AI’s impact on health insurance has been profound. From its beginnings as an automaton for repetitive tasks to its current use in personalised risk assessments and proactive healthcare efforts, AI has positioned itself as a key component in modern operations. Insurers can now offer customised insurance plans, more effectively detect fraud, and predict individual health outcomes with near-instant accuracy. As we dive deeper into the complex world of health insurance and AI, it’s clear that this technology has the potential to create a more streamlined, personalised, and inclusive health ecosystem for all involved. However, integrating AI into health insurance raises several issues that must be carefully considered, such as exacerbating existing inequalities, risking data privacy, and reducing human oversight and responsibility. As the industry navigates the challenges posed by AI implementation, it is essential to address these issues to ensure equitable and ethical health practices for all.
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AI Revolutionising Health Insurance.
Enhancing Customer Interaction
An AI-powered chatbot can answer policyholders’ questions about benefits, deductibles and claim status, taking the burden off of customer service reps. These virtual assistants can even walk policyholders through the claims filing process, ensuring everything is accurate and complete. At Cigna, one of the world’s largest healthcare service companies, AI-powered chatbots answer customer questions about benefits, eligibility and claims status, improving customer satisfaction and reducing call center volume. Cigna’s internal talent management systems use AI to help Cigna retain employees by recommending roles that match their skills, and 65% of roles are filled internally after implementation.
Faster Claim Settlements
AI can automate claim assessment, reduce paperwork, and minimise delays to ensure timely claim settlements for policyholders. Machine learning algorithms look at medical records, invoices, and other relevant information to validate claims quickly, providing policyholders a smooth experience during stressful times. AI can streamline claims adjudication by looking at medical records, identifying discrepancies, and identifying potential fraud. Not only does this reduce processing times, but it also allows adjusters to concentrate on more complex cases. Moreover, AI can also automate policy renewals. AI can send out personalised notifications and make it easier for policyholders to renew their policies online. For example, The NHIS (National Health Insurance Scheme), India’s government-sponsored health insurance program, is looking into using artificial intelligence (AI) to automate the claims processing process for millions of beneficiaries, aiming to reduce processing times and improve access to healthcare services.
Personalised Health Management
AI can help health insurance companies do more than act on claims data. It can analyse various factors, such as medical history, lifestyle habits, and genetic predisposition to certain chronic conditions, to identify those at risk of developing them. AI can also use predictive analytics to identify trends and patterns in health issues so that insurers can proactively engage policyholders, promote preventive screenings, or even create personalised wellness programs for them. Humana, one of the largest health insurance companies in the world, uses AI to identify people at a high risk for developing diabetes. It then launches targeted interventions, such as educational resources or wellness programs, to prevent the onset of diabetes. It can also use medical records to identify anomalies in medical records that may warrant further investigation, allowing for early intervention to improve health outcomes and reduce overall healthcare costs. For example, With Apollo Munich Health Insurance, you’ll have access to a health insurance program that encourages you to live a healthier lifestyle. You’ll be able to track your steps and other important health information through a mobile app and earn rewards for doing so. Apollo Munich Health Insurance’s mobile app uses AI algorithms to tailor recommendations and promote preventive healthcare practices.
Cost Efficiency
AI helps insurers save money on operational costs by automating administrative processes, underwriting, and identifying cost efficiencies. By reducing the number of manual processes, insurers can better allocate resources, resulting in better premiums for policyholders. For example, another prominent Indian insurer, Max Bupa, uses AI to analyse medical data and lifestyle information to evaluate risk profiles. This enables them to provide tailored health insurance plans that better meet policyholders’ needs.
Fraud Detection
Identifying fraudulent claims is a never-ending task. AI algorithms look for patterns, anomalies and historical data to identify suspicious activity. From duplicate claims to falsified medical records to identity theft, AI is a watchful eye, protecting insurers’ interests and building trust in the system.
Speedier Underwriting
Underwriting has traditionally been a time-consuming process that requires lengthy assessments. With the help of AI, underwriters can analyse applicants’ information in real-time. By using predictive models, underwriters can quickly assess risk factors such as medical history, lifestyle choices, and more. As a result, underwriting and policy issuance are faster, helping insurers serve more customers.
Unlocking the Power of Data
The healthcare industry produces many data – medical, claims, lifestyle, etc. We are analysing this data, which used to be tedious and time-consuming. AI recognises patterns and extracts valuable information from these huge data sets, especially machine learning algorithms. For example, Insure AI is an AI-driven platform developed by Star Health and Allied Insurance Company, one of India’s leading health insurers, in partnership with IBM. Insure AI analyses data from medical claims to predict future healthcare costs and detect fraudulent claims. The platform helps Star Health to process claims faster and better manage risk.
Dark Side of AI in Health Insurance
Algorithmic Bias and Discrimination
AI algorithms trained on historical data can reinforce existing racial or socioeconomic disparities in healthcare access. As a result, AI models may unfairly deny coverage or suggest higher premiums to certain demographics. For example, a 2019 investigation by ProPublica revealed that an artificial intelligence (AI) algorithm used by a leading health insurer discriminated against black patients and denied them access to essential healthcare services at rates higher than white patients.
Privacy Concerns and Data Security
AI systems depend on large amounts of personal health information. Security breaches can reveal sensitive information, resulting in identity theft and severe repercussions. For example, in 2021, a large health insurer suffered a data breach that exposed the personal data of millions of customers. This incident is a stark reminder of how vulnerable health data is in the era of artificial intelligence.
Over-reliance and Lack of Transparency
Many AI algorithms’ complexity and lack of transparency cause the Black Box Problem. This makes it hard to understand how they make decisions, leading to insurers relying on AI recommendations without human oversight and overlooking important factors. For example, a 2020 study by the Brookings Institution found that several insurers used AI to process claims without explaining the reasons behind denials to patients. This lack of disclosure makes it hard for patients to contest unfair decisions.
Job Displacement and the Human Touch
Artificial intelligence (AI) can automate many tasks but can’t replace human expertise. This is especially true in health insurance, where AI automation could lead to the loss of jobs in fields such as claims processing, customer service, and more. Many healthcare professionals rely heavily on AI for their day-to-day operations. If they rely too much on AI, they risk losing out on personalised care and the ability to interact with their patients.
Mitigating Risks and Ensuring Ethical Use
The downsides of artificial intelligence in health insurance are far from over. Implementing strong safeguards and focusing on ethical considerations can help us responsibly harness the potential of AI.
Here are Some of the Key Steps We Can Take:
- Data Governance: Strong data privacy regulations and security measures are necessary to protect sensitive health information.
- Algorithmic Fairness: Regular audits and AI bias detection techniques are essential to ensure that AI algorithms are accurate and unbiased.
- Human Oversight: Artificial intelligence should be seen as a tool to enhance human expertise, not to replace it. Healthcare professionals should always have the final say in critical decisions.
- Transparency and Explainability: The healthcare industry needs to shift to explainable AI models so patients and providers can understand the rationale behind AI-driven algorithms’ decisions.
Conclusion
The health insurance industry’s adoption of AI has opened the door to a new era of automation, customisation, and creativity. However, like all transformative technologies, AI presents its risks and challenges. From algorithmic biases and privacy issues to job displacement and transparency issues, various risks must be addressed to ensure AI’s ethical and fair use in the healthcare industry. However, the way forward is to implement strong safeguards, prioritise algorithmic integrity and transparency, and maintain human oversight. With proactive measures and risk mitigation, we can leverage the power of AI for better healthcare outcomes and a more sustainable and inclusive health ecosystem for all stakeholders.
