A Study by the National Library of Medicine¹ has stated that several types of Artificial Intelligence (AI) are being adopted by payers and insurance companies. Machine learning is the most common form of AI as per a survey by Deloitte (A British multinational professional services company).
Healthcare Insurance industry future trends: Impact of AI and Machine Learning
In the healthcare industry, Natural language processing is the dominant AI application that involves the review and classification of clinical documents.
NLP in the insurance industry allows to analyze unstructured patient’s clinical notes, create reports, transcribe the patient’s interactions, and perform conversational AI.
The global market size of NLP in the healthcare industry is expected to grow from $1.8 billion to $3.4 billion by 2026.²
By adopting NLP, AI and machine learning solutions will help your insurance company to get rid of manual, paper-based clinical and administrative processes which repetitive, error-prone, and time-taking too.
Use of key clinical AI solutions can result in a potential savings of $150 billion annually, for the United States.3 This indicates how AI is one of the most demanding insurance industry future trends.
Artificial intelligence and risk management in the insurance
The impact of AI on the future of insurance in the healthcare industry is experiencing traction and is considered to be the next-generation technology. Healthcare professionals need to understand how AI trends are shaping the insurance industry.
Importance of AI Risk Adjustment Tools
Through AI in the insurance sector, payers can analyze huge amounts of clinical notes with improved precision and spot unusual data patterns which often indicate fraud. Such inconsistencies are usually caused due to human error. AI in the insurance company can also benefit payers to detect fraud schemes, allowing them to take appropriate measures for fraud prevention.
How do insurance companies reduce risk?
By employing AI in your insurance company, it will help you predict and prioritize suspected disease conditions for coder review. The AI-enabled solution will enable a quick and highly efficient chart review process while maintaining coding accuracy and completeness.
How do insurance companies use AI to mitigate risk?
With the many advantages of AI, it is also currently one of the most demanding insurance industry future trends that will allow:
- Identify unreported HCC and ICD- 10 diagnosis codes
- Identify suspects while chart review
- Access to patient’s health history
- Automate the risk adjustment process
- Access to analytics to improve retrieval rates
- Maximizing coding accuracy and efficiency and completeness.
How is Risk Assessment and Risk Adjustment Solution affecting payer/insurance companies?
- RAAPID observed that our AI-Enabled Solution resulted in an additional 11 per cent to 15 per cent increase in suspected but unreported conditions captured.
- RAAPID.AI helps gain more accurate and complete coding. It has enabled a 3 per cent validation rate increase within our internal Quality Analysis (QA) oversight processes.
- RAAPID.AI has seen a reduction of 3 per cent to 10 per cent or more in chart retrieval requests.
How artificial intelligence will impact the insurance industry?
AI-enabled analytics will help you transform your insurance companies’ chart review operations in accuracy, even for large amounts of data. It will allow you to switch from the traditional chart review process to precision targeting of charts. In addition, its fewer chart retrieval requests will increase the efficiency of each chart review.
With the above, you can now understand how AI is one of the Insurance Industry’s future trends, and it could save $18 billion annually, as per Harvard Business Review.4
A study by Pricewaterhouse
-Coopers (PWC), a multinational professional services network of firms, conducted to understand the value of AI to the global economy, is expected to reach $15.7 billion, approximately, by 2030.5
_acnmedia/pdf-49/accenture-health-artificial-intelligence.pdf 4https://hbr.org/2018/05/10-promising-ai-applications-in-health-care 5https://www.pwc.com/gx/en/