After we rolled out a new cointainer based on containers.intersystems.com/intersystems/irishealth:2023.1 this week, we suddenly noticed that our FHIR Repository started responding with an Error 500. This turns out to be caused by PROTECT violations on the new HSSYSLOCALTEMP namespace and database used by this version of the IRIS for Health FHIR components.
MonLBL is a tool for analyzing the performance of ObjectScript code execution line by line. codemonitor.MonLBL is a wrapper based on the %Monitor.System.LineByLine package from InterSystems IRIS, designed to collect precise metrics on the execution of routines, classes, or CSP pages.
The wrapper and all examples presented in this article are available in the following GitHub repository: iris-monlbl-example
We're excited to announce the first-ever UI update for CCR Client Tools. The Client Tools UI has been upgraded to match the modern CCR UI, aiming to create a more seamless experience across both applications. The color scheme, fonts, and style elements have all been updated accordingly in the new UI:
For 15 over years I have been playing with ways to speed up the way I use InterSystems systems and technology via AutoHotkey scripting. As a power keyboard user (I avoid my mouse when possible) I found it very helpful to set up hotkeys to get to my most frequently accessed systems and research utilities as quickly as possible. While I have used this approach for many years, this is the first time that I am introducing my approach and a customer-facing hotkey script to the D.C. and OEx...
Just like a knockout punch, without giving the opponent a chance, Kubernetes, as an open source platform, has a universe of opportunities due to its availability (i.e., the ease of finding support, services and tools). It is a platform that can manage jobs and services in containers, which greatly simplifies the configuration and automation of these processes.
But let's justify the title image and give the tool in question the “correct” name: InterSystems Kubernetes Operator.
Embedded Python has been around for a while. You probably followed the tutorials and learned about it. However, if you've tried to combine Python and ObjectScript in real development work, you probably ran into situations where you get an error message like this:
I'm sure most of you are familiar with utility %SYS.MONLBL that is crucial when analysing code performance bottlenecks. It allows you to select a number of routines that you want to monitor at runtime and also specify what process(es) you want to watch. BUT, what if you do not know exactly, what process would execute your code? This is true with many web based (CSP/REST) applications today. You want to minimize the resource utilization on your production system that needs analysis. So, how about doing a small tweak?
Hello! In this article, I will be discussing database degrade, a type of data integrity issue one can face when using IRIS. First, I will be going over a review of the structure of IRIS databases. I'll then discuss how database degrade can manifest and common causes of degrade issues. I'll then conclude with general tips we give our customers about how to prevent or prepare for database degrade issues.
Introducing Smart Clinical Sidechick — the intelligent, no-drama partner your EHR wishes it could be. She reads FHIR data in real time, interprets lab results without ghosting, and explains clinical alerts like she actually cares. Built with GPT-4 brains and YAML sass, she’s not here to replace your main EHR—just to make it look bad. Tired of irrelevant alerts and cryptic warnings? Sidechick serves up real, explainable insights, not vague “elevated risk” vibes. And when your backend crashes, she doesn’t panic—she self-heals.
Observing the avalanche of AI-driven and vibe-coding developer tools that have been appearing lately almost every month with more and more exciting dev features, I was puzzled whether it is possible to leverage it with InterSystems IRIS. At least to build a frontend. And the answer - yes! At least with the approach I followed.
Here is my recipe to prompt the UI vs InterSystems IRIS Backend:
Have the REST API on the IRIS side, which reflects some Open API (swagger) spec.
Generate the UI with any vibe-coding tool (e.g., Lovable) and point the UI to the REST API endpoint.
Profit!
Here is the result of my own exercise - a 100% prompted UI vs IRIS REST API that allows to list, create, update delete entries of a persistent class (Open Exchange,frontend source, video):
Regardless of whether an instance of IRIS is in the cloud or not, high availability and disaster recovery are always important considerations. While IKO already allows for the use of NodeSelectors to enforce the scheduling of IRISCluster nodes across multiple zones, multi-region k8s clusters are generally not recommended or even supported in the major CSP's managed Kubernetes solutions. However, when discussing HA and DR for IRIS, we may want to have an async member in a completely separate region, or even in a different cloud provider altogether.
Here at InterSystems, we often deal with massive datasets of structured data. It’s not uncommon to see customers with tables spanning >100 fields and >1 billion rows, each table totaling hundred of GB of data. Now imagine joining two or three of these tables together, with a schema that wasn’t optimized for this specific use case. Just for fun, let’s say you have 10 years worth of EMR data from 20 different hospitals across your state, and you’ve been tasked with finding….
It helps to remove special characters, such as non-utf-8 characters either control characters or unicode characters from text that is not printable or can't be parsed by downstream systems.
