Encounters and Orders World Mismatch, Our Experience

Encounters and Orders World Mismatch, Our Experience

Our product BodyMapSnap had a humble start, with a vascular surgeon wanting to coordinate his pre-and-post care and developing compliant mobile photo collaboration tool such as Slack to fix the HIPAA issues inherent in social media photo and video apps.

Efficient and accurate care coordination requires a lot of visual elements, including tracking the wound healing process, or checking case planning worksheets to make appropriate pre-operative decisions as a team

As those images accumulate, other clinical users have started to ask why not share some of these images and videos in their PACS/VNAs or EHRs. We’ve found that similar workflows were largely shared by Pediatrics, Orthopedics, Sports Medicine, Dermatology, Wound Care, Podiatry and even Dentistry.

In traditional clinical imaging scenarios, an image acquisition device is considered as a modality (like CTs and Ultrasound). So, to use those devices, an order is made, and radiologists read the images and create reports.

In our development, a few things became very clear:

1.      All those images are centered around an encounter and episode of care.

2.      Not every image is relevant in being associated with medical records, but “exporting” selectimages to PACS/VNA and EHR provides great benefits.

3.      For PACS/VNA imaging orders are typically needed.

This has been the typical clinical integration “impedance mismatch” and has been the subject of many concerns in our own customer discussions.

In this article, we would like to share how we are approaching our solution today to address this impedance mismatch.

Every Study by Default Starts with an Anonymous Encounter

When a clinician launches (or resumes) the BodyMapSnap app, the user is asked whether it is a New Encounter or a continuation of the on-going encounter. In both cases, it does not require a patient name, MRN or order to proceed. The user can proceed to take photos and chat with other users to discuss cases immediately.

Traditional Modality Worklist Starting Point is also Possible

A user is also given a choice to go to open the “Patient List” and select the appropriate patient from the Modality Worklist.

Unified Patient List Mode

If a unified patient/order search* strategy is used in combination with BodyMapSnap, it is also possible to present the unified patient list from the amalgamation of MWL, Prior Studies, and admission events from the EHR feeds.

If appending of a new series to an existing imaging order is permitted, we can “push” selected images into an existing imaging accession.

Automated Order/Accession Generation

Auto order generation and routing strategy* is an option if a patient has already been established and accession generation scheme can be implemented with the customer.

In addition, it is possible to push images to EHRs as an unsolicited order/report and store the image in their “media tab” without an order.

After-The-Fact Push

Any anonymous encounter will “park” on our the BodyMapSnap’s secure server. A user will be able to associate anonymous encounters when a patient or order is established.

Image uploaded from iOS.jpg

OCR to the Rescue

We have an OCR engine** plus a bit of AI and so the encounter has a photo of wrist band, bar-code, QR code, association of anonymous studies and “after the fact” push will be automated. This does not have to be the very first image.

In Conclusion

We have found that a surprising number of clinical users rely on photos to orchestrate efficient and accurate care coordination. We’ve explored many ways to match the encounter based and order based visual imaging workflow and clinical users can have effective choices in realizing both worlds to interoperate. We are hoping better recognition of the encounter based scenarios in medical informatics industries will provide even better support in the coming months.

*WinguMD has tested with DICOM System’s Unifier to realize these functionalities.

** We have integrated with medical grade OCR from EDCO