What happened in health care technology this week, and why it’s important.
Tasso receives FDA 510(k) for patch-like home blood collection device
Emily Olsen’s article in MobiHealthNews starts this week’s coverage. Tasso received FDA 510(k) clearance for its patch-like blood collection device, the Tasso+. The device includes a lancet, which adheres to the arm that connects to a test tube for collection. After users rub their arm or use a heat pack and sanitize the test site, they press a button on the front of the device to begin drawing capillary blood. Then the tube can be removed and sent to a lab for analysis. According to Tasso, it usually takes 10 to 15 minutes to complete the test. The newly cleared Tasso+ will be available in the fourth quarter of this year. Other companies aiming to bring more lab tests into the home include EverlyWell, Cue Health, and traditional player Labcorp, which recently partnered with Getlabs to offer at-home sample collection. Telehealth giant Teladoc has also recently expanded into home collection for its primary care program through a collaboration with Scarlet Health.
Why it’s important – The company said the clearance would allow pharmaceutical companies to use the device for decentralized clinical trials. At the same time, healthcare systems and physicians could utilize it for patient care. The FDA Class II medical device clearance will help improve patient care by relieving traditional phlebotomy-related bottlenecks and enabling more individuals to get the tests they need at the time they are required.
Infographic of the week – This week’s infographic comes from a new report just released by Kaufman Hall on behalf of the American Hospital Association (AHA). Anywhere from 53% to 68% of the nation’s hospitals will end 2022 with their operations in the red versus the 34% reported in 2019. The group’s “optimistic” projections place 2022’s hospital margins 37% lower than what it recorded in 2019. Its “pessimistic” prediction sees that margin decline plummet to 133%. The shortages and losses are forcing many providers to pick and choose which services and locations they can still afford to run. For technology companies looking to sell their products and services into the health care market, these projections are sobering news. What is already a long sales cycle will become even more challenging. Unless the company can demonstrate clear benefits regarding cost reductions, labor savings, or direct impact on the bottom line, they can expect the next few years to be a long, tough slog.
Cancers in Adults Under 50 Have Increased Dramatically Around The Globe
Since 1990, the number of adults under the age of 50 developing cancer has increased dramatically around the world. Fiona MacDonald reports on this disturbing trend in her article on Science Alert. Researchers are already aware that since the 1940s and 1950s, there’s been an increase in people getting late-onset cancer, which means developing cancer after the age of 50. The review looked at data across 14 cancer types: breast, colorectal (CRC), endometrial, esophageal, extrahepatic bile duct, gallbladder, head and neck, kidney, liver, bone marrow, pancreas, prostate, stomach, and thyroid cancer. All of these cancers had been shown by global cancer data to be on the rise in adults under 50 between the years 2000 and 2012. But the researchers took things one step further and reviewed any available studies that could shed light on possible risk factors for these cancers. They also looked for clues in the literature describing any unique clinical and biological characteristics of tumors of early-onset cancers compared to those of late-onset cancers diagnosed after 50. The goal, to quote the title of the paper, was to figure out: “Is early-onset cancer an emerging global epidemic?” According to their results, the answer is yes. At least, this seems to be the case since the 1990s.
Why it’s important – It’s not a groundbreaking notion that cancers are on the rise in modern society. On top of simply being better at finding early-onset cancers nowadays, the evidence suggests that the ‘shift’ in cancer rates happened earlier, when those now in their middle ages were children, around the middle of the last century. Among the 14 cancer types on the rise that we studied, eight were related to the digestive system. Other risk factors include sugary beverages, type 2 diabetes, obesity, a sedentary lifestyle, and alcohol consumption, all of which have significantly increased since the 1950s. The long-term hope is that we can educate people to lead healthier lifestyles in their early years to reduce the risk of early-onset cancers.
Is Salesforce the big tech company that figured out healthcare?
There’s been a lot of reporting in recent years about the role that big tech companies will play in healthcare in the future. Most of that reporting centers around the usual suspects: Amazon, Apple, Google, Microsoft, and Facebook. One company hasn’t received as much attention. Gabriel Perna’s article in Digital Health & Business Technology sets out to correct that omission. While other tech giants have faltered trying to figure out what they’re trying to do in healthcare, Salesforce has quietly become a significant player in the space. Experts say the company’s rise has coincided with a healthcare industry that’s increasingly open to customer-focused technology. Salesforce’s customer base has grown to include health systems, insurance companies, public health departments, pharmaceutical and life sciences firms, retail health, digital health companies, and more. The company has evolved and rapidly iterated, updating its health cloud last September to connect with remote patient monitoring and other connected devices. Executives say its goal is to create a cloud-based, consumer-centered ecosystem connecting clinical, financial, and consumer data.
Why it’s important – Two things happened during the pandemic that buoyed Salesforce’s position in healthcare. First, companies in other industries began using its technology to launch internal and external health and wellness campaigns. Secondly, the health crisis has required healthcare organizations to communicate with and guide patients through a specific care journey. CRM tools, effectively applied, have shown they can help in COVID management and other use cases. Salesforce can expect competition from the big guns in EHRs Epic and Cerner.
