November 18, 2020 -- COVID-19 is now everywhere. As a former practicing physician, I can only imagine how this pandemic has been an overwhelming experience not only for healthcare staff and system administrators but also for patients and their loved ones.
The longest weeks of my career have been when I neither traveled nor met in person with our customers and thought leaders. My recent virtual meetings and conversations with industry partners, analysts, and thought leaders at academic institutes and health authorities across the globe have signified the need to reimagine the delivery of care by focusing on "predicting" and "preventing," with an emphasis on catching the disease before it strikes.
There is a growing need to aggregate clinical informatics, population profile, family and social history, wearable device informatics, and pixel intelligence residing in diagnostic imaging. This makes sense and emphasizes the need to intelligently consolidate predictive analytics, artificial intelligence (AI), and machine learning (ML) on a secure platform ecosystem.
However, before we embark upon discussing the outcomes-based application of innovative technologies in healthcare, let's understand what COVID-19 has taught us so far, and how we can better prepare ourselves as we transition out to the "new normal."
The initial phase
While healthcare organizations across the globe have remained under pressure to deliver cost-effective and high-quality care, the COVID-19 challenge has exposed vulnerabilities in terms of how technology has created certain access and information silos.
The pandemic has also exposed the basic premise on which our health systems have been designed. This initial phase of lack of multispecialty data aggregation and systems interoperability posed significant diagnostic challenges.
While COVID-19 was eventually declared a pandemic on March 11, the impact on the diagnostic role of radiology was already being reimagined.
The pandemic
As COVID-19 spread globally, there was growing interest related to the role of diagnostic imaging and the appropriateness of chest x-rays and CT scans when it comes to screening, detection, and follow-up management.
While the appropriateness of chest x-rays or CT scans to pinpoint COVID-19 pneumonia was being evaluated, a group of experts in Italy had been busy exploring the benefits of bedside ultrasound as one possible alternative for the detection of COVID-19 pneumonia.
There were also initial reports that some technology startups were evaluating their machine-learning algorithms and developing new models to detect COVID-19-specific findings, leveraging chest x-rays and CT scans.
The bottom line is that radiologists within the healthcare system and outside their enterprise were struggling to exchange useful imaging data with their international colleagues in their quest for collaborative learning and understanding of this new disease.
The transition
The phase of transitioning out to the "new normal," or the postpandemic environment, will provide critical lessons learned in relation to how health systems prepare themselves before returning to business as usual.
Radiology departments, while they have seen significant decline in certain diagnostic procedures due to the focus on COVID-19-related hospital visits, with the need to work remotely and in self-isolation, have also mandated the need for secure and modular industrial-scale enterprise PACS solutions.
It was obvious that while COVID-19 was being evaluated from a diagnostic radiology perspective, COVID-19-related AI initiatives would pop up as well. While there have been a few initiatives that are still works-in-progress, one thing's for sure: The utility of AI within existing PACS systems will require workflow integration, and that's where I see Agfa HealthCare standing out with its powerful rules-based workflow engine.
At Agfa HealthCare, because we had purposely built our Enterprise Imaging platform for modularity, we have seen several successes during this pandemic, at short notice, fulfilling requests of our customers ranging from at-home workstation setup, image exchange, and real-time collaboration to 100% remote-supported go-lives.
The new normal
We do not know yet what the new normal will look like; however, I think we do agree on the fact that COVID-19 has exposed not only the vulnerabilities in our healthcare system, its operations, and infrastructure setup but also the need for radical change in how we deploy secure and modern platform ecosystems.
Clinicians were already overwhelmed with data. It's now time to implement solutions that automate their workflows, improve productivity, provide analytical intelligence in outcomes measurement, and help offer optimized tasks that machines and software are better programmed to do.
1. Patient-centered view cross-enterprise
An Enterprise Imaging solution should provide a universal view of patients' multispecialty imaging timeline and journey. With COVID-19, patients may have been followed up over the duration of their care pathway with x-rays, CT scans, and in some cases portable devices like point-of care-ultrasound scanners.
2. Secure, multispecialty real-time communication and collaboration
Whether sharing imaging data within the enterprise or the need for collaboration with external expertise, the silos of imaging solutions have posed security, integration, and interoperability challenges when it comes to multidisciplinary team meetings. Because Agfa HealthCare builds its tools and applications on a modular platform ecosystem, our customers have enabled on short notice onsite and offsite image exchange and real-time chat and collaboration capabilities based on native tools available on the platform.
This allows our customers not only the privilege of sharing patients' diagnostic imaging data in a secure environment between colleagues working in the hospital or at home but also the ability to engage external expertise when needed. The XERO Viewer, our zero-footprint diagnostic viewer, enables collaboration inside and outside the hospital as chat and communication tools let physicians and radiologists look at the same image while communicating securely in real-time.
3. Faster reporting: Remote, at home, or on premise
To deal with the COVID-19 outbreak, the continuity of radiology reporting activities is crucial. To guarantee this, care providers are expanding the remote reporting capabilities for their radiology teams. In Ireland, one of our clinical application specialists was approached by a radiologist who was concerned about being able to work should the need to self-isolate arise. The hospital already had a VPN connection available as well as spare hardware, and within 20 minutes of assembling the spare clinical review workstation and a clinical monitor, the radiologist was able to log in, use his own profile from the hospital, and report in his own home, including full speech recognition, with images instantly available over a normal broadband connection.
With new diseases comes new terminology. Since they are not standard in the radiology lexicon, we received feedback from some radiologists that their speech recognition software for fast reporting was struggling with the recognition of new terms like "corona" or "COVID-19." This was slowing down the reporting turnaround, since repeated manual correction of the unrecognized terms was needed. Our customers in Belgium and Luxembourg, using Enterprise Imaging integrated with the Nuance Speech Magic recognition software, have quickly retrained their Nuance speech recognition systems and added those new terms to the speech lexicon.
4. Rules-based workflow, triage, and task optimization
The power of the Enterprise Imaging platform and modularity rests on its capabilities to adapt to varying demands of hospital systems that differ across the globe.
5. Augmented intelligence: Using data to better measure, predict, and take action
Our customers are already thinking ahead and exploring use cases to leverage our rules-based workflow engine to practically implement image-based AI/ML algorithms not only for clinical use, but also to enable a framework of collaboration leveraging our academic and teaching workflows.