Encounter Based Imaging Workflow - Brief Proposal

1. Proposed Workitem: Encounter-Based Imaging Workflow (EBIW)

• Proposal Editor: Kevin O'Donnell / Kinson Ho
• Proposal Contributors: Elliot Silver, Christopher Roth, Dawn Cram, Alex Towbin, Ken Persons, Paul Lipton, ...
• Editor: Kevin O'Donnell / Kinson Ho
• Contributors: See Support & Resources
• Domain: Radiology

2. The Problem

Encounter-based Imaging (a burgeoning area of activity) needs to be supported as well as Order-based Imaging (aka Scheduled Workflow).

EBI needs the same kind of committee analysis we did for SWF:

• Use Cases - what are the different ways encounter-based imaging is performed
• Metadata - what context details need to be captured, stored, conveyed (to support capture, search and review)
• Linkage - what other artifacts/results do the images need to be linked to, and how
• Organization - how is the data organized to meet the needs of its users (study, series?)
• Communication - what notifications and "loop-closures" are needed
• Data Transfer - what protocols should be used to move the different pieces of data and metadata

Even with many vendors converging on similar concepts, the SWF exercise in the late 90's was valuable to tease out subtle details, resolve elements of disagreement and confusion in the implementer community, and nail down various technical details. It contributed to an extended period of robust departmental interoperability.

An EBI exercise and profile could provide similar benefits in the expanded medical imaging community.

Costs of Status Quo: Sites have highlighted EBI related problems like:

• Images Absent from or Scattered throughout EHR
• Silo-ization of the medical imaging record
• Images Not Available to Care Team
• Images Placed in Paper Record or Scanned into EHR
• Limited Data Sharing w/ Acquired & Affiliated Hospitals
• Time spent on awkward workflow and data capture and lack of automation

Specific Technical Gaps (e.g. relative to Scheduled Workflow):

• Marshalling and conveying metadata:

• Procedure codes are appropriate for some encounter-based imaging but an order per se is not necessary (and would disrupt their workflow)
• Well-populated metadata is critical, but patient metadata comes from the EMR, encounter metadata may come from a Practice Management System or Department System, and procedure metadata may need to be entered at the time of capture.
• Worklists are an effective tool to deliver good metadata to smart devices, but encounter-based imaging and devices may need other mechanisms.

• Capture Process

• Consider focusing initially on the capture process (there is some risk in the varied usage needs in the different departments/use cases)

• Although downstream usage of the data can't be completely ignored.
• What is the end result of the first profile - e.g. what is passed to the EHR to index, find, display, provide to physicians
• A big gap is labelling/tagging to know the procedure behind the encounter image
• Body part is not well populated (2,000 for some dermatology groups, 1 for others) - device should provide it, but often not well done, also tags are lacking for some purposes
• Sharing tags with order-based makes it easy to pair, but need it to be easy

• Will need to be clear what we will/will not do (e.g. start with standard tag/location but standardizing procedure codes is not typically done yet)

• Data flow

• should get the same end result as if the clinician placed the order

• Want to support the same analytics, access/indexing of the imaging

• Facilitate Image Consumption

• In Order based there is an order and a report to close the loop
• Recognize some images are results (diagnostic procedure), some images are documentation (augment another procedure)

• EBI has multiple kinds of results - endo images, surg notes, all linked to the procedure
• EMR can backfill orders, but the cross result linkage on a different system is a problem, esp when exchanging with other institutions
• DICOM Study is a grouping method, but with a JPEG on a disk, the context/linkage metadata is missing.

3. Key Use Case

• Dermatology
• Wound Care/Management
• Infectious Diseases
• Burn Care
• Plastic Surgery
• Nursing/Clinic Photography
• Point of Care Ultrasound

Use Case 1: Imaging with Simple Devices (non-DICOM)

Many departments capture clinical photos for documentation, follow up care, and diagnostics. Capture devices include digital cameras, smartphones and tablets and run on platforms including iOS, Android and camera-specific operating systems.

• Use the systems/information associated with the current patient encounter to generate the needed context details and populate them in the image artifacts created.
• The images (clinical photos) that will be taken are not known prior to the visit, but rather, are at the provider's discretion during the visit, may be used to document various states of wounds, bedsores, or other disorders.
• Orders are not a required element clinically.
• Example:
  • Patient makes appointment for Dermatology visit.
  • Patient arrives for Dermatology visit and is registered/checked in, as a patient class of OP (outpatient)
  • EHR or HIS triggers an ADT^A04 release
  • Provider may or may not decide to take clinical photos of the patient during the visit to document disease processes, pathologies or disorders.
    • If the provider decides to take clinical photos as evident of care or for diagnostic reasons (ie - dermascope), image content may include photos of multiple body parts.

Note: Basic video capture and store is part of scope. Advanced video management (e.g. annotation, point of interest, editing, etc.) are out of scope.

Use Case 2: Point of Care Ultrasound (DICOM modalities in unordered workflow)

TODO: Write some text here

Future Use Cases

As part of keeping the scope practical, the following logical applications and use cases are listed but identified as being out of scope for the first profile.

• Ophthalmology
• Otolaryngology
• Podiatry
• ER/Trauma
• Dentistry
• Sports Medicine
• Pathology Samples
• Procedure Video (e.g. Surgery)
• Sleep Lab Video

Use Case x1: Surgical Documentation

Pre, during, and post-surgery, images document the procedure and provide diagnostic information. Examples include scope video and still images, ultrasound, external photography and video, and ECG. The workflow is encounter-based since orders are not required and capture is either at the discretion of the Surgeon or is inherently part of the surgical procedure.

