Despite the high prevalence and burden of mental health conditions, there is a global shortage of mental health providers. Artificial Intelligence (AI) methods have been proposed as a way to address this shortage, by supporting providers with less extensive training as they deliver care. To this end, we developed the AI-Assisted Provider Platform (A2P2), a text-based virtual therapy interface that includes a response suggestion feature, which supports providers in delivering protocolized therapies empathetically. We studied providers with and without expertise in mental health treatment delivering a therapy session using the platform with (intervention) and without (control) AI-assistance features. Upon evaluation, the AI-assisted system significantly decreased response times by 29.34% (p=0.002), Both groups rated the system as having excellent usability. Introduction Mental health conditions are highly prevalent and exert a considerable burden on society, with a global estimated cost of 125.3 million disability-adjusted life years in 2019 The utility of empathy-related AI support for provider selection of professionally crafted text messages remains unevaluated and is the focus of the current work. Response retrieval has several benefits over generation including the safety and controllability of the responses.

Jack Krawczyk discusses how Google Bard helps users connect and communicate -- and what the future holds for the platform. ChatGPT has been found to have shared inaccurate information regarding drug usage, according to new research. In a study led by Long Island University (LIU) in Brooklyn, New York, nearly 75% of drug-related, pharmacist-reviewed responses from the generative AI chatbot were found to be incomplete or wrong. In some cases, ChatGPT, which was developed by OpenAI in San Francisco and released in late 2022, provided "inaccurate responses that could endanger patients," the American Society of Health System Pharmacists (ASHP), headquartered in Bethesda, Maryland, stated in a press release. ChatGPT also generated "fake citations" when asked to cite references to support some responses, the same study also found.

Healthcare provider Kaiser Permanente reached a $200-million settlement in October with the state of California over long waits experienced by patients needing behavioral health services. Greg Adams, Kaiser's chair and chief executive, cited a shortage of qualified care providers as a major reason for delays in treatment. Such shortages are prevalent statewide: In one survey, only 27% of Californians said their community has enough mental health professionals to serve the needs of local residents. Among adults in the state with any psychiatric illness, 63% said they received no mental health services in the past year. Earlier this year, I found myself among the millions of Californians with mental health needs.

PACS remains an indispensable tool for viewing and interpreting imaging results, but leading health care providers are now beginning to move beyond PACS. The new paradigm brings data from multiple medical specialties together into a single platform, with a single user interface that strives to provide a holistic understanding of the patient and facilitate clinical reporting. By connecting data from multiple specialties and enabling secure and efficient access to relevant patient data, advanced information technology platforms can enhance patient care, simplify workflows for clinicians, and reduce costs for health care organizations. This organizes data around patients, rather than clinical departments. Health care providers generate an enormous volume of data.

Digital health, including telemedicine, has increased access to abortion care. The convenience, flexibility of appointment times, and ensured privacy to abortion users may make abortion services via telemedicine preferable. This scoping review systematically mapped studies conducted on abortion services via telemedicine, including their effectiveness and acceptability for abortion users and providers. All published papers included abortion services via telemedicine in the United States were considered. Articles were searched in PubMed, CINAHL, and Google Scholar databases in September 2022. The findings were synthesized narratively, and the PRISMA-ScR guidelines were used to report this study. Out of 757 retrieved articles, 33 articles were selected based on the inclusion criteria. These studies were published between 2011 and 2022, with 24 published in the last 3 years. The study found that telemedicine increased access to abortion care in the United States, especially for people in remote areas or those worried about stigma from in-person visits. The effectiveness of abortion services via telemedicine was comparable to in-clinic visits, with 6% or fewer abortions requiring surgical intervention. Both care providers and abortion seekers expressed positive perceptions of telemedicine-based abortion services. However, abortion users reported mixed emotions, with some preferring in-person visits. The most common reasons for choosing telemedicine included the distance to the abortion clinic, convenience, privacy, cost, flexibility of appointment times, and state laws imposing waiting periods or restrictive policies. Telemedicine offered a preferable option for abortion seekers and providers. The feasibility of accessing abortion services via telemedicine in low-resource settings needs further investigation.

Doctors believe Artificial Intelligence is now saving lives, after a major advancement in breast cancer screenings. A.I. is detecting early signs of the disease, in some cases years before doctors would find the cancer on a traditional scan. The more I learn about the growing uses of Artificial intelligence in health care, the more convinced I become about its essential place in not just the lab or radiology suite but also in the doctor's office. It can help usher in a world where tests and treatments are applied on an individual basis based on a patient's unique history and predicament. ChatGPT recently passed a radiology board style exam, even as it also informed one of my patients that his hemorrhoids might be from prolonged sitting before I thought to mention that possibility to him.

After the pandemic, artificial intelligence (AI) powered support for mental health care has become increasingly important. The breadth and complexity of significant challenges required to provide adequate care involve: (a) Personalized patient understanding, (b) Safety-constrained and medically validated chatbot patient interactions, and (c) Support for continued feedback-based refinements in design using chatbot-patient interactions. We propose Alleviate, a chatbot designed to assist patients suffering from mental health challenges with personalized care and assist clinicians with understanding their patients better. Alleviate draws from an array of publicly available clinically valid mental-health texts and databases, allowing Alleviate to make medically sound and informed decisions. In addition, Alleviate's modular design and explainable decision-making lends itself to robust and continued feedback-based refinements to its design. In this paper, we explain the different modules of Alleviate and submit a short video demonstrating Alleviate's capabilities to help patients and clinicians understand each other better to facilitate optimal care strategies.

Long-term care service for old people is in great demand in most of the aging societies. The number of nursing homes residents is increasing while the number of care providers is limited. Due to the care worker shortage, care to vulnerable older residents cannot be fully tailored to the unique needs and preference of each individual. This may bring negative impacts on health outcomes and quality of life among institutionalized older people. To improve care quality through personalized care planning and delivery with limited care workforce, we propose a new care planning model assisted by artificial intelligence. We apply bandit algorithms which optimize the clinical decision for care planning by adapting to the sequential feedback from the past decisions. We evaluate the proposed model on empirical data acquired from the Systems for Person-centered Elder Care (SPEC) study, a ICT-enhanced care management program.

Biogen recently announced it is eliminating Adulhelm spending, which brings into question whether drugs are the only answer to Alzheimer's – especially when advanced, IT-enabled early detection technologies and interventions are available. Cognitive screening methods supported by technology are growing in popularity as healthcare professionals realize the value of having faster, more affordable access to cognitive data that informs actionable next steps, says David Bates, CEO and cofounder of Linus Health, a brain health technology company. Healthcare IT News sat down with Bates to discuss the potential of early detection via these sophisticated screening methods and explain how AI-powered testing, using widely available devices, shows decline earlier than a human eye can detect. What kinds of IT-enabled early detection technologies and interventions are available for treating Alzheimer's? A. Healthcare providers have long relied on paper and pencil-based tests to detect early signs of cognitive impairment, dementia and Alzheimer's disease in their patients and serve as the basis of referrals to specialists. Similar to so many other parts of healthcare, though, digital innovation and device accessibility have opened up a wealth of opportunities to improve how providers detect and address brain health issues in primary care.

AI for health care is all the rage. Who wouldn't be excited about applications that could help detect cancer, diagnose COVID-19 or even dementia well before they are otherwise noticeable, or predict diabetes before its onset? Machine and deep learning have already been shown to make these outcomes possible. Possible, that is, in the research lab. In health care, there is often a long lag between research findings and implementation at the bedside.