What is Enterprise Imaging?

Understanding enterprise imaging is often complicated by the use of a myriad of technical terms used to describe it. The most commonly accepted definition, however, is “a set of strategies, initiatives, and workflows implemented across a healthcare enterprise to consistently and optimally capture, index, manage, store, distribute, view, exchange, and analyze all clinical imaging and multimedia content to enhance the electronic health record.”

Evolution of Enterprise Imaging

Healthcare delivery has evolved for the better due to many technological advances that continue today. For some time, the medical sector has been pivoting away from traditional picture archiving and communications systems (PACS, now known as MIMPS) and cardiovascular information systems (CVS) in favor of enterprise imaging and data management systems. The advent of vendor-neutral archive technology (VNA), and especially its accelerated adoption over the past decade, has been an important aspect of enterprise imaging.

Many departments within healthcare organizations such as dentistry, pathology, dermatology, and GI endoscopy, produce images in the visible light spectrum. However, in many enterprises, these images are not easily available through the standard electronic health record, and frequently departments fail to securely digitally archive them. This oversight represents a failure to consider the full effect on patient care and patient experiences, the caregiver’s quality of work, and other factors impacting quality of service. However, in enterprises where VNAs have been adopted, the availability of images via a single login to the system helps improve the quality of interpretation by clinicians, reduce the number of duplicate exams, and improves enterprise efficiency.

Enterprise imaging has been used to refer to the conglomeration of multiple hospitals or radiology departments into a single imaging system that allows moving of images for interpretation of examinations. It also has been defined as the incorporation of all medical images into a single archive, itself frequently integrated into the electronic medical record (EMR). While these two practices are different, they are by no means mutually exclusive. The field will continue to evolve, and the practices will converge. Rather than a productivity tool primarily used by radiologists, enterprise imaging has the potential to become a platform of communication for the medical community.

Healthcare’s reimbursement model is changing, as is the role of radiologists. Other departments are incorporating radiology equipment into their own practice. Luckily, the adoption of an enterprise approach to imaging technology instead of a narrow focus on radiology will encourage internal collaboration to face external pressures. Care coordination, the cornerstone of the new health care model, will require the exchange of clinical care among providers. The ordering of imaging data, and the reduction of costs and increase in efficiency of managing this, will portend excellent results for the future. Connectivity will help facilitate these leaps forward.

Enterprise Imaging for Clinicians

Enterprise imaging will have different connotations for different specialists. The traditional primacy of radiologists as far as imaging goes will mean that, instead of each department having its own specialty PACS, these disparate systems will be connected in a single electronic patient record. The records of cardiology, oncology, and pediatrics will be radiology. While efforts have been made to smooth the flow of data between different vendors’ software, it is the popularization of VNAs that will expedite connectivity across healthcare enterprises. Imagine it in a similar light to how the Internet suddenly enabled connectivity between millions of people worldwide, despite different operating systems.

Of course, this is not the only advantage for clinicians. Automation of complex imaging workflows, including automatic upload and delivery of images from remote locations, will provide a substantial efficiency boost. Enterprise mobile imaging, ensuring timely access to clinical resources and patient summaries at point of care, will also be a substantial improvement. Mobile medical imaging capabilities mean that clinicians can quickly capture and integrate visible light images, as well as videos and corresponding notes with patient health records. Another substantial boon to clinicians of various stripes in the age of enterprise imaging is the availability of cognitive intelligence and analytics. Some enterprise imaging solutions come with built-in analytics engines, that extract crucial health information from a variety of complex data sources. They can also identify high-risk patients and provide intervention via understanding unstructured clinical notes in appropriate contexts.
From a compliance perspective, well-implemented enterprise imaging platforms are able to securely store and distribute clinical contents in standardized healthcare data formats, while supporting the gamut of clinical specialties. These platforms can also reduce storage costs and provide tools for information life cycle management while offering business continuity solutions and disaster recovery options in the event of catastrophes. Overall, an enterprise imaging platform that is suitably furnished with clinical collaboration and synchronization tools can facilitate substantial leaps forward in efforts towards care personalization and patient-centric service.

Enterprise Imaging for IT Professionals

Building and implementing a successful enterprise imaging platform represents a significant undertaking for an institution. Even a crack in-house IT team may need help from freelancers in order to bring a project to completion.
An IT professional working in a healthcare enterprise should be able to advocate for enterprise imaging as a means of improving patient care and operational efficiency.
  • A patient-centric view of all clinical information on a patient, including images, accessible from the point of care, enables the care provider to make better and quicker clinical decisions. The patient can more easily be kept up to date on their condition and treatment.
  • The availability of imaging data in the electronic health record (and its accessibility by imaging analytics and AI applications) has positive repercussions for macro-level preventative efforts: essentially, managing health on a population-wide level.
  • Lastly, while the initial expense of the shift to a new system should not be entirely discounted, there are also substantial financial savings that can be achieved as a result of consolidating imaging data into a smaller number of repositories. Centralized data management cuts maintenance costs significantly, reducing or entirely eliminating the necessity of data migrations.

