As the adoption of AI tools continues to grow, so does the possibility of making major leaps in healthcare delivery. Artificial intelligence is already having significant clinical impacts, notably in cancer detection, and we are just beginning to tap its transformative potential.
The current landscape is marked by an overwhelming array of disconnected AI-enabled point solutions that operate within silos. In radiology, for instance, imaging systems are separated from the radiologist informatics layer, and each have their own separate workflows. Lack of integration limits the potential for data utilization and creates interoperability challenges, which lead to operational inefficiencies and added pressure on care teams.
Better integration is needed, not only to address workflow and data challenges, but also to drive adoption and harness new care delivery opportunities. To realize this vision requires both an end-to-end approach that embeds AI throughout the entire care journey and cloud-native solutions that integrate AI deep with the modality. The way to do this is through connected AI-powered informatics and smart technologies.
Sham Sokka
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An integrated, cloud-native informatics layer across the care continuum is step one. In radiology, this unifying layer would connect the entire clinical and operational workflow – from patient registration through image acquisition to reporting, including collaboration with other physicians. End-to-end AI-powered informatics ensure ‘right place, right user, right time.
First, the ‘right place’ means deeply embedded within the technologies and settings where most needed. The ‘right users’ means customized workspaces for everyone in the workflow, with targeted views to support them in their individual roles and a single patient view – accessible to all in a connected and secure environment. Lastly, ‘at the right time’ means bringing AI in to help when needed – for example, with workflow automation or clinical assistance.
Smart technologies to enhance clinical and operational efficiency
Embedding AI-powered informatics across workflows and with modalities like mammography or MRI systems gives both patients and care teams better experiences. This is the definition of smart technologies.
Smart technologies are ‘disruptive’ only in the sense that they make major care breakthroughs possible. Because smart technologies integrate seamlessly with existing workflows and healthcare IT systems, they are not disruptive for the people delivering care. Rather, they relieve pressure by enabling more streamlined and efficient workflows.
There are no extra clicks or added complexity for radiologists and care teams. Instead, integrated smart technologies would help create a more seamless clinical and operational environment, with AI assisting along the way to enable a better experience for everyone – those delivering care and those receiving it.
Better care experiences for patients
Patients can expect better care experiences with smart technologies. In radiology, by integrating the acquisition workflow – the imaging – with the interpretation workflow, patients would receive a faster readout and potentially a same-day diagnosis. Acquisition time is shortened because the informatics layer postprocesses the imaging in real time, rather than having to postprocess later.
Take breast cancer detection, for example. Integrating AI deeply with the mammography system can not only speed up and improve the process but create new possibilities. This represents a huge leap forward in cancer detection. Imagine getting a complete AI-powered readout from a breast exam in minutes. Patients would no longer have to deal with the stress of waiting for results. Those with no diagnostic findings could leave their appointment with peace of mind, knowing they are cancer-free. And for patients with screening findings, they could know right away and could begin their diagnosis and treatment journey.
Partnering to leverage smart technologies
By embedding AI with medical devices and the equipment used in clinical settings, smart technologies remove the need for care providers to struggle with integration. This accelerates AI adoption and presents great potential to transform healthcare. However, it requires strategic collaboration between health technology companies and medical device manufacturers that focus on integrating AI deep into modalities. These collaborations can unlock the full potential of AI, transforming traditional medical technology into intelligent tools that enhance patient outcomes and improve care delivery. Moreover, as these partnerships evolve, they pave the way for a future where AI-driven innovations become the standard of care in the medical field.
The future of smart technologies is now
Smart technologies show great promise in bringing AI-powered clinical imaging support to breast cancer screening by embedding imaging informatics into advanced mammography systems. But what if we bring the AI-powered informatics layer closer in ultrasound? Or in x-ray, where smart technologies open the possibility of autonomous x-ray.
We already see the incredible potential of AI in real-world clinical settings. To make good on this promise will mean doubling down and partnering on AI-powered informatics and smart technologies to drive industry-wide adoption and, ultimately, revolutionize healthcare.
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