Background:

This guideline provides an overview of how to design and implement a REST API interface for querying patient demographic data from an Electronic Patient Record (EPR) system using HealthConnect. The process involves sending a query request with the patient's identification number, retrieving the response from the EPR system, extracting the required patient demographic data from the HL7 message, and sending it as a JSON response to the supplier. The high-level process diagram is shown below (Screenshot 1).

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Hi Community,

This is my first post in the developer community - would appreciate any feedback!

For testing or demo purposes, you may want to send emails from your Interoperability Production. In this post then I will walk you through connecting an InterSystems IRIS Production to Gmail so you can use it to send emails alerts.

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Article
· Mar 3, 2021 4m read
Access to IRIS from Rust

What do you think If I will say you, that very soon you will be able to connect to IRIS from the application written in Rust.

What is Rust

Rust is a multi-paradigm programming language designed for performance and safety, especially safe concurrency. Rust is syntactically similar to C++, but can guarantee memory safety by using a borrow checker to validate references. Rust achieves memory safety without garbage collection, and reference counting is optional. (c) Wikipedia

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Hi Developers,

Python has a large and powerful ecosystem that contains thousands of libraries and packages available, especially in data science.

Therefore, I wanted to have a first try in using a recent feature of IRIS called Embedded Python, to simply import a python library called datetime, generate data with a timestamp component and persist it in InterSystems IRIS for Health Data Platform. The same will work on IRIS Data Platform as well.

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When creating custom Business Hosts, it's often necessary to add properties to the class for additional settings that will be used in the initialization or operation of the host. The property name itself isn't always very descriptive, so it's an advantage to have a custom caption display with the field.

In Caché, it was fairly straightforward:

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Article
· Jan 13, 2022 4m read
How to find the dataset you need?

Hey community! How are you doing?

I hope to find everyone well, and a happy 2022 to all of you!

Over the years, I've been working on a lot of different projects, and I've been able to find a lot of interesting data.

But, most of the time, the dataset that I used to work with was the customer data. When I started to join the contest in the past couple of years, I began to look for specific web datasets.

I've curated a few data by myself, but I was thinking, "This dataset is enough to help others?"

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Article
· Apr 25, 2023 12m read
Configuring Mirror in Docker

A common need for our customers is to configure both HealthShare HealthConnect and IRIS in high availability mode.

It's common for other integration engines on the market to be advertised as having "high availability" configurations, but that's not really true. In general, these solutions work with external databases and therefore, if these are not configured in high availability, when a database crash occurs or the connection to it is lost, the entire integration tool it becomes unusable.

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++Update: August 2, 2018

This article provides a reference architecture as a sample for providing robust performing and highly available applications based on InterSystems Technologies that are applicable to Caché, Ensemble, HealthShare, TrakCare, and associated embedded technologies such as DeepSee, iKnow, Zen and Zen Mojo.

Azure has two different deployment models for creating and working with resources: Azure Classic and Azure Resource Manager. The information detailed in this article is based on the Azure Resource Manager model (ARM).

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Article
· Nov 29, 2022 6m read
What's HL7v2?!

HL7 (Health Level 7) is a set of technical specifications for computerized exchanges of clinical, financial and administrative data between hospital information systems (HIS). These specifications are variously integrated into the corpus of formal American (ANSI) and international (ISO) standards.

The L7 of HL7 indicates that it is a standard that operates at layer 7, in other words at the application layer, of the OSI model. This means that HL7 does not have to take into account exchange security considerations, or those of message transport (this being ensured by lower-level layers such as SSL/TLS for security or TCP for the transport of data for example). To be more precise, layer 7 supports communications for end-user processes and applications and the presentation of data for user-facing software applications. As the highest layer of the OSI model, and the closest to the end user, layer 7 provides application-specific functions such as identifying communication partners and the quality of service between them, determining resource availability, considering privacy and user authentication, and synchronizing communication, as well as connecting the application to the lower levels of the OSI model.

Returning to the HL7 standard, the HL7 version 2 standard (also known as Pipehat) was originally created in 1989 but is still being used and updated regularly, resulting in versions 2.1, 2.2, 2.3, 2.3.1, 2.4, 2.5, 2.5.1, 2.6, 2.7, 2.7.1, 2.8, 2.8.1, 2.8.2 and 2.9. The v2.x standards are backward compatible (e.g., a message based on version 2.3 will be understood by an application that supports version 2.6) and in higher versions, you will see some fields are left just for it.

Despite it being more than 30 years old, HL7v2 remains the most widely used healthcare interface standard by a large margin according to the HL7.org portal that tells that:

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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 "?".

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Introduction

We are in the age of the multiplatform economy and APIs are the "glue" in this digital scenario. Since they are so important, they are seen by developers as a service or product to be consumed. Therefore, usage experience is a crucial factor for its success.

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FHIR has revolutionized the healthcare industry by providing a standardized data model for building healthcare applications and promoting data exchange between different healthcare systems. As the FHIR standard is based on modern API-driven approaches, making it more accessible to mobile and web developers. However, interacting with FHIR APIs can still be challenging especially when it comes to querying data using natural language.

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Article
· Jun 19, 2020 5m read
Migrate from Java Business Host to PEX

Migrate from Java Business Host to PEX

With the release PEX in InterSystems IRIS 2020.1 and InterSystems IRIS for Health 2020.1, customers have a better way to build Java into productions than the Java Business Host. PEX provides a complete set of APIs for building interoperability components and is available in both Java and .NET. The Java Business Host has been deprecated and will be retired in a future release.

Advantages of PEX

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Article
· Aug 28, 2023 3m read
IKO & The Compatibility Version Gotcha

With the world (as well as our own technology) moving to the cloud at such a fast pace it is easy (at least for myself) to get caught up in the little details. One thing I, and some clients of ours, had run into a couple of times was the necessity to specify the version of the images one plans to use with the IKO.

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We resume our series of articles on the FHIR Adapter tool available to HealthShare HealthConnect and InterSystems IRIS users.

In the previous articles we have presented the small application on which we set up our workshop and showed the architecture deployed in our IRIS instance after installing the FHIR Adapter. In today's article we will see an example of how we can perform one of the most common CRUD (Create - Read - Update - Delete) operations, the reading operation, and we will do it by recovering a Resource.

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ChatIRIS Health Coach, a GPT-4 based agent that leverages the Health Belief Model (Hochbaum, Rosenstock, & Kegels, 1952) as a psychological framework to craft empathetic replies.

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image

This article will cover turning over control of provisioning the InterSystems Kubernetes Operator, and starting your journey managing your own "Cloud" of InterSystems Solutions through Git Ops practices. This deployment pattern is also the fulfillment path for the PID^TOO||| FHIR Breathing Identity Resolution Engine.

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