There is also $C(32) in this condition; sometimes NBSP appears in the text and it will not be recognized by TIE, but downstream it displays as "?".
An extension “extends” or enhances a FHIR resource or a data element in a custom way. The extension can be added to the root of a resource, such as “Patient.ethnicity” in US Core profile, and they can be added to individual elements such as HumanName, Address or Identifier.
Did you know that you can also add an extension to a primitive data type?
Primitives usually store a single item and are the most basic element in FHIR. For example: "Keren", false, 1234, 12/08/2024 etc.
For example, the patient resources might look like this:
RabbitMQ is a message broker that allows producers (those who send a data message) and consumers (those who receive a data message) to establish asynchronous, real-time, and high-performance massive data flows. RabbitMQ supports AMQP (Advanced Message Queuing Protocol), an open standard application layer protocol. The main reasons to employ RabbitMQ include the following:
You can improve the performance of the applications using an asynchronous approach.
It lets you decouple and reduce dependencies between services, microservices, and applications with the help of a data message mediator, meaning that there is no need for producers and consumers of exchanged data to know each other.
It allows the long-running processing of sent data (with the results) to be delivered after utilizing a response queue.
It helps you migrate from monolithic to microservices, where microservices exchange data via Rabbit in a decoupled and asynchronous way.
It offers reliability and resilience by making it possible for messages to be stored and forwarded. A message can be delivered multiple times until it is processed.
Message queueing is the key to scaling your application. As the workload increases, you will only have to add more workers to handle the queues faster.
If one of your packages on OEX receives a review you get notified by OEX only of YOUR own package. The rating reflects the experience of the reviewer with the status found at the time of review. It is kind of a snapshot and might have changed meanwhile. Reviews by other members of the community are marked by * in the last column.
One of the challenges of creating a DICOM message is how to implement putting data in the correct place. Part of it is by inserting the data in the specific DICOM tags, while the other is to insert binary data such as a picture - In this article I will explain both.
To create a DICOM message, you can either use the EnsLib.DICOM.File class (to create a DICOM file) or the EnsLib.DICOM.Document class (to create a message that can be sent to PACS directly). In either case, the SetValueAt method will allow you to add your data to the DICOM tags.
In a project I'm working on we need to store some arbitrary XML in the database. This XML does not have any corresponding class in IRIS, we just need to store it as a string (it's relatively small and can fit in a string). Since there are MANY (millions!) of records in the database I decided to reduce as much as possible the size without compressing. I know that some XML to be stored is indented, some not, it varies.
I recently had to refresh my knowledge of the HealthShare EMPI module and since I've been tinkering with IRIS's vector storage and search functionalities for a while I just had to add 1 + 1.
For those of you who are not familiar with EMPI functionality here's a little introduction:
Enterprise Master Patient Index
In general, all EMPIs work in a very similar way, ingesting information, normalizing it and comparing it with the data already present in their system. Well, in the case of HealthShare's EMPI, this process is known as NICE:
Sometimes customers need a small IRIS instance to do something in the cloud and shut it down, or they need hundreds of containers (i.e. one per end user or one per interface) with small workloads. This exercise came about to see how small an IRIS instance could be. For this exercise we focused on what is the smallest amount of memory we can configure for an IRIS instance.Do you know all the parameters that affect the memory allocated by IRIS ?
When working with InterSystems IRIS, database developers and architects often face a critical decision: whether to use Dynamic SQL or Embedded SQL for querying and updating data. Both methods have their unique strengths and use cases, but understanding their performance implications is essential to making the right choice. Response time, a key metric in evaluating application performance, can vary significantly depending on the SQL approach used. Dynamic SQL offers flexibility, as queries can be constructed and executed at runtime, making it ideal for scenarios with unpredictable or highly variable query needs. Conversely, Embedded SQL emphasizes stability and efficiency by integrating SQL code directly into application logic, offering optimized response times for predefined query patterns.
In this article, I will explore the response times when using these two types of SQL and how they depend on different class structures and usage of parameters. So to do this, I'm going to use the following classes from the diagram:
The first part of this article provides all the background information. It also includes links to the DATATYPE_SAMPLE database, which you can use to follow along with the examples.
In that section, we explored an error type ("Access Failure") that is easy to detect, as it immediately triggers a clear error message when attempting to read the data via the database driver.
I have a new project to store information from REST responses into an IRIS database. I’ll need to sync information from at least two dozen separate REST endpoints, which means creating nearly that many ObjectScript classes to store the results from those endpoints.
The %Library.DynamicObject class has been in IRIS since before it became IRIS. If you have been using it since the Cache days, you may want to brush up on some of its changes.
In Cache 2018, the %Get method only had one argument. It was the key to retrieving from the JSON, meaning that if your JSON object called myObj, it would look like the following:
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