Health care costs continue to rise for the average American, and so do their expectations to match the greater dollar investment that they are required to make. A Kelton Global survey conducted in 2016 found that 94% of patients were of the opinion that their medical data and records should be centrally stored and electronically accessible. Patients are used to having their financial details available at their fingertips. They are most often dissatisfied when their personal health records are not similarly easy to access and share.

Enterprise Imaging Challenges

No infrastructural project is without challenges impeding its implementation. When considering individuals’ medical data, there are significant concerns to address.

One of the most pressing is security. Healthcare providers represent significant targets for cyber attackers. Digital security threats are constantly emerging from unexpected avenues. One of the potential downsides of enterprise imaging solutions is that a centralized network, while offering substantial efficiency gains and savings on storage solutions, is more vulnerable to cybersecurity threats than networks acting individually. Cyber attacks can quickly spread malware and compromise vital operations. Security must be taken seriously by any enterprise that implements an integrated care delivery network. If a hacker is able to penetrate a network to interfere with a medical imaging acquisition device, its safe operation can be jeopardized, which in turn endangers patient safety. Organizational cybersecurity requires a unified effort from departmental staff and the rest of the enterprise. In a 2014 statement, IBM identified ‘human error’ as a contributing factor in over 95% of all cybersecurity incidents.

Preventing cybersecurity risks involves a delicate, closely monitored, system of people, processes, and technologies. IT departments must work closely with imaging service lines to develop operational plans and strategies that are practical and robust. Imaging staff must be kept aware of best practices and cybersecurity threats.

Another challenge is the use of different data standards for medical imaging as opposed to non-imaged data. Perhaps the most well-known standard is Digital Imaging and Communications in Medicine (DICOM), which was specially developed by the American College of Radiologists (ACR) and National Electrical Manufacturers Association (NEMA). The DICOM standard applies to imaging equipment, printers, and PACS (now referred to as MIMPS). This format focuses on the workflow of images, as well as provides protocols for the integration of image data. It also allows functions like film printing or CD burning.

HL7 Interoperability in Enterprise Imaging

A format that is seeking wider acceptance is Health Level Seven (HL7), intended for general use of electronic health information in hospitals. This format manages non-imaging data, and provides protocols for exchange, management, and integration of clinical and administrative electronic health data. It allows interoperability between different systems including patient administration, laboratory information systems, billing systems, electronic medical record and health record systems, and more.

Enterprise Imaging and HIPAA

A third major challenge for enterprise imaging is patient privacy. In accordance with federal law, all patient data must be protected and HIPAA-compliant. However, one of the main advantages of enterprise imaging is the possibility of sharing significant data banks with other enterprises for the purpose of medical research, AI training, and similar projects. It is essential that, whenever data sharing is offered, identifying information is stripped away to protect individuals’ medical data. De-identification is the most common method of performing this information removal for DICOM data in Cross-Enterprise Document Sharing (also known as XDS-I). DICOM files consist of the image and the header, which contains meta-elements containing patient information, as well as institution and study data. The patient name and number must be obscured in order to prevent the patient from being identified. Hence, de-identification. There are two main approaches to de-identification: anonymization and pseudonymization. Anonymization is considered to be more secure, as it involves removing all sensitive information from the header. The aim of this method is to irreversibly remove any probability of revealing the patient’s identity. Meanwhile, pseudonymization instead replaces identifying fields in the data record with artificial identifiers. The intention of this process is to make the data record less identifying. However, this process is used when there is considered to be a potential for the necessity of tracing the actual identity of the subject involved. Typically, the principal investigator or data manager of a research project would be able to obtain the real identity of the subject, while direct attempts to identify the patient would be avoided. Fields not necessary to this process are instead anonymized.

Looking Ahead: Enterprise Imaging Innovations

The field of enterprise imaging is one with a great deal of potential, but also challenges to be surmounted. It took the U.S. healthcare industry almost a decade to adjust after its investment in enterprise Electronic Health Records (EHR). What’s more, the changing legislative environment and consolidations of hospital infrastructure have quenched enthusiasm for pursuing the kind of complex implementations enterprise imaging calls for. There are certain departments and care areas that are, as a general rule, more enthusiastic about converting to enterprise imaging than others. Radiology is obviously one of them, but dermatology, non-invasive cardiology, and standard mammography are also typically receptive to the shift. Departments with which progress for the adoption of enterprise imaging is generally less keen include core pathology, genomics, multimedia endoscopy, and oncology. The reasons why vary, but may involve a lack of leadership, a reliance on committee or cross-department decision making, adherence to a broader contract involving non-software equipment and services, or a desire to use a dedicated best-of-breed functionality in a specific care area.

However slowly it spreads, the long term impact of enterprise imaging will be substantial. From small community hospitals to large institutions, enterprise imaging is an essential component of information technology infrastructure that can promote interoperability between different sites. Communication, via image sharing and other means, within the hospital and beyond, is made easier along different points of the care continuum. As a result of healthcare increasingly being absorbed into the cloud, data migrations will become obsolete. This in turn will diminish the image management role of healthcare IT vendors and place more power in the hands of the providers. Vendor neutral data will give providers the freedom to innovate their own solutions to progress, rather than obeying the strictures of the vendors. The most tangible benefit of this shift in imaging structure will be better patient care, by virtue of faster diagnosis and imaging orders.

