The synergy between Artificial Intelligence (AI) and healthcare has become increasingly evident in recent years. As the data gets analyzed, a report from Morgan Stanley comes to light, predicting a significant boost in the allocation of budgets for AI and machine learning (ML) in the healthcare sector. This anticipated growth, with a projected 10.5% allocation for the coming year compared to 5.5% in 2022, highlights the industry’s growing recognition of AI’s transformative potential. This article will delve deeper into the pivotal domains where AI is making remarkable strides, examine the surge in public interest in AI healthcare, and explore the ways AI is enhancing the delivery of healthcare.
I. AI’s Expanding Role in Healthcare
While AI and ML have been steadily infiltrating healthcare, their complete potential remains untapped. The Morgan Stanley report outlines four key areas where AI is poised to create substantial opportunities:
Biopharma Advancements
AI is ushering in a new era in biopharma. Notably, the report highlights a remarkable increase in the integration of AI into drug and biologic applications submitted to the U.S. Food and Drug Administration (FDA). In 2021, over 100 such applications contained AI/ML components, a significant leap from just 14 in 2020. This surge in AI utilization expedites drug development and regulatory approvals, potentially adding an impressive $70 billion in value to the biopharma industry.
Healthcare Services and Technology
AI is revolutionizing healthcare services and technology. Partnerships like HCA Healthcare’s collaboration with Google Cloud and Augmedix’s utilization of generative AI for emergency medicine exemplify AI’s innovative applications in healthcare. These collaborations are not only enhancing patient care but also streamlining healthcare services, marking a significant step forward for the industry.
Life Sciences Tools and Diagnostics
AI’s profound impact extends to the life sciences field, where it is playing a pivotal role in the development of tools and diagnostics. With access to vast repositories of healthcare data, AI is improving diagnostic accuracy and supporting researchers in making groundbreaking advancements in medical science.
Medical Technology Advancements
The medical technology sector is undergoing a transformative shift through the integration of AI. Anthem Blue Cross and Blue Shield’s AI-driven virtual-first health plan is poised for expansion, highlighting how AI can enhance accessibility and efficiency in healthcare services.
II. Better Delivery of Care
AI/ML offers an opportunity to drive change and efficiency where healthcare services and technology meet. The tools’ predictive capabilities make it easier for doctors and other healthcare providers to detect and diagnose diseases more quickly. This gives them more time with patients, which could improve patients’ satisfaction as well as their health outcomes.
Some other benefits of AI for providers include more efficient and accurate patient access and allocation, diagnostics, risk coding, claims processing, supply chain management, and predictive modeling.
On the patient side, AI could help individuals access and manage treatment. It could unlock the most effective insurance distribution channels and find local pharmacies with the lowest drug prices while improving telehealth services, disease detection, and 3-D modeling capabilities.
Analysts expect AI to improve inefficiencies in care delivery and coordination, as well as reimbursement, to drive value across the healthcare ecosystem. They see companies focused on diagnostics, patient care, and electronic health records as best positioned to benefit.
III. Harnessing Data for Tools and Diagnostics
Tools that help parse minute biological components and diagnose diseases, conditions, and injuries remain at the forefront of applying AI/ML to drive better care and create new business opportunities.
Advancements such as the adoption of next-generation sequencing (NGS) and the broader move to electronic health records have opened the door to advanced diagnostics by combining genomic data with patient health records, medical imaging, and other data. For instance, algorithms could help glean insights into the cause of disease or identify subtle correlations that can’t be parsed through traditional methods of analysis.
AI/ML approaches will become increasingly necessary and highly desirable for companies looking to leverage these complex data sets to build competitive advantage, develop new products, and ultimately shift healthcare toward personalized medicine and improved patient care.
Analysts see diagnostics as a top area for AI/ML investment. By contrast, companies with products and services focused on later-stage, more invasive procedures may experience reduced demand as AI tools identify and treat illness earlier.
The healthcare sector’s increasing investment in artificial intelligence and machine learning represents a monumental shift toward innovation and efficiency. AI’s potential impact on biopharma, healthcare delivery, and diagnostics is poised to revolutionize the industry. From expediting drug development and enhancing patient care to harnessing complex data for advanced diagnostics, AI is reshaping the healthcare ecosystem.
While challenges and concerns remain, including the accuracy of commercially available generative AI tools and data privacy, the opportunities for AI in healthcare are vast. As healthcare companies continue to collect extensive datasets, AI technologies stand ready to unlock breakthroughs in treatment, care, and patient experiences. The future of healthcare is undeniably intertwined with the transformative power of artificial intelligence.
