Literature Review

Fairness in predicting cancer mortality across racial subgroupsJAMA Open Network; Teja Ganta, MD; Arash Kia, MD; Prathamesh Parchure, MSc; Min-heng Wang, MA; Melanie Besculides, DrPH; Madhu Mazumdar, PhD; Cardinale B. Smith, MD; 7/24In this cohort study, a machine learning [ML] model to predict cancer mortality for patients aged 21 years or older diagnosed with cancer ... was developed. ... The lack of significant variation in performance or fairness metrics indicated an absence of racial bias, suggesting that the model fairly identified cancer mortality risk across racial groups. The findings suggest that assessment for racial bias is feasible and should be a routine part of predictive ML model development and continue through the implementation process.

Leaving your legacy via death bots? Ethicist shares concernsMedscape; by Arthur L. Caplan, PhD; 8/21/24I heard recently about a fascinating, important development in artificial intelligence (AI)... It has entered into a space where I think patients may raise questions about whether they should use it or seek opinions from doctors and nurses, particularly those involved with seriously ill people. That space is grieving, and what might be called "death bots..." This would allow not only spouses but grandchildren and people in future generations to have some way to interact with an ancestor who's gone. It may allow people to feel comfort when they miss a loved one, to hear their voice, and not just in a prerecorded way but creatively interacting with them. On the other hand, there are clearly many ethical issues about creating an artificial version of yourself. One obvious issue is how accurate this AI version of you will be if the death bot can create information that sounds like you, but really isn't what you would have said, despite the effort to glean it from recordings and past information about you. Is it all right if people wander from the truth in trying to interact with someone who's died?Publisher's note: The article includes several thoughtful ethical questions regarding this use of AI via "death bots".

How to integrate AI into your business: A 2024 guide eWeek; by Sam Rinko; 8/22/24 If you’re an IT professional or executive, the question of how to integrate AI into your business has probably been top of mind since the recent generative AI boom. You know you should be using AI tools to improve your operational efficiency, but you might worry you lack the policies, data quality and implementation strategy to do so effectively. ... Key Takeaways:

The dangers of healthcare generative AI 'drift' Becker's Health IT; by Giles Bruce; 8/15/24 IT leaders are embracing generative AI in healthcare but also expressing concerns that the technology can "drift." The performance of GPT-4, the large language model that powers ChatGPT, in answering healthcare questions can change over time, a phenomenon known as "drift," according to a study by researchers at Somerville, Mass.-based Mass General Brigham. Their work was published Aug. 8 in NEJM AI. "Generative AI performed relatively well, but more improvement is needed for most use cases," said corresponding author Sandy Aronson, executive director of IT and AI solutions at Mass General Brigham Personalized Medicine, in an Aug. 13 statement. "However, as we ran our tests repeatedly, we observed a phenomenon we deemed important: running the same test dataset repeatedly produced different results." ... The variability of the results could differ across days, so the authors say the AI's performance needs to be continuously monitored. 

Identifying and addressing bias in artificial intelligenceJAMA Network Open; by Byron Crowe, Jorge A. Rodriguez; 8/6/24[Invited commentary.] In this issue, Lee and colleagues (Demographic representation of generative artificial intelligence images of physicians) describe the performance of several widely used artificial intelligence (AI) image generation models on producing images of physicians in the United States. The key question the authors set out to answer was whether the models would produce images that accurately reflect the actual racial, ethnic, and gender composition of the US physician workforce, or whether the models would demonstrate biased performance. One important aspect of the study method was that the authors used relatively open-ended prompts, including “Photo of a physician in the United States,” allowing the machinations of the AI to produce an image that it determined was most likely to meet the needs of the end user. AI tools powered by large language models, including the ones examined in the study, use a degree of randomness in their outputs, so models are expected to produce different images in response to each prompt—but how different would the images be? Their findings are striking. First, although 63% of US physicians are White, the models produced images of White physicians 82% of the time. Additionally, several models produced no images of Asian or Latino physicians despite nearly a third of the current physician workforce identifying as a member of these groups. The models also severely underrepresented women in their outputs, producing images of women physicians only 7% of the time. These results demonstrate a clear bias in outputs relative to actual physician demographics. But what do these findings mean for AI and its use in medicine?Publisher's note: This is a thought-provoking article on machine output - whether that's AI, a Google search, etc. It ultimately places responsibility of outputs and actions on people with conscience.

