Virtual-first care, or V1C, could increase the quality of healthcare and make it more patient-centric by letting patients combine in-person visits with virtual options such as video for seeing their care providers.
That’s the idea behind virtual-first care (V1C), a new care model centered on convenient, customized, high-quality care that integrates a full suite of services tailored directly to patients’ clinical needs and preferences. This package includes asynchronous communication such as texting; video and other live virtual modes; and in-person options.
V1C goes beyond what you might think of as standard “telehealth” by using evidence-based protocols and tools that include traditional and digital therapeutics and testing, personalized care plans, dynamic patient monitoring, and team-based approaches to care. This could include spit kits mailed for laboratory tests and complementing clinical care with health coaching. V1C also replaces some in-person exams with ongoing monitoring, using sensors for more ‘whole person’ care.
Amidst all this momentum, we have the opportunity to rethink the goals of healthcare innovation, but that means bringing together key stakeholders to demonstrate that sustainable V1C can redefine healthcare.
Established V1C healthcare providers such as Omada, Headspace, and Heartbeat Health, as well as emerging market entrants like Oshi, Visana, and Wellinks, work with a variety of patients who have complicated long-term conditions such as diabetes, heart failure, gastrointestinal illness, endometriosis, and COPD. V1C is comprehensive in ways that are lacking in digital health and its other predecessors: it has the potential to integrate multiple data streams, incorporate more frequent touches and check-ins over time, and manage a much wider range of chronic health conditions, improving lives and reducing disease burden now and in the future.
Recognizing the pandemic-driven interest in virtual care, significant energy and resources are already flowing fast toward V1C. Some of the world’s largest innovators jumped into V1C early on: Verily, Alphabet’s Life Sciences Company, launched Onduo in 2016 to disrupt the diabetes healthcare market, and is now well positioned to scale its solutions. Major insurers like Aetna and United now offer virtual-first plans to members, responding as organizations expand virtual options for employees. Amidst all this momentum, we have the opportunity to rethink the goals of healthcare innovation, but that means bringing together key stakeholders to demonstrate that sustainable V1C can redefine healthcare.
That was the immediate impetus for IMPACT, a consortium of V1C companies, investors, payers and patients founded last year to ensure access to high-quality, evidence-based V1C. Developed by our team at the Digital Medicine Society (DiMe) in collaboration with the American Telemedicine Association (ATA), IMPACT has begun to explore key issues that include giving patients more integrated experiences when accessing both virtual and brick-and-mortar care.
Digital Medicine Society
V1C is not, nor should it be, virtual-only care. In this new era of hybrid healthcare, success will be defined by how well providers help patients navigate the transitions. How do we smoothly hand a patient off from an onsite primary care physician to, say, a virtual cardiologist? How do we get information from a brick-and-mortar to a digital portal? How do you manage dataflow while still staying HIPAA compliant? There are many complex regulatory implications for these new models, as well as an evolving landscape in terms of privacy, security and interoperability. It will be no small task for groups like IMPACT to determine the best path forward.
None of these factors matter unless the industry can recruit and retain clinicians. Our field is facing an unprecedented workforce crisis. Traditional healthcare is making clinicians miserable, and COVID has only accelerated the trend of overworked, disenchanted healthcare workers leaving in droves. Clinicians want more interactions with patients, and fewer with computer screens – call it “More face time, less FaceTime.” No new model will succeed unless the industry can more efficiently deploy its talent – arguably its most scarce and precious resource. V1C can help with alleviating the increasing burden and frustration borne by individual physicians in today’s status quo.
In healthcare, new technological approaches inevitably provoke no shortage of skepticism. Past lessons from Silicon Valley-driven fixes have led to understandable cynicism. But V1C is a different breed of animal. By building healthcare around the patient, not the clinic, V1C can make healthcare work better for patients, payers and providers. We’re at a fork in the road: we can revert back to a broken sick-care system, or dig in and do the hard work of figuring out how this future-forward healthcare system gets financed, organized and executed. As a field, we must find the courage and summon the energy to embrace this moment, and make it a moment of change.
A recent study in The Lancet Oncology showed that AI found 20 percent more cancers on mammogram screens than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.