‘The Future of AI and Older Adults 2023’ now published

Laurie Orlov of Aging and Technology Watch in her latest paper tackles the latest iterations of AI and ML, tracing their roots back to 2014 to the original smart speakers and voice assistance, technologies that enabled older adults to access services with convenience and at reasonable cost. What will be the impact of AI using tools such as large language models (LLM) like ChatGPT to develop improved search, voice assistance, answers to health questions, and care plans written in understandable and empathetic language? For care facilities and senior housing, will they leverage AI with voice and sensor tech to improve safety monitoring for both residents and caregivers, plus the dream of predictive health for residents or those living at home with limited assistance? Will chatbots get a lot smarter versus obnoxious? Find out what both the short term and long term (5+ year) impact could be. 

Ms. Orlov’s somewhat gimlety view includes Gartner’s infamous Hype Cycle chart on page 5. As of today, most AI technologies reside in the balmy Peak of Inflated Expectations, the place where whatever investment funding is going. There’s lots of innovation and kitchen table hackathoning. Looming about two years out is the inevitable Trough of Disillusionment which has already been kicked off by Big Thinkers such as Steve Wozniak. As this Editor observed last month, it is a double-edged sword, with the bad side in its potential for data misuse, fraud, fakery, and malicious action. It’s already created controversy that this Editor predicts will crest in the next year with demands for regulation. We’re not there yet, however.

Download of the PDF is here and free.

Perspectives: How AI and ML can accelerate the growth of telemedicine across the globe

TTA has an open invitation to industry leaders to contribute to our Perspectives non-promotional opinion area. Today’s Perspectives is from Deepak Singh, a thought leader in AI and telehealth. In his work, he builds AI-powered healthtech and telehealth solutions that can reach from big cities to remote areas of the world. With double master’s degrees in business and information systems, he has 10 years of experience in product development, management, and design ranging from telecom to multimedia and from IT solutions to enterprise healthcare platforms. This article discusses how artificial intelligence (AI) and machine learning (ML) can accelerate the global growth of telemedicine, including a consideration of risks and possible solutions.

Introduction

The ongoing technological advancements have led the way towards greater opportunities for the growth of the global health business, particularly telemedicine through increased connections via the internet, robotics, data analytics, and cloud technology that will further drive innovation over the next ten years. It is obvious that artificial intelligence (AI) usage plays a noteworthy part in the maneuvering and execution of medical technologies when considering the bulky amount of data handling needed by healthcare, the requirement for consistent accuracy in complex procedures, and the rising demand for healthcare services.

Telemedicine is the practice of performing consultations, medical tests and procedures, and remote medical professional collaborations through interactive digital communication. Telemedicine is an open science that is constantly growing as it embraces new technological developments and reacts to and adapts to the shifting social circumstances and health demands. The primary goals of telemedicine are to close the accessibility and communication gaps in four fields: teleconsultation, which is having all kinds of physical and mental health consultations without an in-person visit to a medical facility; teleradiology, which uses information and communication technologies (ICT) to transmit digital radiological images (such as X-ray images) from one place to another; telepathology, which uses ICT to transmit digitized pathological results; and teledermatology, which uses ICT to transmit medical information about skin conditions.

AI has been progressively implied in the field of telemedicine. AI deals with machine learning (ML) that discloses complex connections that are hard to figure out in an equation. In a way that is similar to the human brain and neural networks that encrypt data using an enormous number of interconnected neurons, ML systems can approach difficult problem-solving in the same way that a doctor might do by carefully analyzing the available data and drawing valid judgments.

A growing understanding of artificial intelligence and data analytics can help to broaden its reach and capabilities. Telemedicine’s goal is to boost productivity and organize experience, information, and manpower based on need and urgency and it can be augmented by the use of AI and ML.

Evolving application of AI and ML in Telemedicine

In order to enable clinicians to make more data-driven, immediate decisions that could enhance the patient experience and health outcomes, AI is being employed in telemedicine more and more. The use of AI in healthcare is a potential approach for telemedicine applications in the future.

Al and ML were able to bring about the necessary revolution in so many sectors due to their competence, increased productivity, and flawless execution of tasks. AI is now surpassing the boundaries of being a mere theory and stepping into a practical domain where the need for human supervision for the execution of jobs by machines will be minimized all due to the presence of enormous datasets along with an increment in the processing power of that data. A computer-based algorithm that uses AI has the ability to analyze any form of input data such as ‘training sets’ using pattern recognition which eventually predicts as well as categorize the output, all of that is beyond the scope of human processing or analytical powers that uses traditional statistical approaches. In the field of telemedicine, the adoption of AI and ML still has to go a long way till its vital concepts are understood and applied likewise, nevertheless, the current scenario gives a promising picture where many research projects have applied AI to predict the risk of future disease incidence, decrypting cutting-edge imaging, evaluating patient-reported results, recording value-based metrics, and improving telehealth. The perspective to mechanize tasks and improve data-driven discernments may be comprehended by profoundly improving patient care with obligation, attentiveness, and proficiency in prompting AI.

