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How to Get Better PACS EHR Integration with Modality Worklist

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Imaging centers that produce a high volume of studies every day, or that use multiple modalities, often struggle with their workflow in the face of strong patient demand. If you use DICOM imaging studies, there is a solution: Modality Worklist (MWL).

So, what exactly is MWL, and how can it provide you with a seamless electronic health record (EHR) integration?

What is Modality Worklist?

Modality Worklist is a technology or software capability associated with DICOM imaging studies that has the potential to significantly improve your workflow. When you use Modality Worklist, the patient demographic information that has been acquired and stored in your EHR system is electronically sent to the imaging modality itself.

Whitepaper: Isn't It Time Your Electronic Health Records Included Your Patients' Images?

This means that later, when a radiologist or technologist needs to acquire the study from the modality, they don't have re-enter the patient or study demographic information, such as name, sex, or date of birth. All of this information has already been populated within the modality based on the data from your EHR system.

The benefits of Modality Worklist are particularly relevant for facilities that see a high volume of imaging studies, or that use multiple modalities, such as imaging centers and hospitals. In such cases, the act of typing in patient demographic information creates a drag on radiology workflow.

Medical imaging professionals spend an inordinate amount of time every day just typing in this information, but using Modality Worklist can make the whole process more efficient and improve productivity.

How Does Modality Worklist Help Integrate Your PACS with Your EHR System?

Many radiologists dream of having a seamless integration between their EHR system and their imaging studies stored in the cloud. For example, an integrated PACS/EHR might have a button within the EHR itself that launches a view of related images stored in the cloud, without ever having to log in or enter an extra set of user credentials.

To achieve this continuous integration, however, there needs to be additional information passed between the EHR and cloud PACS beyond just the patient's demographic information—some sort of unique identifier that connects the patient's exam within the EHR to the related imaging study in the cloud.

Such a unique identifier is generated by the EHR system and is known as the accession number or exam ID. When this number is entered into an imaging modality, it makes it much easier to implement a cloud PACS EHR integration, as the two systems are able to recognize a commonality on the given exam.

However, a unique identifier that can be up to 16 digits long is a substantial burden for many imaging technologists to enter into the modality, and presents a very real possibility for human error when typing it in manually.

This is where Modality Worklist comes in.

It takes the information from the EHR system and provides it to the imaging modality electronically so that the technologist doesn't have to re-enter any of the information. The accession number can then pass to the cloud PACS along with the other DICOM fields when the image is sent. Receiving the accession number in the cloud closes the loop as it enables the EHR and cloud PACS to communicate regarding the specific exam through the use of this unique identifier.

With this type of usage, the benefit of Modality Worklist is greater than simply improving your workflow. It serves as a "man in the middle" to making PACS/EHR integrations as painless, frictionless and error-free as possible.

Final Thought

Using Modality Worklist with an EHR system and cloud-based image storage can be a winning combination for many businesses, especially if you're a high-producing or multimodality imaging center or hospital. Modality Worklist is an enabling technology that can deliver a seamless integration between an EHR system and the cloud, greatly improving your workflow and saving you valuable time.

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