A video demo connecting FHIR Patient Viewer to a sandbox IRIS FHIR server (the fastest way to test it); 2.

Hi, Community,

This post will demonstrate how to display data on the web by using Embedded Python , Python Flask Web Framework and Jquery datatable

We will display processes from %SYS.ProcessQuery table.

Step 1: Add table to HTML page and write below javascript code to display passed data from app.py :

HTML

  <table id="myTable" class="table table-bordered table-striped">                 
   </table>

Javascript

  <script>
    
$(document).ready(function() {
      // parse the data to local variable passed from app.py file
      let my_data = JSON.

This concept may be known to some, but I just found it very useful and I would like to share as it may help someone else.

If you are working with CSP or Zen you sometimes come across the need to use embedded JavaScript. Suppose you are working with some loops, which use < or > as shown in example below:

&js< 

               var test = document.getElementById('seTest');

               for (var i = 0; i < test.options.length; i++) {

                              // Do Something here with my test.options[i].

or "So you just got yelled at by your boss, for sending him an unformatted Hello World webpage"

Our previous lesson ended with us serving a Message value obtained from a Caché REST service to the client, using Angular as a runtime.  While there is a lot of moving parts involved in this process, the page is not especially exciting at the moment.  Before we can start adding new features, we should take a step back and review our tools.

This tutorial is using the JSON functionality built into 2016.2+ versions of Caché.  This functionality is partially available in 2016.

I wrote a step by step tutorial in the qewd-howtos repository how you can write state of the art multi-page web apps with Node.js using a QEWD-Up WebSocket/REST api back-end integrated with a mainstream web framework like NuxtJS & Vue.js. In particular with the latest NuxtJS/Vue.js frameworks, writing web applications becomes fun again, allowing you to write your applications very efficiently, hiding all boilerplate code from you.

The tutorial should be very easy to try out on your development machine and consists of two parts:

• instructions for creating a basic Node.

Hello everyone!

Me and @Henrique.GonçalvesDias proposed a new way to visualize messages in IRIS Interoperability in a recent update of MessageViewer. In such an update, we tried to give users a visualization based on a UML sequence diagram. You could get more information on the previous article.

In order to get all the hard geometry calculations needed to draw such a diagram done, we used the amazing mermaid JS open source library. And what I’d like to share with you in this article, is how to use this library.

Hi guys,

It's FHIR contest and this time, they provided something really cool: FHIRaaS

And to be part of this, @José Pereira and I team up (again) to deliver something easy to use and easy to understand how we did.

Developing a Full-Stack JavaScript web app with Caché requires you to bring together the right building blocks. Previously, I outlined the basic steps to install and connect Node.js to Caché and make it's powerful multi-model database capabilites available for use with Node.js. You can use Caché as a NoSQL-, document- (with unique key-level access!), SQL- and object-database with Node.js. When developing JavaScript applications, you'll see how powerful this combination is and makes Caché a perfect fit for Node.js.

In the first part of this article series I will show how to get started with the React framework, one of the most popular frameworks currently taking over front-end development. In the next parts you'll learn how to connect a basic web app to a Caché back-end.

You'll see, it's very easy to get started with this technology - you can even compare the amount of basic knowledge you need to COS because you only need to know a few basic concepts to start!

Those of you who are following the FullStack competition here in the Developer Community will know that I submitted an entry named qewd-conduit.  I wanted to summarise why I think it's something worth you taking a bit of time to check out.

qewd-conduit uses the Node.js-based QEWD framework alongside IRIS to implement the back-end REST APIs for something known as the RealWorld Conduit application:

https://github.

What is npm-iris? 

N.P.M stands for "No Project Mess."

N.P.M. is a Project & Task Management app that uses InterSystems IRIS and Bootstrap 4.

No Project Mess is created to help developers and small business companies to reduce complexity in their daily problems, with a simple and intuitive projects and tasks management software. 

It offers different views for your tasks, from a spreadsheet, kanban, calendar, or even Gantt!

So, one day you're working away at WidgetsDirect, the leading supplier of widget and widget accessories, when your boss asks you to develop the new customer facing portal to allow the client base to access the next generation of Widgets..... and he wants you to use Angular 1.x to read into the department's Caché server.   

There's only one problem:  You've never used Angular, and don't know how to make it talk to Caché.

This guide is going to walk through the process of setting up a full Angular stack which communicates with a Caché backend using JSON over

Whats NLP Stands For?

NLP stands for Natural Language Processing which is a field of Artificial Intelligence with a lot of complexity and techniques to in short words "understand what are you talking about".

And FHIR is...???

FHIR stands for Fast Healthcare Interoperability Resources and is a standard to data structures for healthcare. There are some good articles here explainig better how FHIR interact with Intersystems IRIS.

My Solution

Chatbot to query FHIR

The most common approach in chatbots is use machine learning to train the model based in old

Some time ago I got a WRC case transferred where a customer asks for the availability of a raw DEFLATE compression/decompression function built-in Caché.

When we talk about DEFLATE we need to talk about Zlib as well, since Zlib is the de-facto standard free compression/decompression library developed in the mid-90s.

Zlib works on particular DEFLATE compression/decompression algorithm and the idea of encapsulation within a wrapper (gzip, zlib, etc.).
https://en.wikipedia.