Authors: Afzal Tarar, Founder & Managing Partner of Quartus Capital Partners LLC and John Q. Walker, PhD, Co-Founder & Chief Technology Officer of uMETHOD Health, Inc.
“NCDs are the leading cause of death and disability worldwide.” These conditions are characterized by their long duration and generally slow progression, stemming from a combination of genetic, physiological, environmental, and behavioral factors, according to the WHO, which complicates their treatment.
The repercussions of these diseases extend beyond families, due to the complexity of the diseases and their resultant management. Their prevention has become a priority for governments worldwide, considering the massive economic impact of treatment. Estimates suggest that by 2030, the global cost of managing chronic diseases will reach $47 trillion, according to figures from the report titled The Burden of Chronic Disease, authored by researcher Karen Hacker.
“The treatment of chronic diseases generally requires repeated medical interventions, hospitalizations, and adjustments or intensifications of therapies, placing a heavy burden on healthcare systems worldwide,” says the report Promoting Health and Well-Being: Employer Strategies for Encouraging Healthy Weight and Metabolic Wellness by the World Economic Forum.
NCDs kill 41 million people annually, accounting for 74% of all deaths worldwide. Low- and middle-income countries account for over three-quarters of these deaths. Cardiovascular diseases (17.9 million), cancer (9 million), respiratory diseases (3.9 million), and diabetes (1.6 million) are the leading causes, according to a report from the World Health Organization (WHO).
uMETHOD Health, an AI-based precision medicine company dealing with chronic disease management, has seen that more than 80% of the patients they have encountered have three or more chronic disease at the same time – coupled with neurodegenerative diseases – as well as frequent co-morbid communicable disease.
Healthcare is entering a new era where artificial intelligence takes center stage, with multiple use cases pointing toward hyper-personalized services. Data analysis is crucial for advancing chronic disease management and improving care models. According to IBM, “Healthcare organizations have accumulated so much data that analyzing it without AI would be impossible.”
AI is key to managing chronic diseases, focusing on prevention and delivering precise treatments through the integrated medical analysis of a patient’s DNA, biochemistry, ongoing lifestyle, co-morbidities, allergies, and medication history.
“Effective AI-based systems prioritize care pathways and suggest preventive strategies to mitigate complications,” says Dr. John Q. Walker, Co-Founder & Chief Technology Officer at uMETHOD Health.
Dr. Walker believes AI brings a step-by-step revolution in preventive care, by addressing systemic barriers, empowering individuals, and leveraging advanced technologies to proactively manage chronic conditions.
Predictive models quantify cost savings from early interventions for insurers and companies, aligning financial incentives with improved health outcomes. Digital tools and wearables granular real-time data, creating prevention-as-a-service models, where insurers incentivize healthy behaviors through reduced premiums or rewards.
Generative AI algorithms also help personalize patient interactions, guiding them to appropriate resources and optimizing care pathways. Practical use cases include delivering clear treatment information, streamlining clinical documentation, evaluating treatment effectiveness, and optimizing treatment across multiple simultaneous chronic diseases – while suggesting alternative management strategies for chronic diseases.
This trend is fueled by investment funds driving these innovations, which are gaining prominence in global portfolios. Bain & Company reports 4,500 venture capital transactions totaling $94 billion in Q2 2024, a 5% increase over the previous quarter. Major drivers of venture investments include AI, healthcare, and financial services.
In this context, collaborations between tech companies and healthcare providers are essential for effectively integrating artificial intelligence (AI) into the healthcare sector. The practical knowledge and diversified data provided by healthcare providers serve as a foundation for tech companies to validate AI models, adapting them to different environments and populations while helping to close gaps in healthcare access.
A clear example of AI's positive impact is its ability to free up physicians’ time. In Europe, it is estimated that with AI adoption, healthcare professionals could dedicate up to 17% more of their time to patients through reduced administrative burden, improving direct care, according to the statistics portal Statista.
By 2021, one-fifth of healthcare organizations worldwide were in the early stages of using these tools, according to the same source. The projections are promising: the global AI healthcare market is expected to grow from $11 billion in 2021 to $188 billion by 2030 as adoption increases across regions.
Managing chronic diseases faces numerous challenges that AI adoption could address, ranging from fragmented care to resistance to new technologies. Dr. Walker at uMETHOD Health highlights several key obstacles that AI can help overcome:
The potential of AI to transform healthcare is immense. However, as IDC warns, “without proper regulations and safeguards, things could spiral out of control,” highlighting the urgent need for a comprehensive understanding of AI's potential and its careful adoption in various contexts.
This is particularly critical given the handling of sensitive medical data and the importance of ensuring its security and privacy for the development of innovative treatments, especially in relation to chronic diseases.
Among the most significant challenges is dealing with the poor quality of the patient input data, as errors or biases in the information can lead to inaccurate recommendations. uMETHOD Health sees about 15% of arriving medical data as flawed in same manner – this dirty data must be corrected, mitigated, or expunged, before being used by any downstream software algorithms. Implementing these technologies requires substantial investments in technological infrastructure, which may limit their adoption in regions or healthcare systems with more restricted resources.
Overcoming these obstacles requires not only technological advancements but also the creation of clear and global regulations that enable the healthcare sector to integrate these solutions more rapidly and effectively.
A critical aspect now is financing, ensuring financial incentives for medical providers to adopt these technologies while also making them financially viable for patients. Dr. Walker, from uMETHOD Health, states that addressing these challenges requires not only technological advancements but also a fundamental shift in how care is conceptualized and delivered.
“I predict that AI will rapidly transform personalized care by integrating detailed historical medical data from electronic health records and health information exchanges. By leveraging these rich data sources, AI can deliver care that is not only highly individualized but also aligned with real-world constraints and patients’ dynamic needs,” Dr. Walker noted.
Afzal M. Tarar, Founder & Managing Partner of Quartus Capital Partners, added that “The effective use AI with the many billions of data points generated daily in the healthcare field stands as a potential solution to the present and future healthcare challenges, particularly the chronic disease management. Ongoing investment will be a key factor in continuing to develop the AI-enabled healthcare ecosystem, enabling more innovative solutions to take shape and address the healthcare challenges.”