Challenges include:

• additional complexity or cumbersome workflow is very unwelcome in the surgical environment
• other pre, during, and post-surgery imaging is order-based and often performed by another department, e.g. x-rays from Radiology or OCT from Ophthalmology
• order imaging often generates it's own visit/encounter, separating surgical imaging from the surgical visit/encounter.
• surgery on an admitted inpatient triggers an ADT transfer which may not include the encounter/visit number of the admitting surgical department.

• but registration/arrival of an ambulatory surgical patient triggers an ADT^A01 or ADT^A04 and can follow the same workflow as an outpatient Dermatology visit

Some needs and mechanisms from the Cardiac Cath Workflow profile may be relevant here.

Use Case x2: Patient provided images

Images captured and provided by the patient are increasingly part of care.

They have advantages such timeliness (being captured at the moment a symptom presents), convenience (they can be captured without the patient or a caregiver having to travel), and frequency (they can provide a daily record while only visiting the clinic every two weeks).

They also introduce challenges to collecting quality images with accurate metadata given that the patient is untrained in clinical procedures, does not have access to the provider IT systems and is using an "uncontrolled" device. It is also necessary to convey the images to the care provider and integrate them properly into the patient medical record.

Use Case x3: Post-Acquisition Processing

After the images are captured, sometimes there are additional image processing steps that need to be performed. For example:

• Annotation
• QA
• Color correction

4. Standards and Systems

Potential Systems

• Image Acquisition Devices (both Lightweight and Heavy/Integrated)
• Image Archiving Devices
• Electronic Medical Record Systems
• Practice Management Systems
• Encounter Management System (office/departmental system that provides the encounter context)
• QA System
• Encounter Imaging Consumer

Potential Standards

• Existing Profiles: PAM, WIC, SWF, MHD-I, XDS*, CARD IEO
• DICOM (DIMSE), DICOMweb
• HL7, FHIR
• Consumer media formats: JPEG, MPEG, PDF, RAW, etc

Relevant Whitepapers:

• SIIM-HIMSS Enterprise Imaging Workgroup - White Papers
• A Foundation for Enterprise Imaging - JDI Whitepaper
• Order-based vs Encounter-based Imaging - JDI Whitepaper
• The Workflow Challenges of Enterprise Imaging - JDI Whitepaper
• Technical Challenges of Enterprise Imaging - JDI Whitepaper
• PCD Encounter-based Patient Identification Management whitepaper

Relevant Current and Past Activities:

• Encounter-based_Imaging_Workflow A special interest group that has started the discussion on encounter based imaging workflow
• Internet-Ready_SWF_-_Proposal started to consider encounter-based imaging as well.

5. Discussion

• IHE is a good venue to solve the encounter-based workflow problem because currently there are many proprietary ad-hoc workflows trying to deal with similar problems. As a start, IHE can create a profile to establish basic encounter-based imaging workflow that are broadly applicable to many specialties. Future enhancements can be introduced for additional support for various specialties.

• Scope Management: Instead of addressing the full spectrum of challenges related to encounter-based imaging workflow, the focus of this proposal is to address the following questions:

• Focus on the two key use cases identified. See Key Use Cases section for further discussion
• Define the minimal necessary set of metadata (related to the patient, encounter, procedure, etc.) associated with those use cases
• Identify the source(s) of each piece/set of metadata
• Try to limit to two pathways to aggregate and combine the metadata and pixels for the two identified use cases
• Address notification to EMR when study becomes available

• During the design, we would keep the clinical usage of the images in mind, but the profile may not address some of the downstream activities in the first release.

• Niche risk - solving an instance of the problem instead of the broad class

• e.g. Is the point-of-care US solution developed applicable to point-of-care endoscopy/photography?
• IHE Rad cochairs will reach out to IHE imaging (Eyecare, Cardiology, Pathology, Endoscopy, Dental) to make sure they are engaged in the requirements and work. Historically they have successfully borrowed heavily from IHE Rad work.
• focus on general metadata, not device/specialty specific, but allow extension from specialty specific code (e.g. dermatology anatomy codes)
• might need domain specialty attributes

• EMR Participation - this profile must consider EMR interactions so we need their participation but that's traditionally been sparse in IHE Rad.

• Ken Persons and Thomas Pickard will reach out to Matt Doyle from Epic
• Mike Bressack can talk to Cerner
• Elliot Silver will talk to Cerner
• Rob Mitchell will contact Julie Pekarek <jpekarek@us.ibm.com> to see if the E-Orders Coalition can be used as a recruiting/engagement channel

• Reach out to IHE (imaging) - Eyecare, Cardiology, Pathology, Endoscopy, PCD (patient identification for encounter-based workflow) - Cochair Action Item

• They have already engaged domain vendors and adapted SWF. Their experience/advice will be important. Specifically, they understand their domain details.
• Invite other domains to present their workflow and see how harmonize/divert this solution compared to what they have already had

• If we build it, will they come? Will image vendors implement this?

• Miami, Duke have found definite interest from the vendors (perhaps by focussing on a specific group, ophth/endo?)

• Vendors may stick with proprietary solution that already exist and unwilling to switch to a standard-based solution

• Solution of this profile tries to be aligned with existing solution