Driving Analytics Transformation for Major Healthcare Payor

A Dallas-based healthcare payor tailoring healthcare plans to their clients’ specific needs required an upgrade their data landscape. The company had data silos preventing them from easy data access and one complete, accurate source of truth for the whole organization. Important data residing in multiple systems necessitated inefficient manual processes and further degraded trust in data quality.

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Setting the Stage

Targeting three primary areas would have great impact toward improving data quality and access within the organization.

  • Claims Data Analysis

    Claims data currently living in multiple internal systems plus third-party processor data needed to transform into a single source of truth to enable the organization to perform accurate, efficient claims analysis.

  • Policy Lifecycle Analysis

    An end-to-end policy view (sales through claim payout) would give a better understanding of policy lifecycles and enable the organization to fully score each policy’s value.

  • Agent Hierarchy and Commission Payment

    Eliminating separate data sources for the sales teams and accounting departments would in turn eliminate internal conflict on agent hierarchy changes and commissions data, rebuilding trust across the organization.

Rebuilding data trust began by collecting data in an accurate, consumable format via a multifaceted approach.

Our Approach

We began by interviewing members of different departmental teams to fully understand the existing data landscape and concerns. Identifying all sources of information provided insight into the types of data analysis they were performing.

Our recommendations included modifying existing data structures to follow best practices, migrating data to the cloud for improved access across the organization, and automating manual processes through a collection of tools that improve efficiency and increase data quality.

We also devised and proposed a multi-phased project with detailed timelines and budgetary guidelines for each phase.

Impact

The organization achieved measurable impact from this project, improving their workflow, customer service, employee engagement and morale, and profitability.

Claims Data Analysis

  • Established a single source of truth for analyzing claims
  • Eliminated 520+ hours per year of manual processes
  • Provided new insight into claims processing backlog
  • Improved significant trust in data

Policy Lifecycle Analysis

  • Provided end-to-end visibility of all policies
  • Eliminated double or triple counting of policy revenue
  • Enhanced forecasting insight
  • Notably improved policy risk assessment
  • Significantly increased trust in data.

Agent Hierarchy and Commission Payment

  • Reflected real-time changes in agent hierarchy
  • Increased visibility in the productivity of agents, regions, and divisions
  • Increased accuracy of commission payouts
  • Increased trust in data across sales, management, operations, and accounting

About the Client

A Dallas-based healthcare payor tailoring healthcare plans to their clients’ specific needs required an upgrade their data landscape. The company had data silos preventing them from easy data access and one complete, accurate source of truth for the whole organization.

Key Outcomes

  • Building and migrating to a cloud data warehouse: A new cloud-based data warehouse enabled a modern approach to data architecture, providing the entire organization access to the same single source of high-quality data.
  • New data architecture: Restructuring data as it flows into the warehouse created consistency across disparate data sources, elements of new metadata, and a mechanism to monitor and improve data quality.
  • Data automation tools: Automating manual processes truly modernized the data platform, saving time and dramatically improving overall data quality.
  • Self-service visual analytics tools: Empowering the organization with self-service visual analytics tools put better insights directly into the hands of more employees.

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