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Don’t Ignore Encounter-Based Medical Images

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In today’s healthcare environment, there are several types of medical images captured outside of structured, order-based radiology processes. Consider, for example, an inpatient who must have a bladder ultrasound performed at the bedside to aid in the placement of a catheter, or a photo of a compound fracture taken in the Emergency Room that is meant to accompany an x-ray.

These images are important to the diagnosis and treatment of a patient and can provide valuable insights when considered as part of a patient’s complete medical history. However, because the workflows used to capture these images are encounter-based rather than order-based, the assets rarely venture beyond the locations from which they were acquired.

Read More: What Is Automated Machine Learning (AutoML) and Is It About to Put Data Scientists out of Work?

This is a problematic oversight when it comes to creating a comprehensive patient imaging record.

Identifying rogue data

Commonly referred to as “encounter-based images,” these assets are typically the product of specialty departments such as dermatology, wound care, infectious diseases, burn care, plastic surgery and point-of-care ultrasound. Furthermore, they often become what Gartner defines as “dark” or “rogue” data (i.e. information assets organizations collect, process and store during regular business activities, but fail to use for other purposes).

This image-based dark data not only fails to provide ongoing value to clinical processes, but because this information typically isn’t controlled by enterprise-wide security protocols, it is vulnerable to exposure and breach.

Encounter-based imaging is a largely overlooked and burgeoning area of activity that needs to be addressed, according to Integrating the Healthcare Enterprise (IHE), a non-profit organization dedicated to improving the way computer systems share medical information. The failure to consider specialty images as part of a patient’s medical record results in time lost due to manual capture workflows, missing or incomplete metadata associated with specialty images and a lack of visibility and sharing of specialty images both internally and externally, according to IHE.

Read More: Why Is Explainability Important and How Can It Be Achieved?

Eliminating rogue data

In an effort to streamline the capture of encounter-based images as well as their integration with core clinical systems, Hyland Healthcare has developed Image Link Encounter Workflow. As part of our PACSgear suite of image connectivity and acquisition solutions, we specifically designed it to address the encounter-based imaging problems common to many specialty departments.

Using an automated process, the solution resolves issues with incomplete or incorrect metadata using a variety of data sources, logic and/or lookup tables. Updated medical imaging data for these assets is then forwarded to the appropriate enterprise repository (e.g. PACS, VNA, etc.).

With Image Link Encounter Workflow, healthcare providers can eliminate rogue or dark data that often results from ad hoc departmental workflows. Furthermore, it can help a health system explicitly manage protected health information (PHI), protect patient confidentiality and reduce organizational risk.

Best of all, because the solution is PACS, VNA and specialty independent, it allows healthcare organizations to quickly enable a comprehensive patient imaging record that can finally include encounter-based images. This empowers everyone in your organization to provide the best care possible.

Read More: In Appreciation of The Technologists Who Simplify Our Lives

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