The healthcare industry is rapidly adopting artificial intelligence (AI) to improve patient outcomes, lower costs, and make processes more efficient. One area that stands to benefit tremendously from AI is health insurance. From accelerating claims processing to detecting fraud, AI has the potential to transform health insurance plans.
Improving Diagnostic Accuracy
Artificial intelligence promises to significantly improve diagnostic accuracy in healthcare. One example is using advanced machine learning systems to analyse medical images and patient data. Research indicates that these AI tools could reduce errors in diagnosis by 30-50% or more. By catching conditions earlier and recommending targeted treatment plans, such systems can greatly improve patient outcomes. Some areas where AI diagnostics are proving valuable include:
Detecting Cancer
Using deep learning, AI systems can analyse scans and detect malignant tumours with expert-level accuracy. By speeding up diagnosis, this allows treatment to begin sooner, improving survival rates.
Assessing Bone Health
AI tools can evaluate bone density scans to measure risks of fracture or breakage. This data helps insurers offer preventative care to high-risk individuals.
Reading Radiology Scans
Automated interpretation of complex radiology scans makes diagnosis efficient. Instead of waiting for a radiologist’s manual review, AI systems can analyse images immediately.
By improving the accuracy of diagnoses, insurers can ensure patients get targeted treatment faster, leading to better outcomes.
Streamlining Claims Processing
Another major area for health insurance companies is claims processing. AI promises to make filing, assessing the legitimacy, and settling claims quicker. Natural Language Processing (NLP) techniques can extract information from doctors’ notes, lab reports, and medical bills to validate claims and speed up approvals.
Some key applications include
- Automating Data Entry: AI can pull relevant data from forms and medical documents to auto-populate insurance claims, eliminating manual entry.
- Checking for Errors and Fraud: Machine learning algorithms can run claims data against established rules to systematically check for duplicate claims, errors, and fraud. This further reduces manual reviews.
- Settling Claims: By pulling data from systems and cross-referencing policies, AI can offer on-the-spot settlements for straightforward claims instead of making customers wait.
By taking over administrative tasks, AI systems enable insurers to settle legitimate claims faster, improving customer satisfaction.
Increasing Affordability with Risk Assessment
For health insurance companies, calculating an individual’s risk profile is necessary to decide premium amounts. AI is helping make this process more accurate. By analysing clinical data, medical history, and lifestyle information, AI systems can build detailed health profiles.
Consider a few cases
1. Finding Adverse Drug Interactions – AI can run a patient’s medications against their conditions and genetic data to alert doctors about potential adverse interactions, preventing hospitalisations.
2. Identifying Disease Risk Factors – Machine learning models can isolate key risk factors for conditions like heart disease, stroke, and diabetes by finding patterns in population data. High-risk individuals can then be advised of preventative steps.
3. Offering Personalised Premiums – Detailed risk modelling by AI allows actuaries to offer targeted premiums based on an individual’s predicted healthcare costs. For healthy policyholders, this increases affordability.
By supporting granular risk assessment using the latest medical research data, AI enables insurers to correctly price policies based on an individual’s health profile. This results in a fair and transparent mechanism that increases affordability.
The Bottom Line
AI is ushering in an era of improved efficiency, accuracy, and customisation across healthcare. For insurance companies, the benefits range from minimised costs to healthier policyholders. However, to unlock AI’s full potential, the technology needs abundant high-quality data to learn from regarding patient outcomes. As healthcare providers digitise their practices and consolidate medical data, it sets the stage for AI innovation to continue transforming the global insurance industry.