CASE STUDY

Eliminating Data Silos saves Healthcare Payer nearly $4 MM yearly

The Challenge

Clinical personnel at a top regional health insurance organization were unable to make real time decisions about care management because of disparate data systems and data silos. Access to this data in real time would allow care managers to drive greater quality care for members. Some major hurdles attributed to these data silos included:

Multiple manual processes to consolidate data
• Technical debt from duplicative data in multiple silos
• Decreased capacity to work on advanced analytics caused by the increased need for data wrangling
• The difficulties of building technical teams outside of IT

The Conflict


Care managers at a healthcare payer organization are suffering from siloed data effecting data quality and hampering capabilities to make real time decisions creating risk for both members and the organization.

The Solution

Integrate disparate data sources from data silos into a quality data models (QDM) to help improve data integrity and standardization with the support of a holistic methodology that combines People (data experts), Process (data governance), and Technology (modern data platform). This proven framework will eliminate data fragmentation as well as enhance data exchange capabilities for the organization.

Goals

Unify all data sources to eliminate data silos and redundancies giving personnel access to quality data that will improve care management capabilities.

The Result

By centralizing all data sources and aligning that framework with business goals, the organization began breaking down data silos and optimized their data with a consolidated approach that saved the organization nearly $4 MM yearly in operational efficiencies. Within this centralized approach, clinical personnel now have timely access to the full breadth of trusted data and can make informed decisions about best care practices that relate directly to the member’s health.

To take this a step further, harnessing a single source of quality data allowed for continuous tracking and monitoring of quality metrics over time, making it possible for automation of patient follow-ups and outreach. Automation helped increase quality scores (HEDIS and Stars Ratings) and more importantly, improve the quality of care that members experience for the organization.

Contact Us

Healthcare

Interoperability in Healthcare: A Patient-First Framework

Healthcare Interoperability is a framework where systems are coordinated to provide standardized methods of interacting with patient data.
Healthcare

Pitfalls to Avoid when implementing Health Information Exchange

In recent years, Health Information Exchange (HIE) capabilities have helped mobilize patient data allowing clinicians and healthcare managers to provide near real time diagnosis closing the gap on member care.
Strategy

Scrum Master Best Practices to Accelerate Data Projects

Scrum is a Delivery Framework, under the Agile umbrella, that can accelerate initiatives, breakdown data silos, and bring organizations together as a team to progress any project. Individuals certified in Scrum are known as Scrum Masters.