Implementing and using product and plan flattening feature

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Implementing and using the product and plan flattening feature / This is the approved revision of this page, as well as being the most recent.
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Implementing and using product and plan flattening feature

Description Details about implementing and using the product and plan flattening feature in PCS
Version as of 8.5
Application Product Composer for Healthcare
Capability/Industry Area Healthcare



Product and plan flattening[edit]

Pega Product Composer for Healthcare (PCS) is a healthcare application that is built on Pega Foundation for Healthcare. One of the powerful features in PCS is data reuse based on a structured inheritance model. This requires that product and plan data are stored in a nested fashion with many layers of inheritance potentially defining coverage information. Only incremental changes for coverage information are stored at each layer in the products and plans. Obtaining a complete view of the cost shares that are associated with a plan requires complex navigation of this data structure in the clipboard. As is consistent with any Pega application, all data is XML and Pega blob-based.

To assist with this, PCS has a feature which reformats (or flattens) the product and plan data objects into a data model which is much more traversable. Using this feature is one of the recommended ways to extract product and plan data from the application.

Before you begin[edit]

The following articles cover the actual process of flattening and how to automate it using configuration controls:

Behind the scenes, the new Auto flattening job work object is created whenever there is a request for flattening. There is a dedicated queue assigned on a separate node, which handles the actual flattening jobs.This ensures that running the flattening process does not impact the performance of the application.The Pending Auto Flatten Entities dedicated workbasket, ensures complete transparency into the status of each flattening job. Each job might contain multiple products and plans. You can see the exact details at all times.

The data model for the flattened data structures (FDS) is updated any time the corresponding data models for the primary data entities in PCS are updated. By using the built-in extension points, you can add more custom properties to the FDS and flattening process which ensures that all relevant properties that are specific to the implementation layer are also available as part of the flattening extract.

Use case examples[edit]

FDS is the recommended source for all integration and data extraction from PCS. The following describes some use cases:

Claims Adjudication[edit]

For high-performing claims adjudication systems which rely on the product repository as the source of truth for benefit determination, the ability to get to the right benefit and associated cost shares in a timely manner is critical. By using FDS, you avoid time-consuming navigation of the inheritance tree. For such business scenarios, FDS is an out-of-the-box PCS feature which takes a product or plan and transforms them into multiple data instances which have all the benefit and cost share data that are associated with the plan. FDS contains all the information to determine the benefit, all cost share data, all limit data, and pricing information. Allowing for decoupling in enterprise architecture, the FDS data model is part of Pega Foundation for Healthcare and thus can be used for claims adjudication by Pega Smart Claims Engine or any claims processing system.

API based integration[edit]

All PCS APIs use FDS as the source for integration with other Pega Healthcare products – Pega Customer Service for Healthcare, Pega Smart Claims Engine, and Pega Sales Automation for Healthcare.

Incremental product and plan updates[edit]

By selectively parsing through the regenerated XML files (compare old and new plan XML), you can derive the changes made to the products and plans. This has many use cases, such as publishing only the changes for approval or regulatory compliance.

Summary[edit]

You now have the detailed walkthrough of the flattening process, the configuration options to automate it, and the possible use cases for leveraging the flattened data. This helps you to successfully integrate PCS into your existing enterprise architecture.