CSRationalized

A next generation Healthcare contact center application bridging the gap between people and distributed systems to ensure data accuracy & integrity.

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Inspiration

One of the frequent tasks of the CSR in healthcare contact center is to update the practitioner NPI and the Specialty information. In present situation, with the available feature in the Pega Customer Service for HC, CSR captures the data in a live interaction from Provider and sends it to back office. Back-office users validate the data manually with external systems like NPPES or CMS and update the system of records. In Case of inaccuracy of data, it could lead to an unwanted rejection or rework. This finally impacts on the Customer satisfaction score significantly. It also has consequences for the overall performance of contact center.

What it does

CSRationalized provides a comprehensive set of features to help CSRs to accurately update the data in the system of record:

• Potentially matched providers from NPPES Registry for Practitioner NPI update • On demand NPPES Registry lookup to identify appropriate NPI • NPI validation against system of record to avoid data integrity issue at the end
• NPI validation against NPPES Registry to ensure accuracy of NPI before updating system of records • Practitioner Specialty lookup using CMS Taxonomy dataset for Practitioner specialty update • Potentially matched provider specialty from NPPES Registry based on Practitioner’s NPI • Specialty validation against NPPES Registry to ensure accuracy of Specialty before updating system of record

How we built it

CSRationalized built on:

• Pega CSHC 8.7 • Pega HCIF 8.7 • Pega Platform 8.7.1

It leverages all the out of the box features of Pega CSHC and extends the built-in capabilities of “Update Practitioner NPI” and “Update Specialties” intents.

The following design and build strategy used:

  1. Requirement: With comprehensive research, it was found that the two most commonly used tasks for CSR are to update the request of NPI and specialty for Practitioners. The update takes time due to lack of integration between the application and NPPES and taxonomy application. The present solution integrates all the sources to create 360° solutions.

  2. Design: The basic backbone of the application was Pega CSHC. Most of the application backbone including Case life cycle, Personas, Channels and Data types were created/extended here.

We have leveraged the exposed public API from NPPES and CMS as mentioned below:

• NPPES: https://npiregistry.cms.hhs.gov/api • CMS: https://data.cms.gov/data-api/v1/dataset/88bd5fb4-7b5c-4107-8131-23c485e00ef0/data

  1. Build: The Build stage was broken down into multiple substages. First the basic workflow was extended. Then, respective connectors were created for consuming NPPES and CMS public API.

  2. Test: Finally, the solution was evaluated end to end using various test users.

Overall, it was a rewarding experience for the team to be able to build and deliver an end-to-end solution within a short span.

Challenges we ran into

  1. Conceiving, designing and building and end-to-end solution within a short timeframe was certainly a challenge
  2. Aligning the data model of CSRationalized with integration data structure of NPPES and Taxonomy service needed significant research
  3. Organization in-network Pega server was not allowing to connect to the public API due to organizational security restrictions
  4. Identification of proper test data keeping synergy across NPPES, CMS and system of record

Accomplishments that we're proud of

  1. Considering the current situation, the entire team was remotely situated. We used primarily MS Teams conferencing to communicate, which was of great help
  2. In spite of having customer project work and personal commitment, the team put in a lot of dedication and hard work to make this solution possible
  3. Being able to deliver a multitude of features with a lot of R&D is something we take a lot of pride from
  4. Gathered knowledge on making the public API as trusted source to organization in-network Pega server

What we learned

  1. Understanding the business case of updating the Practitioner’s NPI and specialty/taxonomy
  2. Gap analysis to align the data model of CSRationalized with integration data structure of NPPES and Taxonomy service
  3. Conceiving, designing, and building an application within such a short period of time provided us a great opportunity to learn and work together as a team
  4. Soft skill leveraging different software during the preparation of media files around the solution

What's next for CSRationalized

CSRationalized can be extended in future to include:

  1. Comprehensive scoring model comprising of configurable parameters to drive system recommended potentially matched providers
  2. Extend “Update Practitioner licenses” intent leveraging NPPES public API to ensure data accuracy & integrity during live interaction
  3. Extend “Update Practitioner address” intent leveraging USPS public API to enable address scrubbing during live interaction

Built With

  • cms-api
  • nppes-api
  • pega
  • pega-cshc
  • pega-hcif
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