In healthcare,interoperability is the ability of different information technology systems and software applications to communicate, exchange data, and use the information that has been exchanged.
ChatIRIS Health Coach, a GPT-4 based agent that leverages the Health Belief Model as a psychological framework to craft empathetic replies. This article elaborates on the backend architecture and its components, focusing on how InterSystems IRIS supports the system's functionality.
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.
The OpenAPI Specification (OAS) defines a standard, language-agnostic interface to HTTP APIs which allows both humans and computers to discover and understand the capabilities of the service without access to source code, documentation, or through network traffic inspection. When properly defined, a consumer can understand and interact with the remote service with a minimal amount of implementation logic. While for SOAP based APIs there is a special wizard in InterSystems IRIS that cuts down orchestrations development time, not all APIs used in integrations are SOAP. That's why @Jaime Lerga suggested to add a wizard similar to the SOAP wizard to generate a REST client from OpenAPI specification. Implementation of this idea cuts down the development time of the REST API orchestrations with InterSystems IRIS. This idea is one of most popular ideas on the InterSystems ideas. This article, the third in the "Implemented Ideas" series, focuses on the OpenAPI Suite solution developed by @Lorenzo Scalese.
The InterSystems IRIS has a series of facilitators to capture, persist, interoperate, and generate analytical information from data in XML format. This article will demonstrate how to do the following:
Capture XML (via a file in our example);
Process the data captured in interoperability;
Persist XML in persistent entities/tables;
Create analytical views for the captured XML data.
Capture XML data
The InterSystems IRIS has many built-in adapters to capture data, including the next ones:
I recently had the need to monitor from HealthConnect the records present in a NoSQL database in the Cloud, more specifically Cloud Firestore, deployed in Firebase. With a quick glance I could see how easy it would be to create an ad-hoc Adapter to make the connection taking advantage of the capabilities of Embedded Python, so I got to work.
There is a Link Procedure Wizard option within the Management Portal (System > SQL >Wizards > Link Procedure) which I had reliability issues with so I decided to use this solution instead.
Record maps are used to efficiently map files containing delimited records or fixed-width records to message classes used by the interoperability function, and to map files from interoperability function message classes to text files.
Record map mapping definitions can be created using the Management Portal, and we also provide a CSV record wizard that allows you to define while reading a CSV file.
Not so long ago, I came across the idea of using Python Class Definition Syntax to create IRIS classes on the InterSystems Ideas Portal. It caught my attention since integrating as many syntaxes as possible gives visibility to InterSystems’s products for programmers with experience in many languages.
All FHIR resources have a Meta element containing metadata about the resource. Some attributes are updated by the server, others are populated by the app constructing the resource.
In the context of HL7 FHIR (Fast Healthcare Interoperability Resources), the terms "id" and "identifier" refer to specific elements used for identifying resources within the FHIR data model. For a newbie, these terms can be confusingly similar, but they serve distinct purposes.
Look at the below Patient resource for August T. Faulkner:
The resource has an id of “1” — generated by the FHIR server when the resource was created. Patient August T. Faulkner also has a identifier (Medical Record Number) — possibly provided by the hospital — of 78510398960
Many organisations implement centralised log management systems to separate and centralise the log data in order to e.g. automate threat detection (and response) and to comply with regulatory requirements. The primary systems of interest are the various user facing applications, but increasingly also other kinds of systems including integration platforms.
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.
IRIS External Table is an InterSystems Community Open Source Project, that allows you to use files, stored in the local file system and cloud object storage such as AWS S3 as SQL Tables.
The motivation behind the InterLang project is rooted in the innovative integration of LangChain chatbot agents with the Fast Healthcare Interoperability Resources (FHIR) framework to revolutionize conversational social prescriptions in healthcare. This project aims to leverage the rich and standardized data available through FHIR, an emerging standard in healthcare data exchange, to inform and empower these advanced chatbot agents.
In our previous post, we discussed the motivation for developing a chatbot agent with access to FHIR resources. In this post, we will dive into the high-level design aspects of integrating a Streamlit-based chat interface with a Java SpringBoot backend, and enabling a LangChain agent with access to FHIR (Fast Healthcare Interoperability Resources) via APIs.
If you work with Productions, highlighting connections between Business Hosts is a very convenient feature, allowing developers to get a visual representation of a data flow.
This feature works by default with all system Business Hosts. If a user writes their own Business Services, Processes, or Operations, they must implement the OnGetConnections method for this functionality to work with their custom Business Hosts (or use Ens.DataType.ConfigName properties for connections). That said, the SMP shows only the first layer of connections of the selected Business Host. Sometimes, we need to get connections of connections recursively to build a complete data flow graph. Or we might need this connection information to check which downstream systems might be affected by a change upstream.
Customizing Stored Procedures with ObjectScript directly has been useful to access NoSQL storage and external messaging via integration, to present output in tabular format.
Wanted to share something I learned recently while working on a problem. We needed to add and change some Business Hosts in one of our edge productions.
In the past, we simply added the production class to CCR and then spreading it around. But there was a problem because different developers were working on different things, and we only wanted to include only the relevent production changes onto the CCR.
Here's a little piece of code that can help add new things to an existing production:
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 a fast-paced clinical environment, where quick decision-making is crucial, the lack of streamlined document storage and access systems poses several obstacles. While storage solutions for documents exist (e.g, FHIR), accessing and effectively searching for specific patient data within those documents meaningfully can be a significant challenge.
The Telegram Adapter for InterSystems IRIS serves as a bridge between the popular Telegram messaging platform and InterSystems IRIS, facilitating seamless communication and data exchange.
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