Artificial Intelligence (AI) in medicine uses data science and algorithms to recognize patterns in medical data and then generate meaningful predictions and outputs.
The reliance of medicine on imaging, histopathological, biochemical and other investigational outputs is generating ever-increasing amounts of data, opening the field to new possibilities via machine learning.
AI systems will take on an expanded role in healthcare from researching, sorting data, finding patterns and making predictions to medical diagnostics and even treatment.
AI in health insurance
AI provides enhanced and proactive management of healthcare data, claims and risk, as well as network and administrative processes.
- AI can analyze large amounts of data from images and clinical research trial data to medical claims and can identify patterns and generate insights that might elude discovery via manual human skill sets. This will assist in the early identification of patterns related to fraud, abuse, waste management and claims utilization, which could result in tremendous savings for insurers. A McKinsey report estimates better use of data could save up to $100bn annually as a result of better insight and tools for decision-making and improved efficiencies in clinical trials and research.
- AI can leverage machine learning to enable advanced, timely and dynamic data analysis of health insurer data and electronic health records to produce deep insights into the medical cost of claims and employ these outcomes for networks, claims, pricing and risk management.
- AI can enable more efficient claims adjudication and automate prior authorization workflows with better efficiency and accuracy based on a set of predefined rules. It can learn and analyze experience data to provide current and predictive analytic reports faster than humanly possible.
- AI can streamline operational processes, applying robotic process automation to repetitive administrative processes, leading to more efficiencies, reduced operational expenses and better-utilized resources for more technical functions
- AI tools can monitor and transform analyzed data to predict diseases and develop personalized treatments, potentially improving health outcomes and reducing costs.
- Chatbots are being used to provide better member engagement, customer service management, triage services, differential diagnosis, direction to appropriate specialities and appointment scheduling (in addition to acting as a gatekeeper and saving administrative costs)
- AI is enabling the increased utilization of remote and telehealth services for triage, primary care, disease management, medication refills, cost-effective interpretation and diagnostic services.
Healthcare may move from illness management to wellness management through a proactive, data leveraging and predictive modelling approach. Such an approach will yield greater accuracy in diagnosis, more appropriate diagnostics and treatment planning without waste or overutilization. These will improve health outcomes and lower claims costs, allowing insurers to have a better chance of improving claims ratios and competitiveness.