Literature Review

Adoption of artificial intelligence-enabled robots in long-term care homes by health care providers: Scoping reviewJournal of Medical Internet Research; Karen Lok Yi Wong, Lillian Hung, Joey Wong, Juyoung Park, Hadil Alfares, Yong Zhao, Abdolhossein Mousavinejad, Albin Soni, Hui Zhao; 8/24Long-term care (LTC) homes face the challenges of increasing care needs of residents and a shortage of health care providers. Literature suggests that artificial intelligence (AI)-enabled robots may solve such challenges and support person-centered care. We identified three barriers to AI-enabled robot adoption: (1) perceived technical complexity and limitation; (2) negative impact, doubted usefulness, and ethical concerns; and (3) resource limitations. Yet, our findings show that health care providers might not use robots because of different considerations. The implication is that the voices of health care providers need to be included in using robots.

Rethinking medical records and electronic health EMR Industry - Information & Intelligence; 9/11/24 Since healthcare delivery is rapidly moving toward a more digital model, electronic health records, or EHRs, are likely to become even more important and impactful in the years to come. EHRs are the foundation for providing safe and effective care. The themes covered in this seventh edition of Healthcare Foresight are insight-driven decision making based on data platforms, developing regional EHR approaches that enable integrated care, and avoiding implementation problems. ... The phrase “electronic medical record” is becoming a bit archaic. It has been replaced by an electronic health record, or patient record, which compiles clinical data from several locations into a single, all-encompassing picture of the patient. Healthcare providers can now more easily achieve the long-aspired-for health data ideal of one patient, one record, thanks to developments in cloud computing, cybersecurity, and artificial intelligence (AI). Patients moving between multiple care settings—the community, hospitals, primary care clinics, and wherever else they might receive care—should have a seamless experience thanks to the EHR. However, the possibilities are far more.

Leadership in the age of AI: At the crossroads of humanity and technology Forbes; by Dr. Adil Dalal, DBA; 9/9/24 It has only been 200 years since the First Industrial Revolution and the mass adoption of what we now call technology... The Second Industrial Revolution in the late 19th and early 20th centuries, marked by great progress in mass production, ... emphasizing the importance of machines over humans and managers over employees. ... Today, the world stands on the precipice of the Fourth Industrial Revolution with artificial intelligence, which is not just reshaping industries but also redefining the very essence of leadership and decision-making. ...  A technology-driven leader [TDL] who prioritizes novelty over humanity can pose significant risks, potentially leading to societal downfall. ... A human-centric leader [HCL] prioritizes the well-being, growth and empowerment of people, steering humanity toward greatness. ... So is there an ideal Technology Age leader who can lead humanity through this historical moment? Yes! ... They must embody and demonstrate the following three qualities:

Seven pillars to put healthcare consumers at the heart of the digital transformation Forbes; by Hélène Musikas, Géraldine Maouchi, Lorenzo Mandelli, Daniel Brown; 9/6/24 The digital age has seen many industries undergo a profound transformation, evolving into agile "Hybrid Organizations" that blend traditional and digital business models. ... The healthcare sector, however, faces a unique set of challenges on its journey toward this transformation. ... One of the most significant shifts in healthcare is the rising concept of "Self-Care". Seven Ways To Harmonize The Digital Landscape In Healthcare ...

The biggest threat in health IT and RCM Becker's Hospital Review; by Randi Haseman; 9/6/24 Are organizations adopting AI technology too quickly or too slowly? And what's the future of payer relationships? ... As part of an ongoing series, Becker's is talking to healthcare leaders who will speak at our conference. ... Question: What is the biggest threat in health IT and RCM right now? [Responses from 47 executives featured in this article address the following and more: payer programs; modernizing legacy systems while ensuring data security and compliance; cyber-crime / cybersecurity; relieving provider and staff burden thgouth clinical workflows; state and federal legislation; human error; Gen AI 'mission-creep'; extended systems downtimes; the velocity of technical disruption; more ...]

Urgency to adopt AI intensifies for health IT leaders Becker's Health IT; by Naomi Diaz; 9/4/24 A Sept. 4 survey from healthcare data platform Arcadia revealed that 96% of healthcare technology leaders view the effective use of AI as crucial for gaining a competitive edge. ... The findings show that while 33% of these decision-makers see AI as essential today, that number rises sharply to 73% who believe it will be indispensable within the next five years. Despite their confidence in AI adoption, 96% of health tech leaders report feeling an increasing urgency to act, driven by pressure from data and analytics teams (82%), IT and tech departments (78%) and executive leadership (73%). However, the survey also highlights a significant challenge: 40% of leaders cite a talent shortage as a major barrier to AI implementation. This has led CIOs to place greater emphasis on skills such as data-driven decision-making (71%), data analysis, machine learning and systems integration (66%), as well as the need for roles focused on training and support for healthcare staff (59%).

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."