The OpenIMIS initiative drives an interoperable agenda for both the provider and payer players globally. The current deployments in Nepal and Tanzania have priority developments focused on Claims Management, and Members management that would greatly impact efficiency for the different stakeholders.

As Healthix, we wish to replicate our success in Kenya to Nepal where we have developed and deployed similar integrated solutions for Payer and Provider stakeholders. We shall automate claim processing with fraud detection while improving on the JLN Processes of improving Claims Management.

Today, Artificial Intelligence (AI) techniques such as Machine Learning (ML) can be used to discover patterns from non-linear datasets (Figure 2).

The AI techniques are coded to ensure that the predictable and linear processes can be flagged out in the claims as early as during submission. Figure 3 shows the sample AI processes that we shall use to discover linear flags that need to be watched.

Based on the learned pattern, the algorithms can predict payments on a claim; or even identify potential fraudulent claims and flag them for investigation. Insurers now have the option of achieving far better claims management by utilizing the technology in the following ways:

1. Use rule-based engine to pre-assess claims while automating the evaluation process.
2. Use artificial intelligence to automate claims fraud detection through rich data analytics.
3. Use machine learning to predict patterns of claim volume.
4. Augment loss analysis.

Improved Claim Review

The Improved Claim Review requirement describes two distinct mechanisms aiming at Claim processing automation. To enhance openIMIS functionality, our specific assignment will be to improve the functionality of the new platform by providing Python-based Configurable Claim Review Engine; and AI-based Claim Automated Adjudication and fraud detection.