Physician leaders from Pieces, Amazon Web Services, and LeanTaaS share insights on how AI can maximize its impact for clinicians with natural language processing and natural language generation
DALLAS, Aug. 16, 2022 /PRNewswire/ — Pieces, a healthcare AI company, recently convened an industry roundtable with physician leaders to reflect on the current state of AI and how it is supporting physicians, nurses, and care teams. The roundtable participants shared their perspectives from both practicing in the field and working with healthcare IT companies to drive much-needed change for healthcare professionals. The consensus was that while AI has made great strides in recent years, it is ready and able to make a deeper impact on the day-to-day work of clinicians, as well as to drive a strategic shift towards re-empowering clinicians to focus more on patients and less on administrative tasks.
The roundtable participants included:
Ruben Amarasingham, MD, Founder and CEO, Pieces
Mark Michalski, MD, Worldwide Head Healthcare and Life Sciences for AI and machine learning, Amazon and Amazon Web Services (AWS)
Jim Ritchie, MD, Consultant Renal Physician and CCIO at The Northern Care Alliance NHS Foundation Trust
Pallabi Sanyal-Dey, MD, FHM, Director of Client Services, Inpatient Beds, LeanTaaS
“AI is beginning to help clinicians with the care and treatment of patients but we really are in the first inning here,” said Dr. Amarasingham. “This roundtable discussion reflects the increasingly expressed hope that AI can bring back the joy and delight into the practice of medicine, enabling clinicians to spend all of their attention on the patient.”
Key takeaways from the roundtable included:
AI has the potential to vastly reduce charting and EMR friction that has bedeviled healthcare for decades: “One of the most exciting areas for me, coming from a clinical world, is how advancements in artificial intelligence (AI) and machine learning (ML) will help reduce the burden on medical professionals,” said Dr. Michalski. “Our providers have had a tremendously difficult two years, and beyond the stress of increasing patient volumes, they are also grappling with alert and documentation fatigue. An exciting near-term goal is to streamline repetitive charting activity with predictive AI – and the ultimate goal is to modernize clinical documentation and charting activities altogether. This will free up medical practitioners’ time from critical yet repetitive tasks, and help them focus on patient care.”
Dr. Amarasingham agrees. “There is an increasing focus on AI systems and methods that can take over the documentation and communication tasks physicians have been saddled with since the advent of EMRs. For example, systems can summarize a medical record or a complicated patient history, reducing the time a physician may have to read a record or prepare a summary.”
AI and NLP can help cure healthcare’s workforce crisis by driving efficiency and supporting retention: “The NHS has recognized that more staff are leaving the field than ever before and has committed to taking action,” said Dr. Ritchie. “Staff retention is a top priority. If we can apply AI to enable a better staff experience that is less about administrative tasks and more about safely looking after patients, it will make a difference. Similarly, if AI can help clinicians to increase the efficiency of their work with automation, they will be able to look after more patients which is a win for both organizational efficiency and our staff’s quality of their working experience.”
NLP is making a difference and will make an even bigger impact as it continues to evolve: “In the last 5 years we’ve seen a significant development in NLP and speech recognition technology,” said Dr. Michalski. “We’ve seen huge step changes in the capabilities of AI in those models and technologies, and I think those are making the most progress.
Dr. Sanyal-Dey sees the promise of NLP as well. “I’m most excited about the NLP arena—and really fine- tuning that functionality so that it allows physicians to not spend their time reading non-relevant information but rather focusing on what they need to make clinical decisions. NLP can help assign role-appropriate tasks so that everyone’s time is spent most efficiently. Case managers are doing true case management and nurses can do nursing,” she said.
Dr. Amarasingham commented, “I’ve heard John Bohannon say: ‘It used to be, software is eating the world; then ML is eating software; and now NLP is eating ML.’ That certainly feels real to me when I look at healthcare AI. NLP, and now NLG, has great power for healthcare”
Some physicians are still skeptical but others are eager to embrace AI and experience the benefits: “Skepticism absolutely remains – whenever change is introduced, especially in healthcare, because of the way we do things,” said Dr. Sanyal-Dey. “I have seen people who are quite positively taken aback and impressed by what AI and machine learning can do, but it will take time for everyone to get there. After all, there’s an element of trust because it’s new data, new recommendations, and healthcare workers must be able to trust what they see and do. The human element is needed to balance everything else that is being captured.”
Dr. Amarasingham however also emphasizes that many physicians are ready to adopt AI. “My discussion with physician colleagues is that they are hungry for advances in AI to be applied to their work to make their lives easier and their patient’s outcomes even better,” said Dr. Amarasingham. “There is enormous complexity and information in medicine and many physicians would like tools that make it easier to do their work, manage routine items, and reduce cognitive overload similar to what they see their smartphones doing in their lives outside of medicine.”
“So much of the discussion about AI has been focused on predictive modeling or risk scores but AI must also be about helping me to get work done rather than giving me another number to think about,” said Dr. Ritchie. “Helping clinicians to get work done, like streamlining the clinical handover process, improves operational efficiency and much more. It’s an easier fix than the strictly clinical use cases and more appreciated in many ways.”
Healthcare organizations are finding new ways to accurately evaluate AI technology, like dedicated sandbox environments: “Most healthcare organizations are not adept at evaluating AI technology, “said Dr. Ritchie. “They often lack a structured approach to evaluating features and usability outside of foundational technical requirements like cybersecurity essentials. But standards still cannot inform whether an AI technology will work in your environment, if it is the right tool for your technology infrastructure, or whether the training group is representative of the population you serve. That’s why we’re exploring building a sandbox environment for AI vendor testing. Even though that is costly and time-consuming, it is important.”
The future is bright for healthcare AI in the near-term and for decades to come: I’m looking forward to technology like AI and machine learning allowing clinicians to spend their critical thinking time on a patients’ medical issues,” said Dr. Sanyal-Dey. “Giving clinical care the space that it needs, without the clutter of administrative tasks, will free up brain space to think about our patients better.”
As for Dr. Michalski, he sees talking about AI less as the future goal. “I’m hoping for a day, not too far from now, where we’re talking about AI and ML less because we’ll be able to incorporate AI and ML seamlessly from a product and workflow standpoint. We will view AI as a feature of a successful product as opposed to being a talking point. When that happens, the natural and healthy skepticism of the physician world about AI and ML will fade away because the product works seamlessly and improves efficiency significantly. We’ve seen that happen in imaging, it’s no longer an AI tool, it’s an effective tool that helps improve patient care”
Dr. Amarasingham notes that future iterations of AI systems will become more anticipatory. “AI will become a clinically holistic assistant to physicians, like having a really great intern to help with things,” he said.
Pieces, Inc. is a healthcare artificial intelligence and technology company that connects health systems and the community to address clinical and social determinants of health through community networks and intelligent software and services. Our solution interprets patient information in real-time and connects health systems and community-based organizations to support healthier outcomes, both inside and outside of hospital walls. Using cloud-based artificial intelligence with clinically-based natural language processing (NLP) and physician-supervised machine learning, our tools help streamline clinician workflows and improve patient outcomes.
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SOURCE Pieces, Inc.
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