5 common clinical information blind spots
A new white paper titled Beyond Radiology and Cardiology: Harnessing non-DICOM Dark Data discusses (in detail) the growing problem non-DICOM image and video files (e.g. JPEGs, MPEGs, PDFs, etc.) pose to healthcare facilities when they aren’t included as part of a centralized enterprise image management strategy.
The growth rate of data moving into VNAs (vendor neutral archives) is exploding – expected to have reached 1.4 billion objects in 2017 – and approximately 75 percent of these objects will be non-DICOM assets, according to the paper. To date, many hospitals don’t have formal strategies for how to identify, import and manage non-DICOM images and video as part of core image management and security efforts.
This puts organizations at risk of exposing PHI (protected health information).
Moreover, these assets often aren’t included in or accessible from the EHR (electronic health record). These holes in the health record provide clinicians with an incomplete picture of the patient that can negatively impact diagnoses, treatment plans and ultimately, outcomes.
Reducing data silos
With increased scrutiny on healthcare organizations to tighten security efforts to protect patient data, and an industry-wide movement toward greater interoperability and patient-centered care, the need to establish centralized insight and control of your non-DICOM assets has never been more important.
However, this can be a significant challenge because these images reside in all sorts of systems, devices and media throughout HDOs.
The departmental nature of care delivery in the past has created a plethora of locked and blocked data silos that contain critical clinical images your organization may be unaware even exist. Identifying and consolidating these assets as part of an enterprise imaging strategy allows for the deployment of a more complete EHR, while reducing costs locked in departmental system solutions.
The key is to identify areas throughout the HDO where the largest numbers of unconnected and potentially valuable non-DICOM images are likely to reside. By bringing these images into the fold, you can address some of your biggest risk areas while adding the most clinically relevant patient information to the health record.
Reducing blind spots
The following are five of the biggest sources of non-DICOM blind spots in hospitals and health systems:
1. Visible light images and video
Granted, this source is fairly convoluted because of all the areas of the hospital where visible light images and video are captured and stored. However, they are all important whether they’re endoscopy or colonoscopy images from Gastroenterology; ureterostomy or cystoscopy images from Urology; or laparoscopy images from OR/Surgery.
It’s vital that you identify all of the producers of visible light images and video throughout the hospital. The next step is to implement technology solutions that allow you to capture and import these assets in their native formats from a wide range of video scope systems and processors.
2. Dermatology and Plastic Surgery
Many Dermatology and Plastic Surgery departments have specialized imaging systems that capture high-definition (and sometimes 3D-rendered images) of everything from routine skin conditions to complex reconstructive surgery.
These images are important pieces of the clinical narrative that are often missing from a patient’s electronic health record because of the isolated and proprietary nature of many of these systems, so it’s important to find a solution to make them accessible across the organization.
3. Ophthalmology
Ophthalmology departments also routinely leverage specialty systems that capture images of the retina, cornea and other features of the eye. A complete picture of a patient’s eye health can only be obtained by including images from these specialty systems in an overall enterprise imaging strategy.
4. Mobile devices
The healthcare industry today is increasingly mobile. Clinicians at the point of care (especially in Emergency Rooms) routinely capture images of wounds, allergic reactions, skin anomalies and more in the exam room on their smartphones and tablet devices.
Capturing, consolidating and managing these photos as part of an enterprise medical imaging strategy can be challenging, particularly in healthcare environments that have adopted a BYOD (bring your own device) mobile policy. A technology you can install on mobile devices to encrypt and route medical images from these devices to a central PACS, VNA or EHR, while ensuring no image data is saved to the device camera roll is essential.
5. CD/DVD media
This is another convoluted source of non-DICOM (and potentially even DICOM) images and video. Practically any medical department that leverages imaging in some way, shape or form has (at one point or another) stored old patient images on CDs or DVDs.
These images are rarely, if ever, accessed by clinicians and are completely disconnected from the EHR. It is important that the pertinent historical imaging data contained on this media is imported into an enterprise imaging platform and reintroduced to the patient record.
These five sources of medical imaging clinical blind spots are just a sample of the areas to keep in mind as you pursue an end-to-end enterprise imaging strategy. As the industry moves further down the path toward delivering true personalized medicine, other emerging areas – such as pathology and genomics – will be important to consider in an effort to produce and maintain a comprehensive patient record for clinical use.
Furthermore, HDOs also sometimes forget additional unstructured information exists within other departmental systems and provides another source of important clinical information. A well-articulated and focused enterprise imaging and content platform strategy forming an enterprise information platform with a reputable partner capable of delivering the necessary interoperability requirements can put your HDO on the path for delivering a truly comprehensive EHR.
For more, read Beyond Radiology and Cardiology: Harnessing non-DICOM Dark Data.
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