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#HL7

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Health Level-7 or HL7 refers to a set of international standards for the transfer of clinical and administrative data between software applications used by various healthcare providers

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Article
· Oct 17, 2024 2m read
ORU to MDM with large HL7 v2 messages.

I was working on a DTL but kept getting ERROR #5002... MAXSTRING errors. The problem was that most of the DTL GUI action steps only support the string data type when working with the segments. A %String has a limit of 3,641,144 characters and my OBX5.1 was 5,242,952 characters long as the example provided. Of course PACS admin stated ultra high quality up to and including 4K resolution files were needed, so we could not get the vendor to compress or reformat these files to compressed jpg or something similar.

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Two fairly common requests we receive from HL7 customers are (1) how to remove all trailing delimiters for fields and segments in HL7 messages and (2) how to "find and replace" for an entire HL7 message (as opposed to one segment/field at a time). The code sample below shows a custom function that solves for item 1 and by extension item 2 above. In other words the same approach can be used for finding/replacing any sequence of chars in an entire HL7 message, with some tweaks to the custom function.

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DTL Transformations and GetValueAt/SetValueAt calls on HL7 messages will truncate any fields longer than 32K. To avoid this, the methods GetFieldStreamRaw and StoreFieldStreamRaw must be used when dealing with fields that might be larger than 32K. OBX:5 is a frequent example. These methods have some subtleties and must be used carefully.

This can't be done by simply dragging from left to right in a DTL. It must be done with a code action. Also, the StoreFieldStreamRaw call must be the last edit made to the segment because the segment becomes immutable after that.

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I'm always on the lookout for tools that make the development and testing of my interfaces more efficient. A couple of years ago I came across HL7 Spy, from Inner Harbour Software. It quickly became my go-to tool for running message comparison reports for interface engine migrations, message statistics gathering, and troubleshooting message receipt and delivery. It also offered enhanced functionality for things like fetching messages via sftp that other tools don't provide.

I've recently been working with HL7 Spy's author, Jon Reis, to enable support for fetching messages directly from the Ensemble message store. Its SQL Loader feature now has native Caché/IRIS support, and I've contributed a small server-side class to support the extraction of messages using it.

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InterSystems and Intel recently conducted a series of benchmarks combining InterSystems IRIS with 2nd Generation Intel® Xeon® Scalable Processors, also known as “Cascade Lake”, and Intel® Optane™ DC Persistent Memory (DCPMM). The goals of these benchmarks are to demonstrate the performance and scalability capabilities of InterSystems IRIS with Intel’s latest server technologies in various workload settings and server configurations. Along with various benchmark results, three different use-cases of Intel DCPMM with InterSystems IRIS are provided in this report.

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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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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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This article will describe and include an example of how to embed an external PDF file into an HL7 segment, specifically ADT_A01:2.3.1 OBX(). This can be useful when attempting to insert pictures or other external data into an HL7 message. In this example, the name of the PDF file to be embedded is provided in the incoming HL7 message in OBX(1):ObservationValue field.

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Fun or No Fun - how serious is it?


Large language models are stirring up some phenomena in recent months. So inevitably I was playing ChatGPT too over last weekend, to probe whether it would be a complimentary to some BERT based "traditional" AI chatbots I was knocking up, or rather would it simply sweep them away.

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Introduction

InterSystems has recently completed a performance and scalability benchmark of IRIS for Health 2020.1, focusing on HL7 version 2 interoperability. This article describes the observed throughput for various workloads, and also provides general configuration and sizing guidelines for systems where IRIS for Health is used as an interoperability engine for HL7v2 messaging.

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Introduction

This article aims to explore how the FHIR-PEX system operates and was developed, leveraging the capabilities of InterSystems IRIS.

Streamlining the identification and processing of medical examinations in clinical diagnostic centers, our system aims to enhance the efficiency and accuracy of healthcare workflows. By integrating FHIR standards with InterSystems IRIS database Java-PEX, the system help healthcare professionals with validation and routing capabilities, ultimately contributing to improved decision-making and patient care.

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(Originally posted by @Ben Spead on June 25, 2014)

This code snippet generates a list of Ensemble Lookup Tables and Schema documents in the user's current namespace. Run the code by running the class method "test":


