AI-Powered Knowledge Management for Healthcare Support

In the complex world of healthcare services, managing member interactions efficiently is crucial. This document outlines the process of leveraging an AI-powered knowledge management system to streamline operations, providing consistent and accurate information. By unifying data from multiple sources, this system enhances the ability of service agents to handle inquiries, ensuring compliance and improving member satisfaction.

Step 1

The healthcare industry operates in a highly complex service environment. Member services teams must efficiently manage benefits questions, claims reviews, demographic changes, grievances, appeals, and compliance-driven workflows, often within a single interaction. However, the information required for these tasks is dispersed across various systems like CRM platforms, claims databases, knowledge management systems, provider files, and PDF documents. Agents often switch between seven to twelve different systems, manually search PDFs, interpret policies on the spot, and document every action for CMS and HIPAA compliance.

Step 2

High turnover and lengthy training cycles result in predictable challenges: inconsistent responses, long handling times, compliance risks, and frustrated members. This is where the knowledge management AI employee comes into play. It functions beyond a typical chatbot or lookup system, serving as a reasoning engine powered by agentic AI. This system unifies CRM data, claims information, and knowledge base content, creating contextual understanding before proceeding with actions.

Step 3

The AI system integrates with MR's generative workflow engine, where retrieval and reasoning agents collaborate with intelligent action agents. This collaboration ensures that processes are explainable, consistent, and fully auditable. In a live support scenario at TP Healthcare, the agent can request the AI to retrieve the full profile of a member named John Smith for review before addressing the member's query.

Step 4

Before resolving the member's query, the agent reviews the complete profile of John Smith.

Step 5

The AI employee synthesizes a unified overview by accessing CRM member portals and knowledge bases. It confirms John's enrollment in a dual special needs plan, details his active coverage, and summarizes his benefits across dental, vision, hearing, transportation, and OTC allowances. The system also identifies any recent interactions, such as prior benefits inquiries, synthesizing information from multiple systems.

Step 6

To proceed further, the agent verifies John's identity by requesting, "Please verify the member's identity."

Step 7

The identity verification process, as per the CRM system, has been completed. Authentication details have been provided, validating John's name, date of birth, member ID, and the last four digits of the SSN. This verification is compiled from multiple applications.

Step 8

To retrieve the claim details for the member, the AI employee consults the member portal for structured eligibility data. This action allows the agent to review John's benefits and claim information.

Step 9

From the member portal, the AI employee gathers key details and provides them to the agent. Based on this information, the agent can request the AI to explain how to file a new claim for John, including the necessary steps outlined in the knowledge management system's process documentation.

Step 10

The AI employee assists in preparing grievance details based on the claim information.

Step 11

Each piece of information aligns with the evidence of the coverage document. The agent then asks the AI employee to assist in creating a grievance case summary.

Step 12

Using the provided information, the AI employee creates a draft of the grievance case summary.

Step 13

The case management system is utilized to draft a record of the grievance summary, detailing previous grievances submitted by John. The agent instructs the AI employee to file the grievance case in the system.

Step 14

The grievance case is prepared for submission.

Step 15

The preparation is complete.

Step 16

The grievance has been successfully filed in the case management system based on the summary and member interaction. After confirmation and reasoning by the agent, the case is logged. This scenario demonstrates a unified agent capable of reasoning, synthesizing, and executing actions across fragmented systems with human confirmation.

Step 17

With the information gathered, the system can also generate a ticket.

Step 18

The system files the ticket based on the grievance details.

Step 19

Compiling all gathered information and context from the conversation, the system creates a ticket and prompts the agent to finalize communication with the member.

Step 20

The system generates the member communication, ready for submission by the agent.