Literature Review

'This innovation was a home run!': Top tech projects for 8 systemsBecker's Health IT, by Laura Dyrda; 2/19/24C-suite executives are taking a critical eye to any technology spend, focusing on applications and partnerships that will support the clinical workforce, automate administrative tasks and expand access to care through virtual platforms. They're also looking upstream at opportunities to use artificial intelligence and machine learning to gather better insights into operational efficiency and patient care. Which investments yielded the best results in the last year? Eight health system leaders shared with Becker's the most needle-moving projects and initiatives from 2023.

Why the Tech Industry Won’t Disrupt Health CareHarvard Business Review, by John Glaser, Sara Vaezy, and Janet Guptill; 2/16/24Because health care delivery is heavily data-driven but lags in adopting new technologies, it is easy to jump to the conclusion that it is ripe for digital disruption. Indeed, it’s obvious that U.S. health care badly needs significant change: It costs too much, its quality isn’t what it could and should be, and as for access, millions of people live hundreds of miles from the nearest hospital and/or don’t have a primary care doctor. But does that mean that new tech-savvy entrants, armed with powerful digital tools and novel business models, could displace and demolish incumbent health systems with their better-fastercheaper ethos? They haven’t so far, and we don’t think that they will.Publisher's note: Thank you Ernesto Lopez, The Denver Hospice, for sharing this article with us.

Healthcare's Oppenheimer moment Becker's Health IT, by Laura Dyrda; 2/16/224The thing that makes C-suite executives most excited about the future is also making them incredibly nervous: artificial intelligence. AI exploded in healthcare over the last 18 months as ChatGPT ushered in a new era of capabilities to automate repetitive tasks, analyze data and generate sophisticated chatbot communications. But there are risks with AI, including trained biases, information security and accuracy.

How AI-enabled speech analysis could diagnose, treat diseasesModern Healthcare, by Gabriel Perna; 2/2/24Healthcare providers and digital health companies are using speech analysis AI to anticipate heart attack and better understand a patient's social needs.

VNHS leveraging tech to optimize hospice patient experience: A game-changer in end-of-life careCompsMag, by Tech Desk; 2/8/24... Georgia-based hospice provider Visiting Nurse Health System (VNHS) ... has been a pioneer in implementing various technologies that are becoming increasingly common in the post-acute space. For example, VNHS implemented its remote patient monitoring program in 2007 and more recently delved into predictive analytics. According to VNHS CEO Dorothy Davis, they have invested for five years in a platform that has become the repository for claims data coming in. 

Mass General Brigham pilot: AI tool helped optimize palliative care utilizationFierce Healthcare, by Anastassia Gliadkovskaya; 2/2/24Artificial intelligence can help identify easy to miss patients who might be good candidates for a palliative or hospice care referral, a recent pilot at Mass General Brigham (MGB) revealed. ... Over the course of the pilot, 9% of 1,522 MSSP ACO patients were recommended for a consult by the tool, with 40 receiving inpatient palliative consults. An estimated 17 of those would have been missed without the Radial tool. 

Home health industry’s technology partners continue racing toward AIHome Health Care News, by Joyce Famakinwa; 2/1/24Artificial intelligence is likely to be a hot topic in home-based care over the next few years. With that in mind, most companies in the space are already adjusting. Post-acute technology company WellSky, for instance, has partnered with Google Cloud to leverage its artificial intelligence (AI) platform, Vertex AI. The partnership also includes Google Cloud’s secure cloud technologies, advanced data analytics tools and machine learning capabilities.

Regulate Artificial Intelligence in health care by prioritizing patient outcomes JAMA, by John W. Ayers, PhD, MA; Nimit Desai, BS; Davey M. Smith, MD, MAS; 1/29/24Artificial intelligence (AI) holds great promise to enhance the quality of health care. Despite the aim of health care regulations to ensure high-quality care, there are few regulations governing the use of AI in health care. This dearth will soon change because a White House executive order instructed the Department of Health and Human Services to develop new AI-specific regulatory strategies addressing equity, safety, privacy, and quality for AI in health care before April 27, 2024.

Top 5 digital health priorities for health systemsBecker's Health IT, by Giles Bruce; 1/31/24Nearly two-thirds of health system C-suite leaders say digital health is easing access to care, though using it to improve patient experience has fallen as a tech priority for executives, a new study found. ... [According] to the Jan. 22 report from management consultant Sage Growth Partners ... [here are] the top five digital health priorities for the next 12 months, per the survey of 108 hospital and health system C-suite executives:

Palliative telecare team aids QOL, health status for chronic conditionsHealthDay News, by Lori Solomon; 1/23/24Use of a nurse and social worker palliative telecare team is associated with clinically meaningful improvements in quality of life at six months for adults with chronic obstructive pulmonary disease (COPD), heart failure, or interstitial lung disease (ILD) versus usual care, according to a study published in the Jan. 16 issue of the Journal of the American Medical Association.

Healthcare orgs taking steps to remove racial bias from algorithm and AI tools, new report showsMcKnight's Senior Living, by Aaron Dorman; 1/22/24... A team of doctors at the American Academy of Pediatrics is going through hundreds of algorithms and other materials to find, and remove, anything that could exacerbate racial disparities, a “herculean task,” as the JAMA report describes it. The potential for AI-enabled bias could be a major problem for diagnosing life-threatening conditions in seniors. 

Predictive analytics in action: How machine learning is driving successful outcomes for value-based end of life programsSenior Housing News, by Sophie Knoelke; 1/17/24Based on a discussion with Jordan Holland and Mark Bailes of VNS HealthHolland: "We are using predictive analytics to identify patients that are in that end-of-life stage, and then intervening on those patients earlier through a palliative-centric model. We take a full view of an individual’s health across the continuum. Then, we identify what the right clinical model is for their individual situation -the technologies, the analytics to help successfully deploy that model."

Hospital study on AI identifies undiagnosed dementia patients coming from LTCMcKnights Senior Living, by Aaron Dorman; 1/16/24A high number of senior living and care residents have dementia on admission, or develop it during their stay, despite never receiving a formal diagnosis. When these “secret” dementia patients, however, have an emergency – say, a fall – and are hospitalized, they can catch the new care team unaware and struggling to make appropriate clinical decisions. To avoid this pitfall, new research is looking at electronic health records to flag individuals who might have dementia, possibly undiagnosed, so that when they arrive at a hospital, the care team is ready.