Class benspead.EnsTablesSchema
{
    classmethod test() {
        If ##class(%Dictionary.CompiledClass).%ExistsId("Ens.Util.LookupTableDocument") {
            // only supported in Ensemble 2012.1+
            Write !,!,"Exporting Ensemble Lookup Tables..."
            Set sc = $$$OK
            Set rs = ##class(%ResultSet).%New("Ens.Util.LookupTableDocument:List")
            Do rs.Execute()
            While rs.Next() {
                Set item=rs.Data("name")
                Write "document found: "_ item,!
            }
            Do rs.Close()
            Set rs=""
        }
        If ##class(%Dictionary.CompiledClass).%ExistsId("EnsLib.HL7.SchemaDocument") {
            Write !,!,"Exporting Ensemble HL7 Schemas..."
            Set sc = $$$OK
            Set rs = ##class(%ResultSet).%New("EnsLib.HL7.SchemaDocument:List")
            Do rs.Execute()
            While rs.Next() {
                Set item=rs.Data("name")
                Continue:$listfind($lb("2.1.HL7","2.2.HL7","2.3.HL7","2.4.HL7","2.5.HL7","2.6.HL7","2.7.HL7","2.3.1.HL7","2.5.1.HL7","2.7.1.HL7","ITK.HL7")
                                    ,item)
                Write "document found: "_ item,!
            }
            Do rs.Close()
            Set rs=""
        }
    }
}

Here's a link to the code on GitHub: https://github.com/intersystems-community/code-snippets/blob/master/src/...

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Your Mission

Let's pretend for a moment that you're an international action spy who's dedicated your life to keeping the people of the world safe from danger. You recieve the following mission:

Good day, Agent IRIS,

We're sorry for interrupting your vacation in the Bahamas, but we just received word from our London agent that a "time bomb" is set to detonate in a highly populated area in Los Angeles. Our sources say that the "time bomb" is set to trigger at 3:14 PM this afternoon.

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Introduction

Say you have a receiving system that accepts HL7 and provides error messages in field ERR:3.9 in the ACK it returns. You require a different reply code action depending on the error message, however the Reply Code Actions settings for the operation do not provide this level of granularity. One option could be to create a process that takes the ACK and then completes the action you were expecting, however things can get a bit messy if the action is to retry the message, especially when trying to view a message trace.

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Hi Community,

In this article, I will introduce my application iris-fhir-bridge

IRIS-FHIR-Bridge is a robust interoperability engine built on InterSystems IRIS for Health, designed to transform healthcare data across multiple formats into FHIR and vice versa. It leverages the InterSystems FHIR Object Model (HS.FHIRModel.R4.*) to enable smooth data standardization and exchange across modern and legacy healthcare systems.

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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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Do you ever spend an age entering criteria in the message viewer page, trying to find a message just to realise you're in the wrong instance of IRIS?

Or get lost in a sea of message tabs struggling to spot that Visual Trace page your were JUST looking at?

Well, have you tried the IRIS WHIZ browser extension and its suite of tools designed to help you avoid such unpleasantness?

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In this article we are going to see how we can use the WhatsApp instant messaging service from InterSystems IRIS to send messages to different recipients. To do this we must create and configure an account in Meta and configure a Business Operation to send the messages we want.

Let's look at each of these steps in more detail.

Setting up an account on Meta

This is possibly the most complicated point of the entire configuration, since we will have to configure a series of accounts until we can have the messaging functionality.

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EnsLib.HL7.Message.cls provides many API methods for manipulating an HL7 message. RemoveSegmentAt(), for example, can be used to remove a segment by path or index, but only one segment at a time. There may be times that you'll need to remove all segments within a group or even many groups of segments from the HL7 message. Surely you can iterate through each segment in each group and remove them one by one, but there's a much easier way.

With just one command, like below, you can remove all OBX segments in an ORU_R01 message (msg):

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One of the pain points for maintaining HL7 interfaces is the need to run a reliable regression test upon deployment to new environments and after upgrades. The %UnitTest class allows unit tests to be created and packaged alongside interface code. Test data can also be maintained within the unit test class, allowing for quick and easily repeatable smoke-testing and regression testing.

Resources:

  • Standard %UnitTest class

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In the previous article, we've discussed the origin of the standard HL7v2, the structure and the types of messages. Let's now look at one of the most used types of messages and an example of its structure. I'm talking about ADT.

HL7 ADT messages (Admit, Discharge, Transfer) are used to communicate basic patient information, visit information and patient state at a healthcare facility. ADT messages are one of the most widely-used and high volume HL7 message types, as it provides information for many trigger events including patient admissions, registrations, cancellations, updates, discharges, patient data merges, etc.

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Because I had no idea how to build an integration solution for HL7 and didn't know where to start, I decided to follow the course Building Basic HL7 Integrations with InterSystems on Learning portal to get at least the idea of where to begin. After I studied all of it, I decided it might be a good idea to share my thoughts and reflections about it with everyone.

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High-Performance Message Searching in Health Connect

The Problem

Have you ever tried to do a search in Message Viewer on a busy interface and had the query time out? This can become quite a problem as the amount of data increases. For context, the instance of Health Connect I am working with does roughly 155 million Message Headers per day with 21 day message retention. To try and help with search performance, we extended the built-in SearchTable with commonly used fields in hopes that indexing these fields would result in faster query times. Despite this, we still couldn't get some of these queries to finish at all.

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