How Payers Can Use AI-Powered Chat for Iterative, In-the-Moment Analysis to Decrease Costs and Accelerate Time-to-Market

24 Sep, 2023 •

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Payers struggle to attain insights into the Electronic Enrollment Transmission (EET) with countless manual processes and need to access multiple systems. This slows time-to-market and lengthens the implementation timeline.  

Eliminating manual processes, accelerating enrollment, and easier client onboarding are all desired outcomes.    

Insights can be attained by leveraging an AI-driven chatbot. Importantly, it must be done in a way that guarantees reliable results and ensures the security of the data.  The new digital experience can be tailored for both National and EET groups. It will help reduce the administrative burden while providing competitive client onboarding processes.   

The challenge: not just ad hoc analysis, but “in-the-moment, iterative analysis”  

To say the challenge is simply “ad hoc analysis” understates the data challenge. The ad hoc nature of analysis is also both iterative and “in-the-moment.” The requirements cannot wait days for an ad hoc analysis by a BI or data team.  

BI reports often give a reasonable starting point for the investigation of an “in-the-moment” hypothesis. BI assets are developed by data analysis experts who understand the data well, and their efforts often solidly address the more obvious 80% of the reporting analysis requirements. But in many scenarios, the Electronic Enrollment Transmission and National Account groups need to go much deeper and pivot to many other related questions – all very quickly and iteratively, and in-the-moment.  

DvSum CADDI Value Proposition 

With DvSUM CADDI, the staff such as the care manager can quickly and easily know which patients need additional consultation and design appropriate care support. 

Complementing existing population health reporting and analytics with DvSum CADDI allows the payor’s teams to better allocate the right resources based on patient populations and to personalize patient engagement. This can lead to improvements in health outcomes, member retention, and ratings. 

In all, DvSum CADDI empowers payors to drive: 

  • Operational improvements  Decreased implementation timelines  
  • Elimination of manual processes  
  • Accelerated enrollment process   
  • Member satisfaction 

The following are examples where DvSum CADDI helps payors attain “in-the-moment,” fast, iterative insights from immense data sources. 

a. Electronic Enrollment Transmission (EET)  

Simply ask questions to attain basic information and actions:  

  • Contact information for the specific client or case.  
  • Information from the Census tool of the EET application.  
  • An export with the setup status of a new client along with the relevant facts.  
  • Specific details, e.g., total number of members, demographics summary, and status for individual members in the plan. 
  • Automated workflow, from a service connect to submit an access request. 

b. Member Attribution & Assignment 

Just ask simple questions to gain valuable insights:  

  • Which members are attributed to which providers post-enrollment?  
  • Directly affects aligned incentives under value-based care.  
  • How does attribution improve care, provider-member communication, payer-provider collaboration, and the efficacy of provider payment models?  
  • What is the effectiveness of tiered networks and performance criteria for maintenance of “high performing” provider networks? 

c. National Accounts 

Simply ask questions to attain basic information and actions: 

  • Extract sales & customer information from systems of record, eg, Salesforce.  
  • For a new case installation, automatically create a new customer in the appropriate system(s).  
  • Map changes in plan and benefit coverage across states and populations  
  • Aggregate coordination of benefits impact and cost of claims to (ASO) employers  
  • Evaluate plan changes and enrollment impact on healthcare cost, outcome, and employer/member experience trends. 

d. Broker Administration 

DvSum empowers users to monitor broker sales patterns for product churn. This is particularly in the small group market, channel effectiveness, broker metrics, etc. 

e. Operational Metrics  

Just chat to analyze data quickly, iteratively, and in-the-moment. 

Conclusion  

DvSum securely combines OpenAI’s GPT-4 with a powerful underlying data infrastructure to monitor critical open enrollment functions and processes, from Electronic Enrollment Transmission and National Accounts enrollment support, to member attribution and broker administration. This empowers staff to become more autonomous and productive “in-the-moment”.  Watch the recorded webinar, and contact us today to see how DvSum CADDI can help you. 

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