Drawbacks of artificial intelligence in telemedicine (more…)

Weekend news and deals roundup: Allscripts closes sale of hospital EHRs, closing out CEO; DEA scrutiny of Cerebral’s ADHD telehealth prescribing; more telehealth fraud; Noom lays off; fundings; and why healthcare AI is only ML

That was fast. Allscripts closed its $700 million March sale of its hospital and large physician practice EHRs to Constellation Software Inc. through N. Harris Group. The Allscripts EHRs in the transaction are Sunrise, Paragon, Allscripts TouchWorks, Allscripts Opal, and dbMotion. They reported their Q1 results today. According to HISTalk earlier this week, CEO Paul Black will be stepping down, with President Rick Poulton stepping in immediately. Update–this was confirmed on their investor call Thursday and the transition is effective immediately. No reasons given, but there were no effusive farewells.  Healthcare Dive

A damper on telemental health? Online mental health provider Cerebral, which provides talk therapy, audio/video telehealth, and prescriptions for anxiety, depression, insomnia, ADHD, and other conditions, is finding itself under scrutiny. This week, its main mail fulfillment pharmacy partner, Truepill, stopped filling prescriptions for Adderall, Ritalin, Vyvanse, and other controlled Schedule 2 pharmaceuticals. Cerebral is redirecting current patients with these prescriptions to local pharmacies and as of 9 May, will not prescribe them to new ADHD patients.

Based on reports, the Drug Enforcement Agency (DEA) is looking at Cerebral in particular as part of a wider scrutiny of telehealth providers and pharmacies filling telehealth-generated prescriptions due to allegations of overprescribing. It also didn’t help that a former VP of product and engineering plus whistleblower claims in a wrongful dismissal lawsuit that Cerebral execs wanted to prescribe ADHD drugs to 100% of diagnosed patients as a retention strategy. Bloomberg Law. Unfortunately, Insider is paywalled but you may be able to see a report in the Wall Street Journal. Becker’s Hospital Review, FierceHealthcare

Also troubling telehealth is recurrent fraud, waste, and abuse cases involving Medicare and Medicaid. Back in 2020 the National Healthcare Fraud Takedown took down over 80 defendants in telemedicine fraud [TTA 2 Oct 20, 30 Jan 21]. The Eastern District of NY based in Brooklyn has indicted another physician, an orthopedic surgeon, in a $10 million fraud involving durable medical equipment (DME). In exchange for kickbacks from several telemedicine companies, he allegedly prescribed without examination and with only a cursory telephone conversation DME such as orthotic braces. DOJ release

Some fundings and a sale of note–and a big layoff at a well-known digital health leader:

  • Blue Spark Technologies, an RPM company with a patented Class II real-time, disposable, continuous monitoring body temperature patch good for 72 hours, TempTraq, raised a $40 million intellectual property-based debt solution (??) to fund growth led by GT Investment Partners (“Ghost Tree Partners”) with support from Aon plc (NYSE: AONRelease
  • Specialty EHR Netsmart acquired TheraOffice, a practice management platform for physical therapy and rehabilitation practices which will be added to its existing CareFabric platform. Neither terms nor management transitions were disclosed in the release.
  • ‘White label’ telehealth/virtual health provider Bluestream Health is implementing its systems in Mankato Clinic, with 13 facilities across southern Minnesota. It’s a rarity–physician-owned and led–and in business since 1916. This also fits into a new telehealth trend–providers working with ‘white label’ telehealth companies and not with the Big 5. Release
  • Ubiquitously advertised (in US) weight-loss app Noom is laying off a substantial number of employees–180 coaches plus 315 more employees. Reportedly they are pivoting away from on-demand text chat to scheduled sessions that don’t require so many people. While profitable in 2020 ($400 million) and with Series F funding of over $500 million in 2021, it’s come under criticism that while its pitch heavily features easy behavioral change achieved through cognitive behavioral therapy (CBT), their real core of weight loss is severe calorie restriction. Engadget
  • Element5, an administrative software provider for post-acute facilities, raised a $30 million Series B from Insight Partners. They claim that their software is AI and RPA (robotic process automation) based. ReleaseMobihealthnews

And speaking of the AI pitch in healthcare, a VC named Aike Ho explains why she doesn’t invest in healthcare AI companies because there’s no such thing in healthcare–it’s just machine learning. On that, Ms. Ho and your Editor agree. She also makes the point that the market they address is ancillary and not core services, plus they have difficulty clinching the sale because they don’t relate well to achieving or can’t prove at this stage improved clinical outcomes. Ms. Ho’s looooong series of Tweets is succinctly summarized over at HISTalk (scroll down halfway).