I recently published the "appmsw-docbook" module for deploying the solution not by individual programs, but by the entire database. This solution allows you to deploy a project without source codes.

Having received feedback, I decided to improve it significantly. Replaced zip archive with tgz, which will allow not using external system-dependent archivers.

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I have just created a new Global Master Topic, "IRIS Cheatsheets". IRIS has introduced a lot of new functionality, especially in scripting languages, FHIR R4 support, enhanced Interoperability Tools, and IRIS Analytics. Having spent 35 years working on Windows-based PC's and Laptops, I have surprisingly little knowledge of Linux, Docker and Git. Furthermore, I have written almost every application and Interface in ObjectScript with splatterings of SQL, .Net, and Java Gateways and the most basic knowledge of WinSCP, Putty, SSH. All that changed when I received my first Raspberry Pi.

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In this article I will demonstrate the following :

  • Update ReferencesRange(OBX:7) against ObservationIdentifier(OBX:3.1)[TestCode] from database by using custom utility function
  • Update Abnormal Flag(OBX:8) against ObservationIdentifier(OBX:3.1)[TestCode]  and ObservationValue(OBX:5)[Result] from database utility function
  • Route Message based on Abnormal Flag(OBX:8)

Below is the primary and transformed HL7 2.5 ORU_R01 message:

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I'd like to share with you some storage features that also exist in Caché but are almost 
unknown and mostly not used. They are of course available in IRIS and gain importance
with large and distributed storage architectures.

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I have attached a document that describes the product I have developed called NiPaRobotica Pharmacy. This is an interface I developed that accepts Pharmacy Dispense Requests and converts the line items on the order into dispense dialogues which it sends to pharmacy robots. I deployed the interface into 3 Hospital pharmacies two of which had 6 robots that were arranged in such a way that the dispense chutes channelled medications to desks by the pharmacists sitting in windows serving 1200 patients a day. The robots cut the average waiting time from 2 hours down to one hour.

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Continuing the description of work on the use of the openhl python module in productive mode.

Since the version of iris with Embedded Python, does not yet have a final release, it is already necessary to use it in production now. We decided to back up the service for exporting requests to a xlsx file on a separate server, and save the query result in a global in a separate database.

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Healthcare interoperability is instrumental in improving patient care, decreasing healthcare provider costs, and providing a more accurate picture to providers. However, with so many different systems, data is formatted in many different ways. There are many standards that have been created to try to solve this problem, including HL7v2, HL7v3, and CDA but each one has its drawbacks.

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InterSystems SAM is a great tool to monitor your InterSystems IRIS and InterSystems IRIS For Health clusters on prem or in a cloud environment. This article describes how you can implement a customized alert handler. This is currently an undocumented and most likely an unknown feature of InterSystems SAM. With future releases it will be probably made easier to leverage this useful concept.

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This is a demo to make use of a simple WebSocket Client with Embedded Python in IRIS.

To continue my series of WebSocket Client I have added an example written in Python.
The most impressive experience was how easy the writing and testing of the client was
which happened total offline from IRIS.
Embedding, running and feeding the client with data from IRIS was also incredibly simple.

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Google has one intersting tool named Data Studio. This tool allows creating some interactive dashboards, based on your data, available from the internet. It already offers hundreds of connectors to any sort of data developed by the community. As well as some amount of community developed visualizing. And most importantly, Google offers a way to develop your own connector to your data. 

FHIRaaS provides a REST API, and it's available from the internet. So I've decided to try to create some basic report on data stored there. And in the end, I got this.

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In the first article, a simple tutorial was help you to set up your FHIRaaS deployment.

Now, let's move forward and introduce a JS library to access the FHIR resource.

In the end, two examples of usage of this library will be presented, exploring the Appointment FHIR resource type.

SMART on FHIR JavaScript Library

FHIR is a REST API, so you can use any HTTP client in order to use it. But, it’s always a good idea to have help.

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José Roberto Pereira · Jun 5 8m read
FHIRaaS overview


This article aims to provide an overview of InterSystems IRIS FHIR Accelerator Service (FHIRaaS) driven by the implementation of application iris-on-fhir, available in OEX developed for the FHIRaaS contest.

A basic tutorial will guide you in configuring a function FHIRaaS deployment, including an API key and an OAuth 2.0 server.

A library to use FHIR resources through FHIRaaS also is briefly discussed.

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Like hardware hosts, virtual hosts in public and private clouds can develop resource bottlenecks as workloads increase. If you are using and managing InterSystems IRIS instances deployed in public or private clouds, you may have encountered a situation in which addressing performance or other issues requires increasing the capacity of an instance's host (that is, vertically scaling).

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