Enterprise Imaging: What is It and Why have It?

Rear view of two female doctors working together on computers
Jan 23, 2020

Enterprise Imaging: What is It and Why have It?

Martin Kappeyne

Written by Martin Kappeyne

Category: Imaging

Healthcare delivery is moving from specialized silos of patient care to an integrated team of health specialists sharing patient information. Enterprise imaging (EI) focuses on enterprise-wide delivery of imaging information. It brings technical complexities, as well as organizational challenges that should not be ignored.

 

What is Enterprise Imaging?

EI now extends far beyond diagnostic imaging in radiology, cardiology and ophthalmology. It now includes any conceivable type of image, whether it’s a CT scan, intraoperative video, photo taken from a cellphone or even a PDF. An organization needs to save, retrieve and display the information in the proper context. Data needs to be organized, categorized and data-aging tracked so it can be removed or at least anonymized. We will examine these aspects, as well as technical, organizational, security, and legal considerations.

Definitions for EI can vary, but at its core, it involves the pulling together of all images that are frequently distributed across a healthcare environment in different databases, on desktop hard drives, memory sticks or DVDs and placing the data into a single storage environment with an associated database. Oftentimes, the existing storage method is inefficient, not backed up and may not comply with HIPAA security requirements. Such images become difficult to link to the patient’s electronic medical record (EMR), resulting in some users having to log into multiple systems to gain full insight into the patient’s record. Often, this data is captured in an ad hoc, spur-of-the-moment fashion, perhaps without orders and without the acquiring clinician spending much time setting up the image capture.

The process of collecting images from multiple sources needs to be suited to the environment where the image is created. One method of collection is often sub-optimal for other workflows and environments. Ensuring that this can be done in a fashion acceptable to the clinical staff is often at the heart of user acceptance. Simplicity and integration into the workflow become keys to user adoption.

Each clinical image needs to capture pertinent information not only about the patient, but also items such as the timestamp of the encounter, a description of the encounter and some information (tags) around what it contains so it can be retrieved in the appropriate context. The image retrieval needs to occur transparently to the user and should be as easy as clicking on a hyperlink within the context of the application being used. After an image has been acquired, specialists may want to take the data and manipulate it with other software and then return it with some additional images or comments to the storage.

Why have Enterprise Imaging?

Enterprise imaging’s goal is to make any clinical image available to authorized users – anytime and anywhere. This has direct impact on telehealth, continuity of care, and physician and patient access.

Centralizing and standardizing data collection and storage ensures security, enhances data quality, reduces the cost of data management, and simplifies access to the data. The data can be shared with others (health information exchange) and gets used for comparison to document the state of disease and healing. This supports better care delivery and allows physicians to gain a more complete picture of the patient without having to log into multiple specialty systems.

In many cases, the data may need to be shared with outside specialists or referring physicians, or perhaps researchers may want to examine clinical information needed for developing artificial intelligence (AI) routines that require large amounts of standardized and anonymized data. In such cases, the system will be required to provide a secure and efficient means of transferring data.

From data management, cost and legal perspectives, all data should age out after regulatory and organizational retention time limits have been met. The system needs to be able to do so automatically and retain only selected cases that may be needed for litigation, regulatory or other designated purposes.

In summary, EI is multifaceted and needs to address all these aspects appropriately and in the right sequence to ensure successful deployment.