The Future of Health Insurance

The Future of Health Insurance - Gargash Insurance 15 Sep, 2022

After pandemic, heath has become the most important factor of our lives. Explore the factors influencing the future of health insurance in UAE.

Modernization of the Healthcare Sector

The healthcare sector has become increasingly modern in the past decade with the integration of technology. Operations, diagnostics, and treatment are all becoming digital with the help of Artificial Intelligence (AI) backed mechanisms. The health insurance market is no exception. AI is set to transform this industry as well in the near future.

Currently, your standard health insurance plan is based on a number of factors, such as:

  • Pre-existing health conditions
  • Age and Gender
  • Family medical history
  • Profession and lifestyle

These usually determine the terms of the policy and the cost of premium. However, change is anticipated with developing technology and advanced analytics. Personalized plans are the future of health insurance.

Quick Read Section

  • Four major factors affecting your health insurance plan are :
  • Pre-existing health conditions
  • Age and Gender
  • Family medical history
  • Profession and lifestyle
  • Your health data will be monitored using personalization engines to design the perfect health insurance plan for you
  • Ethical limitations pertain linked to the easy availability of patient data and its ownership.
  • Steps to address concerns regarding data privacy.

The Wave of Personalization

Social media and E-commerce websites are early adopters of personalization. They actively collect consumer data using cookies to analyse the content consumed by users and then relay targeted ads based on this data.

The health insurance market can leverage the benefits of personalization tool to formulate customized plans for customers. With the rapid development of AI and easy availability of  insights on consumer behaviour, it is now possible for companies to devise individual-centric solutions for their unique requirements.

How it will work:

  1. Data collection: Involves individual snapshots created using all publicly available data such as digital health records which include family health history, hospital visits, pharmacy records, medical tests etc. Additionally, behavioural data would be collected through personal wearables which track fitness and physical health markers.
  2. Identifying key points: A machine learning algorithm can analyse these snapshots to identify each customer’s care touch points and their triggers. For instance, for an individual with a family history of diabetes, the algorithm assesses the risk factors, outlines preventive measures, and sets up regular check-ups. This data can be used to build a customised health plan suited for the person at-risk for diabetes.
  3. ‘Pay as you live’ model: With real-time updates data updates, insurance underwriting will also become a continuous process. The increased availability of predictive analytics enables a personalized pricing model that includes a unique and holistic coverage for the customer. A report by McKinsey and Company outlines the example of a South African firm that has started collecting health data through wearables and provides incentives for preventive care while pricing their plans on the basis of the customer’s engagement with their health.


Personalization and Data Privacy & Protection

Our technological advancements have made it possible to easily access data which was previously unattainable. As the sensitivity of the data increase, the risk and accountability for those dealing with the data also increases.

 There are several ethical concerns that arise when such information is circulated. These include:

  • Data Privacy – Devising a personalized health plan requires detailed personal health information. The issue arises when there is unauthorized data sharing of it. Such confidentiality breaches are the biggest point of concern for an individual that has trusted an entity with their information. Organizations must work towards building ‘trust-architecture’ or data sharing that is privacy-protected.
  • Data Protection - Multiple stakeholders have access to customers’ digital health records. The sensitive nature of this data makes it vulnerable to cyber threats. It is extremely important to cautiously deal with it. This calls for strict enforcement of data protection mechanisms to prevent cyber-attacks.

The existing cyber laws may not be adequate for addressing violations of data privacy. The integration of health insurance with AI makes it even more challenging to protect sensitive data. It becomes a shared responsibility for those dealing with it to always prioritize customer privacy.  

Addressing concerns over data privacy

As the wave of personalization takes over health insurance, it is essential to adopt necessary measures to protect customer interest with respect to their personal information. Given below are some suggested steps at the individual, organizational and policy level:

  • At the individual level, you should only reach out to reputed insurance brokers and organizations to minimize risk. You should also read all contracts regarding data collection and sharing carefully, before signing. Ensure all parties with access to your data are listed explicitly to avoid conflicts later.
  • At the organizational level, privacy protected data sharing systems should be installed beforehand. The access to individual data should be restricted to the concerned departments. And all employees must strictly maintain confidentiality.
  • At the policy level, there is a need for data protection laws globally that highlight privacy to prevent misuse of loopholes. These must be enforced across all sectors to protect consumer interest.

The future of health insurance is around the corner. Personalized health plans will be a game changer – if implemented ethically.

If you are looking for health insurance plans that can meet your unique needs, contact our team of health insurance experts today.


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