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· 3 min read
Reshma Khilnani

Medplum’s Open-Source FHIRcast Hub Enables Rad AI Omni Reporting's Interactive Measurements​

Radiology is a bellwether for innovations in Healthcare IT due to the time-sensitive and data-intensive workflow. Naturally, radiology applications lead the way in adopting real-time functionality like FHIRcast, a WebSockets-based protocol that enables development of highly interactive applications.

Today, we are showcasing the Rad AI Omni Reporting platform, with FHIRcast support through Medplum’s open source FHIRcast hub.

How does it work?​

Let’s consider an example: a radiologist makes a tumor measurement from a PACS workstation; that measurement can be sent in real-time to the FHIRcast hub as an event. The event is then forwarded to the radiologist’s report editor, where a context-aware description is automatically filled in describing the tumor findings, all without the radiologist ever needing to touch another application or do dictation.

Why open source?​

Proprietary notification systems are a walled garden, and make it difficult or impossible to build highly ergonomic applications. An open-source FHIRcast hub is a foundational community asset, as developers and vendors can focus on building integrations rather than the plumbing. Open source provides a lot of flexibility for prototyping, testing and integrations across organizations.

Why FHIR?​

Integration is a thorny problem in healthcare overall, and the adoption of standards has been a key tool in allowing system interoperability. Specifically for FHIRcast, a reference implementation that partners can prototype against and use without restriction will increase quality and speed of integration.

Rad AI interactive reporting enabled by FHIRcast​

Rad AI Omni Reporting uses the Integrated Reporting Application (IRA) spec and Medplum’s open source FHIRcast hub to enable the rich, interactive application seen in the video.

Rad AI is excited to use open source FHIRcast for context syncing and data passing with our imaging and worklist partners. Having an open-source, standards-based FHIRcast hub lowers the barrier of entry for products to work together.

John Paulett Director of Engineering, Rad AI

About Rad AI​

Rad AI is the fastest-growing radiologist-led AI company. The company was recently listed on the CB Insights’ Digital Health 50 as one of the top privately-owned companies using digital technology to transform healthcare, Digital Health 150 as one of the most innovative digital health startups, and AI 100 as one of the world’s 100 most promising private AI companies. Rad AI won AuntMinnie’s “Best New Radiology Software” in 2023 for Omni Reporting and “Best New Radiology Vendor” in 2021. In 2022, Black Book ranked Rad AI #1 in Mean KPI score on its survey of 50 emerging solutions challenging the healthcare technology status quo.

Founded in 2018 by the youngest radiologist in U.S. history, Rad AI has seen rapid adoption of its AI platform and is already in use at 8 of the ten largest private radiology practices in the U.S. Rad AI uses state-of-the-art machine learning to streamline repetitive tasks for radiologists and automate workflow for health systems, which yields substantial time savings, alleviates burnout, and creates more time to focus on patient care.

· 3 min read
Reshma Khilnani

Those who have experienced the wait and shuffle of a specialist referral will appreciate the thoughtful and futuristic approach of the team at Titan Intake.

(5 minute demo)

Problem​

Continuity of care is broken because practices rely on fax and paper referral workflows to send patients to specialists. It is unrealistic to expect practices to change their systems, but patients need referrals and practices want to process them faster and capture all of the incoming clinical data without manual data entry.

Solution​

Titan provides a novel solution that leverages large language models (LLMs) to normalize unstructured referral data to FHIR, and gives practitioners and staff a button to synchronize data to their EHR (Cerner and others) via FHIR API. This saves manual work by staff and helps patients track the status of their referral. To lighten provider load, the Titan Intake app automatically synchronizes FHIR data to enable faster and more complete chart prepping.

In addition, as part of the intake process, Titan’s Natural Language Processing (NLP) engine detects and predicts the presence of Hierarchical Classification Codes and Elixhauser Comorbities to help both health systems and payors measure and receive reimbursement for the health of their patient populations. These are added to the FHIR Resources as CodableConcepts.

Medplum Solutions Used​

  • Enterprise Master Patient Index (EMPI) - As part of their EMPI implementation Titan checks and deduplicates patients, to prevent the fear of hospital IT - that an integration will introduce duplicates into their system and disturb their reporting and workflow.
  • Interoperability Service - From their web application, Titan triggers data synchronization into many downstream EHRs like Cerner, NextGen and others. This uses the Medplum integration engine a natively multi-tenant system that is very scalable and they serve many providers on the same technical stack.

Here is the full list of Medplum Solutions.

Challenges Faced​

  • Extracting data from documents/PDFs and structuring the data as FHIR is a very difficult technical problem. The team employs use of LLMs and modern artificial intelligence techniques to structure and tag the data with code systems.

  • Due to the nature of referrals, with a single patient being sent to many different institutions, duplicate Patient resources immediately become an issue. The team built a FHIR native Enterprise Master Patient Index and deduplication pipeline to support this use case.

  • Synchronizing to many downstream EHRs, like Cerner and Epic on an event driven basis is difficult because each EHR has slightly different conventions and requirements to accept data.

Medplum Features Used​

· 3 min read
Reshma Khilnani

(2 minute demo)

Introduction​

Summer Health is an innovator in direct-to-patient pediatrics, with a focus on messaging and mobile access for parents via SMS. Their fast growing practice is available nationwide and is known for excellent patient engagement.

Medplum Solutions Used​

  • Custom EHR - The Summer Health custom EHR allows providers to respond to patient messages, enables task management and automation, and has AI-assisted encounter documentation.
  • Patient Portal - The patient experience includes the ability to reach pediatricians via messaging, and to view information across web and mobile devices.
  • FHIR API - with all data being natively stored as FHIR, enabling synchronization through a FHIR API to Google BigQuery allows robust analytics and visibility into operations.

Challenges Faced​

The unique nature of the Summer Health offering necessitated custom software development, specifically:

  • Messaging-based workflows are convenient for users, but require aggregation, careful data extraction and synthesis to be actionable for providers.
  • Pediatrics requires complex access control patterns because patients are children and multiple caregivers are creating and accessing data on their behalf.
  • Timeliness and tasking are crucial and providers and staff respond in a timely manner to patient inquiries.
  • Mobile access with single sign on for clinicians who primarily administer care through mobile devices. This was a key pain point with other solutions.

Why Medplum?​

Medplum stood out for the following reasons:

  • Complete control over the user experience, reducing burden for the providers.
  • Identity management and access control allows caregivers to access records.
  • Unlimited and flexible integrations, and ability to build them as needed without restriction, including streamlined incorporation of cutting edge technologies like LLMs.

The team completed their initial build in 16 weeks.

Features Used​

The following Medplum features were used to build this product.

  • Integrations - notably Medplum's integration framework and tools made it easy to integrate BigQuery and LLMs.
  • Google Authentication and External authentication - Summer Health uses multiple identity providers for practitioners and patients respectively.
  • Access policies - Patients are children, so parametrized access policies support parent and caregiver access.
  • Subscriptions - integrations to data warehousing and other applications are powered by event driven notifications
  • FHIR Datastore, specifically family relationships and GraphQL allow for medical records that incorporate sibling and family member context
  • Charting and Task Management - encounter documentation and tasks are featured in the application and major drivers of the workflow.
  • Bulk FHIR API to support reporting and interoperability with other systems.