Amber Nigam, CEO, and cofounder of basys.ai, a company based at Harvard, is utilizing generative AI to streamline prior authorization for health plans. The healthcare industry is notoriously complex, burdened by operational inefficiencies and bureaucratic hurdles. Processes like case management, care management, and utilization management are particularly labor-intensive, requiring extensive manual work that can detract from patient care. However, the advent of AI and large language models (LLMs) has the potential to transform healthcare operations and improve efficiency.
In current operational realities, case managers spend a significant amount of time on administrative tasks like data entry and paperwork, impacting their ability to focus on patient care. Care management involves managing chronic conditions and requires constant monitoring and meticulous documentation. Utilization management involves reviewing patient cases to determine the necessity of treatments or procedures, often involving manual reviews and approvals. These processes are crucial but are ripe for disruption with the aid of generative AI and LLMs.
Generative AI and LLMs can automate many administrative tasks in healthcare. In case management, AI can automate data entry, analyze patient records, and suggest personalized care plans to reduce the workload on case managers. For care management, AI can monitor patient data, identify at-risk patients, and facilitate virtual check-ins to improve adherence to treatment plans. In utilization management, AI can review patient cases, make recommendations based on historical data, and reduce the time required for manual reviews and approvals.
Geographical arbitrage, the practice of outsourcing tasks to regions with lower labor costs, has been a common strategy for large healthcare companies to reduce costs. However, as AI-driven automation can perform many of these tasks, the reliance on outsourcing is decreasing. Moreover, stricter healthcare policies are being implemented, making geographical arbitrage less effective. As AI technology advances and regulatory requirements tighten, the reliance on low-cost labor markets is expected to decline.
The healthcare industry is facing a major disruption, with legacy companies at risk of becoming obsolete if they fail to adopt generative AI and LLMs. Large healthcare companies are acquiring smaller startups to access cutting-edge technologies to enhance operational processes. Legacy companies must recognize the importance of this technological shift to keep up with efficiency and compliance demands. Embracing generative AI and LLM technologies is crucial for the future of healthcare operations.
As generative AI and LLM technologies mature, the operational burden on healthcare providers is expected to reduce. Legacy companies must identify potential use cases for generative AI, set clear goals, and key performance indicators to measure the impact effectively. Challenges like patient and data privacy, compliance with regulations like HIPAA, and the learning curve involved in integrating AI technologies need to be addressed. The companies that embrace change, innovate, and integrate new technologies will succeed in a landscape defined by efficiency and patient-centric care, while those hesitant to adapt risk falling behind or facing extinction. Smaller, tech-savvy startups are paving the way forward with groundbreaking innovations, prompting legacy giants to evolve and harness new technology to revolutionize healthcare.
