Digital health executives share their predictions on how artificial intelligence (AI) will continue to shape the healthcare industry in 2022.
Diana Nole, EVP and GM of Healthcare at Nuance Communications, Inc.
AI will find more game-changing use cases – According to Optum’s fourth annual survey on AI in healthcare, 96% of respondents said AI plays an important role in increasing health equity, and 94% said they have a duty to ensure AI is used responsibly in healthcare. As healthcare organizations and researchers establish strong standards for the secure sharing of healthcare data, new collaborative AI projects are set to drive more informed care decisions.
Brian Foy, Chief Product Officer at Q-Centrix
Artificial Intelligence (AI) and Natural Language Processing (NLP) are here to stay, not to replace clinical experts, but rather as an augmentative tool, making clinicians more efficient. Hospitals will play a crucial role in fostering innovation in this area by partnering with companies that are committed to developing these automation tools and getting greater leverage from clinical data.
Ari Kamlani, AI Solutions Architect / Senior Data Scientist at Beyond Limits
Healthcare has changed dramatically over the past few decades with innovations in brain scanning technology, disease diagnosis, cancer treatment, and much more. In 2022, some of the latest and most impressive innovations on the healthcare industry’s horizon are emerging from the technology field – particularly artificial intelligence. This pattern is similar to what we have seen in other regulated, risk-averse industries, such as the fintech industry.
In the coming years, Responsible AI solutions will aid physicians with their decision-making in a trustworthy, fair, and safe manner – dramatically reducing the time they spend deciphering data. This not only guides doctors towards improved patient outcomes, but allows for more quality time to spend with their patients.
Mark Day, EVP of R&D at iRhythm
Bias in AI: Within the next year, AI companies will continue to improve data collection methods and develop processes that avoid bias in algorithm training and, in turn, performance in the intended population. Specifically, improved clinical study design will foster more heterogeneous and representative patient populations, resulting in algorithms that reduce bias.
On the technical side, methods will develop to provide greater insight into the “black box” of AI algorithm decisions, which will guide understanding into whether these decisions represent bias based on factors including race, gender and age.
Mark Olson, CEO of RecoveryOne
AI will be used to deliver even more personalized interventions. Augmented and virtual reality in MSK will use familiar devices such as smartphones and laptops, rather than proprietary hardware and sensors, that cause friction in the consumer experience.
Gaurav Kaushik, Ph.D., Co-Founder and President of ScienceIO
Natural language processing is at an inflection point, but still needs to mature in the healthcare industry. Healthcare-specific NLP will come of age in the next several years as the technology advances we made in media and finance will translate into healthcare, be more widely available, and act as an accelerant for patient-centric solution development across the industry.
Dr. Trishan Panch, Co-Founder of Wellframe
Health providers and insurers will use AI in a wide variety of contexts in 2022. They will see the best results in a hybrid context, where they can leverage the human ability to generate hypotheses and collaborate by combining it with AI’s ability to analyze large volumes of data to optimise for specific, well-defined criteria. Health systems should not look at AI like a medical device, but more as a resource for information. To properly apply AI within clinical workflows, health systems will need to hire AI specialists or clinicians to maintain its quality and safety.
Calum Yacoubian, MD, Associate Director, Healthcare Strategy, Linguamatics, an IQVIA Company
We have reached an inflection point for the adoption of tools such as natural language processing (NLP) that help organizations manage large sets of unstructured data. One factor driving demand for such technologies is the pending Patient Access rule deadline requiring the interoperability of full-text medical records. Payers particularly recognize that they will soon be flooded with unstructured data that must be managed to effectively inform patient care, meet value-based care goals, and drive predictive algorithms that improve outcomes. The growing presence of big tech and cloud vendors in the text analytics space has also raised overall awareness about these tools, which are increasingly available for easy and convenient consumption through cloud-based approaches instead of large-scale software deployments. Finally, the pandemic has impacted healthcare in many ways, including increased acceptance and demand for cloud-based technologies, which have enabled users to access and manage data remotely. The pandemic has also highlighted the need to look beyond structured data and use tools like NLP to understand and address social determinants of health factors that lead to inequitable outcomes across populations.
Art Papier, M.D., Chief Executive Officer of VisualDx
In 2022, the tremendous hype around artificial intelligence in medicine will start to wane and digital thought leaders will begin to have more realistic expectations (at least that’s my hope), realizing that clinical decision making needs augmented intelligence, not artificial intelligence. Focus will move to collaborative processes, ongoing education and information tools that guide and teach. The crushing professional labor shortage will necessitate better tools, particularly visualization decision support systems that educate as they are used.