The sound of your voice might diagnose diseases
Researchers are building a database of human voices that they’ll use to develop AI-based tools that could eventually diagnose serious diseases; they’re targeting everything from Alzheimer’s to cancer. Nicole Wetsman reports the story in The Verge. The National Institutes of Health-funded project, announced Tuesday, is an effort to turn the human voice into something that could be used as a biomarker for diseases, like blood or temperature. The project is funded through the Bridge2AI program at the NIH, which supports projects that build ethical, rigorous, and accessible datasets that can be used to develop AI tools. It’ll run over four years and could get up to $14 million in funding over that time period. The research team will start by building an app that will collect voice data from participants with conditions like vocal fold paralysis, Alzheimer’s disease, Parkinson’s disease, depression, pneumonia, and autism. A clinician will supervise all the voice collections.
Why it’s important – For now, the new research program isn’t interested in building programs for home devices. It’s focused on developing tools that would be used by doctors in doctor’s offices and clinics. It’d be beneficial in lower-resourced settings where someone might not be able to see a specialist. Medical researchers aren’t the only groups interested in using voice to diagnose disease — big tech companies that make voice assistants are also. Amazon has patents that would use Alexa to determine if people have emotional problems, like depression, or physical issues, like a sore throat. Theoretically, if the sounds in someone’s voice showed signs of something like Alzheimer’s, a passive in-home voice assistant could flag the condition. That’d raise another layer of ethical and legal problems, which experts are already starting to think through.
Hype versus reality: What you can’t do with DeepMind’s AlphaFold in drug discovery
DeepMind’s AlphaFold model has predicted nearly all known protein structures discovered yet, though its ability to help scientists find new drugs remains unproven. Katyanna Quach separates the hype from the reality in her article in The A Register online. Advances in AI algorithms and training have led to software development, such as AlphaFold, that can accurately predict the 3D shapes of proteins given their amino acid combinations. AlphaFold is impressive and has now predicted over 200 million proteins from their amino acid strings. Researchers hoped that building such an extensive database would allow scientists to develop treatments targeting specific proteins associated with diseases such as cancer or dementia. Coming up with such medicines may require you to know the physical structure of the protein, which is where programs like AlphaFold can be used. An investigation led by academics at MIT in America, however, shows just how difficult the task is in practice. Essentially, the AI software is useful in one step of the process – structure prediction – but can’t help in other stages, such as modeling how drugs and proteins would physically interact.
Why it’s important – Breakthroughs such as AlphaFold are expanding the possibilities for in silico (computer simulation) drug discovery efforts. Still, these developments need to be coupled with additional advances in other aspects of modeling that are part of drug discovery efforts. Being able to model these types of chemical interactions is an unsolved problem. No algorithm is perfect. Even if scientists have a good model of the protein, its shape changes when it interacts with a potential drug candidate in mysterious ways. AlphaFold may prove helpful in other parts of the drug discovery pipeline, where comparing protein structures obtained via different methods against the model’s predictions is valuable.
Healthcare plays by CVS, Walgreens and Amazon will drive more partnerships, tech investment, experts say
CVS, Walgreens, and Amazon are ramping up their focus on in-home medical services and primary care, and it will cause significant disruptions for more traditional brick-and-mortar providers. Heather Landi reports on these developments in her article on Fierce Healthcare. With the rapid move to healthcare at home, companies are seizing opportunities to take a piece of the market. CVS rival Walgreens made a $330 million majority-stake investment in post-acute and home care company CareCentrix. Best Buy shelled out $400 million for remote patient monitoring company Current Health. Amazon plans to buy primary care company One Medical for $3.9 billion. Walmart is expanding into medical services by opening about 20 in-person clinic locations across Georgia, Arkansas, Illinois, and now Florida, with locations attached to its supercenter stores.
Why it’s important – As the industry shifts to the home as a site of care, legacy patient-provider relationships and businesses will face disruption. Health systems would do well to consider how they are positioned to deliver care at home as an integrated part of their care models. This may include evaluating legacy home health assets and programs while also rapidly evaluating the business case for launching a hospital at-home program as part of their broader strategic and operational plan.
New Israeli AI tech can detect cancerous biomarkers in real time
Artificial intelligence (AI) models developed by Sheba Medical Center and the Imagene precision-oncology-diagnosis company in Tel Aviv have been used to detect cancerous biomarkers in real-time from a biopsy image alone. The Jerusalem Post’s Judy Siegel-Itzkovich profiles the research. The researchers have just published their findings in the Modern Pathology journal. It appears under the title “Direct identification of ALK and ROS1 fusions in non-small cell lung cancer from hematoxylin and eosin-stained slides using deep learning algorithms.” The study compared the performance of ALK and ROS1 conventional testing methods to that of Imagene’s AI solutions. Immunohistochemistry (IHC), Fluorescence in situ hybridization (FISH), and NGS were used as gold standard methods for the analysis. Validation of the ALK/ROS1 classifier on a cohort of lung cancer cases at the pathology department at Sheba Medical Center displayed sensitivities of 100% for both genes and specificity of 100% and 98.6% for ALK and ROS1, respectively. These results present unprecedented accuracy levels that are comparable with the gold-standard techniques.
Why it’s important – Identifying gene alterations is vital for improving patient care and guiding targeted therapeutic decisions. Lung cancer, resulting primarily from smoking, is the most common cancer and accounts for some 1.76 million deaths per year worldwide. Non-small cell lung cancer (NSCLC) comprises 85% of all lung cancers and is typically diagnosed at advanced stages.