As we move toward an emphasis on precision medicine and population health management, we’ve come to understand the central role imaging can play – whether it’s accelerating time to treatment, treating at a lower cost or with higher diagnostic precision. However, today’s radiology departments face many hurdles with less resources and less time than ever before. To compound this pressure, healthcare organizations are being assessed in a value-based care world in which an investment in advanced imaging technology must be balanced with the ability to demonstrate ROI. In light of this, here are three of the biggest trends in imaging that I believe will impact radiology departments in significant ways in 2019 and beyond.
Broader adoption of technology that enables precision diagnostics
In radiology, our goal has always been to overcome imaging obstacles so that we can improve diagnostic confidence and streamline workflows to improve patient care and staff efficiency. Recent technology advancements such as Spectral CT are doing just that. Spectral CT allows radiologists to make a definitive diagnosis using low-contrast imaging to get even more insights than conventional CT at a low radiation dose. For example, Philips IQon Spectral CT
applies spectral technology 100% of the time, which gives radiologists the ability to find lesions that aren’t visible with ordinary scans – lesions they may not have even been looking for that may be significant in determining a patient’s diagnosis.
There are benefits for both patients and healthcare organizations in eliminating the guess-work in image reading with Spectral CT. At the same time, it is a major workflow advancement, leading to fast procedures and enhanced diagnostic confidence.
Greater emphasis on total-cost-of-ownership (TCO) value
The balancing act of cost and value is playing an increasing role in purchasing decisions of imaging technology. Beyond finding the right technology for your specific needs and workflow, it is now arguably equally as important to identify the right partner who provides long-term strategy and value. Radiology administrators need to ensure that imaging technology not only works effectively, but that their technologists are adequately trained on the technology, protocols are standardized to obtain consistent images, they know who to call if service is needed, and that the technology can easily be upgraded down the road. Vendors need to create reliable, scalable solutions, while proving their ability to reduce TCO end-to-end.
This TCO mindset is in the context of the growing focus on quality as we transition to value-based care. In years past, CT suppliers were solely selling a boxed solution, and healthcare organizations only considered the technology’s quantitative specifications. Today, what is in the box is only part of what they are purchasing – they are looking for a partner to provide integrated solutions, workflow advancements and quality improvements on top of the box offering. There is a shift in the mindset on savings; it is broadened to total cost of care.
Expanded use of AI in Clinical Decision Making
There is much discussion around the hope and hype of artificial intelligence (AI) in radiology, and its ability to enhance clinical decision making, especially in a practice when clinicians are overburdened due to resource shortages and staff burnout. We are already starting to see AI augment the radiologist’s role in tangible ways, such as improving operational efficiency and diagnostic confidence, and we can only expect that momentum to continue in 2019 and beyond.
AI can help improve workflow which results in savings for the hospital because it enables staff to provide high quality service to more patients more efficiently. At Philips, we believe that applying AI to healthcare and personal health requires a deep understanding of the clinical, operational, or personal context in which such methods are used. We use the term “adaptive intelligence” to talk about applying artificial intelligence
in a meaningful way that improves people’s lives. AI-enabled solutions can help to combine large amounts of medical data to generate a more holistic view of patients. This supports clinicians in their decision making, leading to better patient care and improved population health.