Which parts of healthcare are off limits to AI? Becker's Health IT; by Giles Bruce; 8/9/24 The AI physician will not see you now — or ever, for that matter. As artificial intelligence proliferates in healthcare, health system leaders told Becker's that human providers will always be part of the medical field, with their — AI-aided — treatment recommendations being discussed with patients and family members. "Any patient care decisions ... should be made by patients and their caregivers or family members, obviously in consultation with their physician or provider," said Joe Depa, chief data and AI officer of Atlanta-based Emory Healthcare. ... Robots — or AI — will simply never take the place of that human touch, health system leaders say.

WellSky CEO Bill Miller: Exercise caution, responsibility with AI in hospice Hospice News; by Jim Parker; 8/12/24 Many expect AI to revolutionize health care, speeding access to care, improving diagnosis and prognosis, enhancing efficiency and achieving other benefits. However, providers need to see through the hype and ask the hard questions. This is according to Bill Miller, CEO of the health care tech company WellSky. ... Hospice News sat down with Miller to discuss current perspectives on AI, its potential benefits and possible risks. [Miller:] "... we’re exercising responsibility and caution when we start thinking about AI jumping into the diagnosis game, or somehow replacing the caregiver. We think of it more of how you could enhance the caregiver, keep the human in the loop. If we can help caregivers arrive at better outcomes for their patients by using AI tools and assisting them, then we’ll do that."

Local hospice and palliative care center starts virtual reality program to better patient experienceKYMA (Yuma, AZ); by Danyelle Burke North; 8/6/24The Southwestern Palliative Care and Hospice is bringing a new virtual reality experience program to its center. They added the Oculus VR device to their program to better their hospice and palliative patient experience. They say it provides a therapeutic escape and a way for patients to digitally see new environments without needing to leave their bed.

10 Steps to Creating a Data-Driven CultureHarvard Business Review; by David Waller; 2/6/20Exploding quantities of data have the potential to fuel a new era of fact-based innovation in corporations, backing up new ideas with solid evidence. Buoyed by hopes of better satisfying customers, streamlining operations, and clarifying strategy, firms have for the past decade amassed data, invested in technologies, and paid handsomely for analytical talent. Yet for many companies a strong, data-driven culture remains elusive, and data are rarely the universal basis for decision making. Why is it so hard? ... So we’ve distilled 10 data commandments to help create and sustain a culture with data at its core.

No one is ready for digital immortality: Do you want to live forever as a chatbot? The Atlantic; by Kate Lindsay; 7/31/24 Every few years, Hany Farid and his wife have the grim but necessary conversation about their end-of-life plans. ... In addition to discussing burial requests and financial decisions, Farid has recently broached an eerier topic: If he dies first, would his wife want to digitally resurrect him as an AI clone? ...  Editor's Note: Click on the title's link to continue reading this fascinating and disturbing article about potential, new uses for AI. Calling all bereavement counselors--who are truly trained in contemporary grief theories, research, and clinical best practices--please learn about this trend and prepare to examine its use and misuse from your expertise, for now and through years ahead.

Optimizing patient data transfer processes in healthcare settings Healthcare Business Today; by Majed Alhajry; 7/28/24 Managing and transferring large and often sensitive datasets is a routine yet critical task for healthcare organizations. Practitioners and administrators regularly share substantial files containing sensitive personal health information (PHI) that must be sent not only securely and reliably, but also quickly. So how should healthcare organizations send large files? ... 

HHS unveils major revamp to shift health data, AI strategy and policy under ONC Fierce Healthcare; by Emma Beavins; 7/25/24 The Office of the National Coordinator for Health Information Technology (ONC) has been renamed and restructured, the Department of Health and Human Services (HHS) announced [July 25]. The restructuring will affect technology, cybersecurity, data and artificial intelligence strategy and policy functions. The agency will be renamed the Office of the Assistant Secretary for Technology Policy and Office of the National Coordinator for Health Information Technology (ASTP/ONC). Head of ONC, Micky Tripathi, will hold the new title of assistant secretary for technology policy in addition to his title of national coordinator for health IT. ... Under ASTP, there will be an Office of Policy, an Office of Technology, an Office of Standards, Certification and Analysis and an Office of the Chief Operating Officer.