AI In Enterprise Imaging

One of the biggest innovations that widespread enterprise imaging will facilitate will be the ‘on-ramp’ of artificial intelligence for diagnostics. Thanks to AI, radiologists foresee a future in which machines enhance patient outcomes and reduce misdiagnosis. As more departments and enterprises consolidate their image management into enterprise imaging health systems, AI developers’ ability to source the terabytes of deidentified images necessary to train their machine learning diagnostician algorithms will increase. The ability of machines to, in a split second, assess a mammogram, MRI, or other medical scan and accurately (more accurately than any human diagnostician) diagnose a patient will represent a significant leap forward in the efficiency of medicine as a whole.

Enterprise Imaging Workflow Options

One of the main challenges of an institution converting its multiple imaging sources over to a healthcare enterprise imaging solution such as that which a Vendor Neutral Archive provides is dealing with different workflows that non-radiology departments use. In many cases, these must be reinvented. There are a dizzying number of workflow and integration options. The goal is for these to converge into a few popular ones, as vendor support and standardization push the fittest to the top. The IHE SWF (Scheduled Workflow) profile details the traditional radiology and cardiology workflow, which incorporates Patient Information Reconciliation (PIR). This Procedure Based Imaging Workflow contrasts with what is called an ‘Encounter Based Imaging Workflow’, used by non-radiology and cardiology departments. The difficulty of Encounter Based Imaging is that there are so many options for implementations that it is difficult to be prepared for all of them.

Cloud Computing Solutions for VNA

A Vendor Neutral Archive (VNA) is highly beneficial to the average healthcare enterprise. The ability to switch PACS vendors regardless of image data migration/conversion is highly significant. A cloud-based archive can remove one of the biggest impediments to implementing a VNA: how to store all that data? Data migrations within a cloud are far more painless, and operational and maintenance costs for data storage drop off considerably. There are additional benefits, including flexibility in terms of archive size, and the capability to homogenize data from disparate systems. Data stored on a cloud is much more affordable to recover in the event of a disaster. Furthermore, many solutions are capable of expanding the capability and longevity of a client’s current PACS. Similarly, some options also present the option of easier and more sophisticated de-identification of personal healthcare information contained in DICOM metadata and pixels, protecting your patients’ confidentiality and presenting greater research possibilities for your enterprise and associated labs.

Imaging on Devices

In the time since DICOM became one of the imaging data standards, cell phones and other mobile technologies have gone from being unwieldy and limited-use machines to highly sophisticated personal electronic devices capable of not only communication, but imaging, analysis, and more. A 21st century healthcare organization deserves 21st century solutions to make clinical communication and collaboration easier and more productive. Certain enterprise imaging options on the market also provide opportunities to utilize mobile medical photography and collaboration solutions. These users can capture images, label and organize data, collaborate with colleagues, and import data into the PACS—all while complying with HIPAA and compliance audit reporting. Data is encrypted on devices at all times and transmitted, processed, and stored on encrypted systems. Photos are automatically organized by patient encounters, and all data can be seamlessly integrated into the enterprise’s systems via DICOM or any of the other prevalent data standards. Users are not restricted to capturing medical images, however. They can also use a smart document scanner to scan printed orders. Additionally, they can use the device to search across PACS and EHR systems from a single search field, calling up images for comparison—especially useful, given the functionality of making any device a valid size measurement device. Nicklaus Children’s, a leading pediatric hospital in Florida, has implemented a mobile medical photography and collaboration tool, which resulted in a faster, more intuitive viewing workflow for clinicians. Images captured at the point of care were automatically added to the EHR. This meant that multidisciplinary teams found it far easier to collaborate, thanks to their straightforward access to all types of imaging through the EHR. The vast compatibility of the system meant that all staff were able to use the mobile devices they were comfortable with while at the same time ensuring a compliant and secure remote solution.

Want to see Enterprise Imaging in action? Learn more about the Unifier platform by Dicom Systems.

AI Conductor

Unifier with AI Conductor for PACS and EHR drives and conducts AI workflows to get the right information to the right location at the right time and in the right format.

Learn More

Latest News

Taming the AI Gold Rush

Taming the AI Gold Rush

Is AI a threat to physicians? Is it possible for AI algorithms to make physicians obsolete? Will the robots take over? In the second part of this series, Florent Saint-Clair kiboshes some of the many fears associated with AI. And highlights the many advancements the merging of AI and healthcare has benefitted the industry.

Request Demo

To request an online demo or to learn more about Dicom Systems products, please fill out the form or call us.

Partner & Resellers Program

Dicom Systems has built a global network of premier channel, solution, and technology partners that

FAQ

In 2008, Dicom Systems started with the idea to design a high-performing

Blog

Find out how you can use Unifier to successfully deploy AI algorithms to your PACS and EHR.