Top Five Technologies to Support Encounters-based Imaging Workflow

In the medical imaging community, there is plenty of buzz surrounding encounters-based imaging workflow. So what is encounters-based imaging?

Historically, when people think of medical imaging, diagnostic imaging comes to mind, such as what you see in radiology and cardiology. Workflows in diagnostic imaging are generally order-centric. Providers order imaging exams for their patients (e.g., X-ray, CT, MRI, etc.), and those orders are sent to the diagnostic imaging department for processing. Orders drive the technologists’ and diagnosticians’ workflows in RIS and PACS applications. The imaging devices, or “modalities,” receive the orders, which also contain patient demographics. Ultimately, the patient is scanned, or “imaged,” for the requested exam, digital images are created, and diagnostic reports are produced by the diagnostician. That data is then sent back to the requesting provider, billing is generated, etc. Within this workflow, the entire process revolves around the order.

Let’s contrast this to encounters-based imaging. In many clinical specialties outside of diagnostic imaging, the decision to acquire imaging is made spontaneously at the point of care. Nobody places orders ahead of time to request the imaging department to acquire imaging. Rather, the providers decide to acquire imaging in real time based on what is going on with the patient. Examples include wound photos, dermatology photos, point-of-care ultrasound, orthopedic videos (e.g., range of motion and gait study videos), and plastic surgery, just to name a few.

Sounds easy, right? The challenge, however, is how to attach patient demographics to the images in the absence of orders so the images can be properly indexed to the patient and integrated into the electronic health record (EHR). Furthermore, where do you store these images so they become part of the patient record? As with diagnostic imaging, a desired outcome of encounters-based imaging is to make the imaging available to the entire care team through the EHR. Most PACS are very order/DICOM-centric platforms and thus not well-suited to accommodate encounters-based imaging and non-DICOM content. So what solutions are well-suited to support these kinds of workflows?

Here are the five most common solutions for automating encounters-based imaging:

1. Vendor-neutral archive (VNA): A true VNA is the best option to support encounters-based imaging. As mentioned earlier, PACS are generally order-centric platforms and optimized around the DICOM standard. Attempting encounters-based imaging workflows and non-DICOM content can be challenging with PACS.

A key feature of the VNA is its ability to notify the EHR upon ingestion of new patient content. This allows the EHR to place a link in the patient’s chart to view the content via the enterprise viewer. While patient care improvements are the main benefit of encounters-based imaging, charge capture and billing are also important. Fujifilm’s Synapse® VNA makes it easy to add procedure codes to encounters-based imaging, thus enabling our customers to capture revenue and increase the return on investment on their VNA. Procedure codes and descriptions are also included in the notifications to the EHR, when applicable.

Encounters-based imaging and support for non-DICOM content are two of many reasons why a VNA, along with a robust enterprise viewer, should be the foundation of your enterprise imaging strategy.

2. Mobile capture applications: These tools are essential for healthcare providers. Not only do they provide methods for attaching patient demographics to photos and videos, but most also offer a layer of security by deleting the content from the device after uploading to the VNA. This functionality virtually eliminates the risk of protected health information (PHI) inadvertently walking out of the healthcare facility. At Fujifilm, we offer Connext Mobile for secure, point-of-care capture of patient photos and videos. The solution also supports configurable electronic forms to document additional observations, notes, and metadata. Connext Mobile includes a department-specific, encounters-based worklist for patient identification. Alternatively, the patient’s barcode can be scanned, or users can simply look up the patient manually.
3. Browser-based or desktop upload applications: These applications serve as a more general-purpose, “upload to VNA” tool for enterprise patient content. They often function like mobile capture applications, though they are geared toward uploading files such as MPEG, MOV, or AVI video files, JPEG or PNG photos, PDFs, and TIFFs to the VNA. At Fujifilm, we offer Connext Web for secure upload of any patient content, regardless of file type.
4. File pollers: File pollers come in handy for devices and systems capable of exporting their content to the file system. File pollers watch or monitor a shared location on the file system, and when a new file or folder is detected, they automatically upload the content to the VNA with no human interaction. Patient demographics can be obtained from the file’s header or from a companion XML file, which is placed alongside the media files and contains the patient demographics as XML tags. Fujifilm has many file pollers active across its customer base, and we’re making more all the time.
5. HL7: Believe it or not, HL7 has a mechanism to send files through observation result (ORU) messages. Some imaging systems can embed files in HL7 ORU messages as base64-encoded objects. This is analogous to email attachments—the files are like attachments to HL7 messages. Capable VNAs, such as Synapse VNA, can extract the file from the HL7 message and upload it to the VNA using the demographics from the HL7 message to index the content to the patient record. Note that even though ORU message types are used, it does not imply that an order-based workflow is required. This is simply the message type used to send the files to the VNA.

What is the IHE EBIW profile, and should I care about it?
Encounters-Based Imaging Workflow, or EBIW, is an IHE profile that describes the functions of the various actors involved in encounters-based imaging. It describes an “encounter manager” actor that is responsible for delivering patient demographics to the image acquisition device/modality, an image manager/image archive (i.e., a VNA), and a results aggregator (i.e., the EHR). The fact that the EBIW profile exists is a testament to the prevalence of encounters-based imaging in modern healthcare, and the profile provides a nice blueprint for how such imaging can be implemented. Long story short: Yes, you should become familiar with the concepts described in the profile, and if your VNA vendor doesn’t know EBIW, that should be a red flag.

What is XDS, and is it required?
Let me put it this way: If you don’t know what Cross Enterprise Document Sharing, or XDS, is, you probably don’t need it. Put another way, if you have a business need for XDS, then you may need it. XDS is another IHE profile. This profile describes a framework for how documents (i.e., non-DICOM files) can be shared among a community of loosely affiliated health organizations. Some VNA vendors design their entire non-DICOM solution based on the XDS profile. This may make sense if you have a business need to share non-DICOM files with affiliates. If not, XDS may bring an additional layer of complexity that you don’t need. At Fujifilm, we built our non-DICOM solution to be very lightweight and not require XDS. We do offer XDS as an option for organizations with a business need, however.

Overall, EBIWs are quite common in modern healthcare, and there are numerous workflow solutions to support them. These EBIW solutions, such as Synapse VNA’s Connext Workflow Solutions, allow for seamless and secure capture, indexing, archival, and display.

Want to learn more? Download our Synapse VNA Connext Workflow Solutions Brochure to see all the ways Fujifilm supports encounters-based, intelligent workflows and schedule a demo with us during HIMSS 2024 to see our technologies in action.