One of the challenges to successful implementation of an enterprise imaging strategy is workflow design. As hospital systems adopt enterprise imaging, they are faced with the inherent disparate workflows associated with various legacy PACS.* While standardizing workflows can lead to efficiencies, there are circumstances in which customizing workflows by department can benefit both provider and patient.
When workflow customization is dependent on a new software release from a PACS vendor, however, it can be a slow process. The key is to move the customization process from the vendor to the healthcare provider.
When workflows don’t “fit.”
Each PACS vendor develops its own proprietary software and workflows. Given the distinct needs of different branches of medicine, these “off-the-shelf” workflows are typically not flexible enough to meet the needs of different departments or facilities within an organization.
When workflows don’t fit diverse department, facility, modality or reporting needs, IT staff resort to requesting functionality changes from the PACS vendor for its next software release. As a function of the vendor’s prioritization processes, the changes may be made… eventually. Such is the dilemma when change is managed at the PACS vendor level.
Tailoring workflows in-house.
Rather than relying on outside vendors to make workflow changes in a product-release context, some healthcare organizations are taking ownership and tailoring workflows themselves. As part of an enterprise imaging solution, the right dataflow engine should empower users to develop workflows that fit their needs precisely, saving significant time.
A strong dataflow engine also incorporates a graphical dataflow designer, including basic workflow building blocks and drag-and-drop editing tools. It allows users to make extensive modifications quickly and easily, determining when to tag morph and pre-fetch, when to find and filter studies, and when to route them between PACS and VNA. With a few simple clicks of a mouse, they can design a workflow in which correct metadata and reports are associated with images, whether order-based or encounter-based.
With new workflow-customization capabilities, healthcare leaders are now able to meet organizational workflow needs at any level – enterprise, specialty or user. The flexibility an effective dataflow engine provides ensures even future needs can be met.
The question remains.
Can workflows work better? With an enterprise imaging solution and a dataflow engine that enables easy, end-user workflow customization, the answer is, “Definitely.” To learn more, contact us today.
* Towbin, A.; Roth, C.; Bronkalla, M.; Cram, D. (2016). Workflow Challenges of Enterprise Imaging: HIMSS-SIIM Collaborative White Paper. Retrieved from The National Center for Biotechnology Information (www.ncbi.nlm.nih.gov) March 7, 2018.