Literature Review

Digital avatars and personalized voices—How AI is helping to restore speech to patients JAMA Network, by Samantha Anderer and Yulin Hswen, ScD, MHP; 3/22/24 This conversation is part of a series of interviews in which JAMA Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, and expert guests explore issues surrounding the rapidly evolving intersection of artificial intelligence (AI) and medicine.  As a specialist in advanced brain mapping methods, Edward Chang, MD, set out to understand the mechanisms that turn our thoughts into words. Now, with the help of AI, his team at the University of California, San Francisco (UCSF) Weill Institute for Neurosciences has demonstrated that the brain signals associated with speech-related sensory and motor processes could grant a new voice to patients who have lost the ability to speak.

AI scribe saves doctors an hour at the keyboard every dayAMA, by Andis Robeznieks; 3/18/24 When a health system rolls out new technology that it insists will make physicians’ lives easier, the announcement is typically met with skepticism. But the use of augmented intelligence (AI)—often called artificial intelligence—has changed that. The Permanente Medical Group’s rollout of ambient AI scribes to reduce documentation burdens has been deemed a success, saving most of the physicians using it an average of one hour a day at the keyboard. ... Refinement of the tool, however, is ongoing. ... For example, one physician mentioned scheduling a patient’s prostate exam, but the AI scribe recorded that the exam had been performed. 

Give generative AI another decade to revolutionize healthcare Modern Healthcare - Opinion, by Keith Figoli; 3/15/24... Generative artificial intelligence is poised to transform healthcare by enabling solutions to effectively address [common patient care] challenges. This cutting-edge technology opens new avenues for innovation in diagnosis, treatment planning, operations efficiency and overall healthcare delivery–and industry leaders are taking notice. A recent survey revealed that 25% of healthcare organizations implemented a generative AI solution in 2023, while 58% plan to adopt one this year. However, the generative AI-driven transformation won’t – and shouldn’t – happen overnight.

Are the robots coming for my nursing job? Minority Nurse; 3/20/24 While medication-dispensing robots, telemetry, electronic fetal monitoring, artificial intelligence, and other technological advances have altered our work as nurses, fears that robots will replace us and send nurses into the historical career dustbin are likely unfounded. ... The human side of nursing is the art that maintains the sacredness of the nurse-patient bond. Nursing may be partially driven by plans of care developed within the parameters of the nursing process, but where the rubber hits the road is where person-to-person interaction informs the patient experience and the nurse’s calling.

Use of machine learning to optimize referral for early palliative care: Are prognostic predictions enough  Journal of Clinical Oncology - Editorials; by Gary E. Weissman, MD, MSHP; Joseph A. Greer, PhD; and Jennifer S. Temel, MD; 3/15/24  The Takeaway In the article that accompanies this editorial, [Weissman] et al used a machine learning (ML) algorithm to identify patients with advanced cancer who were receiving non–curative-intent treatment and at risk of death within 1 year to allocate early palliative care services at least 6 months before death as a means to increase use of early palliative care in the context of limited resources. While ML prognostic models are one promising strategy for triaging palliative care services, initiation of palliative care based exclusively on estimated survival and in the months before death likely excludes patients who would benefit from early palliative care initiated at the time of diagnosis, regardless of their estimated survival.

Google Cloud releases new clinical generative AI tools at HIMSS24MedCity News, by Katie Adams; 3/12/24 At HIMSS, Google Cloud announced new AI features designed to assist providers, payers and any other healthcare organizations seeking to make better use of their clinical data.

What are important ethical implications of using Facial Recognition Technology in health care? AMA Journal of Ethics, by Nicole Martinez-Martin, JD, PhD; orig post 2/24, redistributed 3/13/24Applications of facial recognition technology (FRT) in health care settings have been developed to identify and monitor patients as well as to diagnose genetic, medical, and behavioral conditions. The use of FRT in health care suggests the importance of informed consent, data input and analysis quality, effective communication about incidental findings, and potential influence on patient-clinician relationships. Privacy and data protection are thought to present challenges for the use of FRT for health applications.

Healthcare technology regulatory update - March 2024 JD Supra, by Justin Chavez and Vimala Devassy; 3/8/24Federal and state agencies are actively proposing and enacting health technology-related legislation and regulations. 

Seniors more likely to let conditions escalate into emergency if their only care options are digital, poll finds McKnights Senior Living, by Aaron Dorman; 3/7/24 Although residents in senior living communities and nursing homes are becoming more accepting of artificial intelligence and other tools such as remote monitoring systems, that doesn’t mean they don’t still strongly prefer human caregivers to manage their healthcare needs, a recent poll finds. ... Among older adult survey respondents who had dealt with a recent emergency, 33% said that they felt as if the incident could have been averted if they had had access to a live, in-person caregiver to manage their health concerns and needs.

Understanding the role algorithms play in our lives and navigating palliative careListen - Life Matters, by Hilary Harper, presenter podcast; 3/4/24Every day, we interact with dozens of algorithms as we go about our lives, but many of us don't understand how they work. How do we get the the best out of these tools while keeping the potential dangers in check?Editor's Note: From palliative care experts Australia; information about algorithms and Artificial Intelligence (AI) transfers to our USA palliative care (of course, without applications to CMS systems).

The future of end-of-life care: How advanced directives are revolutionizing patient autonomyBNN, by Mazhar Abbas; 2/23/24Discover hos advanced directives leverage AI, telemedicine, and patient-centered care to empower individuals in making informed end-of-life healthcare decisions, overcoming challenges, and shaping the future of healthcare.

Health systems bucking IT outsourcing trend Becker's Health IT, by Naomi Diaz; 2/19/24The role and size of information technology departments within health systems play a crucial role in shaping the organization's technological infrastructure. And despite a growing trend toward outsourcing IT functions, many health systems continue to maintain robust in-house teams.

AI-generated clinical summaries require more than accuracyJAMA Network; by Katherine E. Goodman, JD, PhD; Paul H. Yi, MD; and Daniel J. Morgan, MD, MS; Originally published 1/29/24, redistributed 2/20/24 ... Currently, there are no comprehensive standards for LLM-generated [Large Language Model] clinical summaries beyond the general recognition that summaries should be consistently accurate and concise. Yet there are many ways to accurately summarize clinical information. Variations in summary length, organization, and tone could all nudge clinician interpretations and subsequent decisions either intentionally or unintentionally. To illustrate these challenges concretely, we prompted ChatGPT-4 to summarize a small sample of deidentified clinical documents. [Click on the title's link to view the example.]