AI is expected to impact almost every aspect of healthcare in the coming years – from predicting the next pandemic, to enabling point of care diagnostics, remote patient monitoring, enhancing drug discovery and other backend systems. The healthcare system as it exists today requires this type of digital renovation and realignment with human needs. An aging population requiring more care, combined with clinical staff shortages, global health crises like COVID, and the worldwide rise of chronic diseases, are driving this need. Implementation should focus first on these areas of highest concern. Available healthcare data, which will exceed 10 trillion gigabytes by 2025, will require AI to understand, sort and make use of. Other data that has been heretofore inaccessible, unfathomable, or seemingly unrelated to healthcare will also be brought into the realms of AI for interrogation and evaluation. The innovation that AI will bring to healthcare, driven in part by big tech players, will radically change how healthcare is perceived, practiced, and consumed. Necessity is the mother of this disruptive cybernation. AI technology and data will fuel the inventions that will reform, impact and improve healthcare globally.
An Ailing Healthcare System
Globally, healthcare systems are struggling. In part, the systems are ailing because healthcare is ill-equipped to address modern challenges. The rise of chronic diseases has led to a fundamental mismatch between the acute care model traditionally used in healthcare and the long-term, comprehensive care required for chronic conditions. These long-term conditions, such as heart disease, cancer, obesity, and diabetes, account for a significant portion of the US’s $4.1 trillion annual healthcare costs and are responsible for 7 out of 10 deaths.[1] Mental health and aging are also significantly impacting healthcare: 1 in 5 adults in the U.S. experiences mental illness in a given year; 1 in 4 adults will experience a clinical mental illness at some point in their adult lives.[2] With the world’s population aging, the percentage of people aged 65 and older is increasing faster than those below that age.[3] These older adults consume a disproportionate share of healthcare resources due to increased utilization and chronic disease burden. Like the world over, the U.S. is facing a severe shortage of elder care workers that will only worsen as the population rapidly ages, with a projected 60% increase in workers needed by 2040 to keep up with demand.[4]
Data, Automation and Empowerment
A top driver of growth for AI in healthcare is the growing amount of medical data available. According to the DATCON index, the healthcare data explosion will exceed 10 trillion gigabytes by 2025.[5] This is about equal to 250 billion hours of high-quality video. This data will include patient generated data, EMR data, medical imaging data, genomics and molecular data and more. This volume of data will require AI systems to filter, sort, understand and then present results and actionable insights for clinicians, payers and patients. In addition to these existing datasets being used in AI, many academic, nonprofit and industry groups are aggregating and curating novel multi-institutional datasets spanning clinical, genomic and imaging data to fuel development of new AI systems addressing a variety of clinical needs. An example of a company using novel datasets is my own company, Oncoustics. Instead of just analyzing ultrasound images, Oncoustics applies AI to the raw ultrasound signals/data from handheld ultrasound devices. The resulting AI algorithms and models analyze these raw signals to differentiate and delineate healthy versus diseased tissue thereby enabling easier, faster, and less invasive screening, diagnosis and monitoring of liver conditions. Other tools that use AI to tap into datasets outside of their standard uses include Modality.AI, that can detect and stage CNS disorders like Parkinson’s and ALS from speech patterns as patients talk and interact with Tina™, a virtual guide. The Rho™ by 16Bit, a screening tool that opportunistically evaluates routine and standard x-rays to screen for bone disease like osteoporosis is another. More are available today and many others are in development.
In 2024, even after significant advances in electronic health records and other digital developments across the industry, healthcare is still considered amongst the least digitized industries globally. By some, it is considered the 5th least digital industry after mining.[6] According to Gopal G. et al., healthcare has the lowest level of digital innovation compared to other industries, such as media, finance, insurance and retail.[7] It’s time to correct this and move healthcare into the digital and AI age. AI and scalable digital technologies can help manage chronic disease patients and address growing mental and behavioral health issues by offering always on, always available therapeutics, diagnostics and remote monitors. AI and digital technologies also promise to address the staggering growth in need and shortages of care by making existing care workers more productive and sometimes by replacing them altogether.
It’s evident our healthcare systems are misaligned with our healthcare needs. We have tools and technologies today that can and should be brought to bear to address these clinical needs. It’s up to all of us in the healthcare ecosystem: developers, payers, regulators, clinicians, and patients to see where and how we might facilitate advancing these technologies so that digital tech and AI may quickly address the myriad unmet clinical needs we see in healthcare today.
An overview of AI in healthcare in five bites:
- The global artificial intelligence in the healthcare market was valued at USD 16.3 billion in 2022 and is expected to grow at a CAGR of 40.2% to reach USD 173.55 billion by 2029. The healthcare AI market is experiencing a remarkable and significant surge in its growth and acceptance.
- The top segments dominating AI in healthcare today are Robot-Assisted Surgery, Clinical Trials, and Connected Machines. Diagnostics, Dosage Error Reduction, and Cybersecurity are also top areas in development.
- Emerging global health issues like COVID-19 and NAFLD and T2D, aging populations and lack of medical staff are all driving the need for more digital systems with AI systems leading the way.
- Big tech is entering the field in a big way: Google, Amazon, Apple and Microsoft all have AI in healthcare initiatives.
- A top driver of growth for AI in healthcare is the growing amount of medical data available: According to the DATCON index, the healthcare data explosion will exceed 10 trillion gigabytes by 2025.
Beth Rogozinski
Beth Rogozinski is CEO of Oncoustics, an innovative AI solutions company that applies machine learning to an untapped dataset in ultrasound to create virtual biopsy tools that will democratize diagnostics and healthcare. Beth spent the last 15+ years focused on digital medicine and has produced and published over a dozen software as a medical device solutions and has contributed to 6 SaMDs that are FDA cleared – including having submitted the first prescription SaMD that the US FDA ever cleared in 2017. Beth has written and published on health-tech innovations and is board director or advisor to many companies, universities and industry organizations.
[1] https://www.healthcentral.com/chronic-health/the-cost-of-being-chronic-in-2023-a-special-report
[2] https://www.nami.org/about-mental-illness/mental-health-by-the-numbers/
[3] https://www.census.gov/library/stories/2023/05/2020-census-united-states-older-population-grew.html
[4] https://thegerontechnologist.com/ring-the-alarm-theres-a-global-caregiver-shortage-can-technology-help/
[5] https://www.forbes.com/sites/delltechnologies/2022/08/24/how-healthcare-organizations-can-transform-and-become-data-driven/?sh=4383484958bb
[6] https://www.insidermonkey.com/blog/5-least-digitized-industries-that-are-ripe-for-digital-transformation-1150942/?singlepage=1
[7] https://pubmed.ncbi.nlm.nih.gov/30530878/
