Newsbytes

Regenstrief and SNOMED kick off terminology initiative

The Regenstrief Institute and SNOMED International have commenced their initiative under which they will generate the LOINC Ontology, standardized terminology to drive broader health data interoperability globally.

The ontology is intended to support providers and other users who implement different combinations of Systematized Nomenclature of Medicine Clinical Terms and Logical Observation Identifiers Names and Codes in health information systems by allowing them to meet clinical and regulatory requirements in a single solution. “Linked together in a complementary way, SNOMED CT provides the computable framework and LOINC provides laboratory and pathology content in an [understandable] format to countries who do not currently use LOINC,” according to a Regenstrief press release.

The LOINC Ontology, which is owned by Regenstrief, will be made available without charge under the current royalty-free LOINC license. SNOMED International members and users will be able to work with LOINC in the same format they use for SNOMED CT.

Each organization retains editorial control of its respective standard.

At CAP TODAY press time, more than 24,000 terms had been included in the LOINC Ontology preview, which was slated to be published for review and feedback by the end of 2023.

MTuitive releases solution for aggregating oncology data

MTuitive has introduced mTuitive Insight, a database that consolidates structured oncology data from any integrated lab information system or EHR.

The solution can be used to accrue, share, present, and analyze standardized data of value to pathology, oncology, surgery, research, and quality control.

MTuitive Insight uses structured data captured via synoptic reporting. The system also employs standard, purpose-built reports to measure performance against standard quality metrics.

MTuitive can build custom query functionality and custom dashboards for the solution that are centered on patient information, tissue, images, and other data useful to research and patient care.

“MTuitive Insight exports data to all major business intelligence platforms, complements existing enterprise data warehouse strategies, extends the use of current solutions, and is intuitive to use, even for nontechnical users,” according to a company press release.

mTuitive, 508-771-5800

Microsoft introduces health care AI tools

Microsoft has launched a series of analytics and artificial intelligence offerings as part of its Microsoft Fabric data analytics platform and Azure AI services.

The company has developed health care data and analytics tools, available in preview capacity within the Microsoft Fabric platform, that allow health care entities to combine data from previously siloed sources across their organization, including laboratory information systems, EHRs, picture archiving and communication systems, claims systems, and medical devices.

“The [Fabric] solution brings structured, unstructured, imaging, and medical device data into the Fabric data lake with open data standards using FHIR [Fast Healthcare Interoperability Resources], DICOM [Digital Imaging and Communications in Medicine], and MedTech services, providing customers with one common architecture,” according to a Microsoft blog post.

A new service for the Fabric platform will also allow organizations to de-identify patient data using machine-learning models that extract, redact, or surrogate identifiers before extracting information from unstructured data, such as doctors’ notes.

Among the new tools for Microsoft’s Azure AI services are Azure AI Health Insights, Azure AI Health Bot, and Text Analytics for health.

Azure AI Health Insights provides prebuilt models for performing analyses and providing inferences that can be used by clinicians and researchers to facilitate patient care. The models, being launched in preview, are patient timeline, which extracts information from unstructured data to create a chronological overview of a patient’s medical history; clinical report simplification, which converts medical jargon into simplified text while preserving the essence of the clinical information; and radiology insights, which provides quality checks through feedback on errors and inconsistencies across reports and identifies follow-up recommendations and findings within clinical documentation.

The generative AI-based Azure AI Health Bot can pull data from within a health organization and external sources, such as the FDA and National Institutes of Health, to provide users with information on treating disease and handling protocols and processes.

Text Analytics for health uses machine-learning intelligence to label medical information and extract it from a variety of unstructured data sources, such as clinical documents and notes. Microsoft plans to offer the tool not only in English but also Spanish, French, Italian, German, Portuguese, and Hebrew.

Dr. Aller practices clinical informatics in Southern California. He can be reached at rayaller@gmail.com. Dennis Winsten is founder of Dennis Winsten & Associates, Healthcare Systems Consultants. He can be reached at dennis.winsten@gmail.com.