How Striim Enhances Healthcare at Discovery Health with Real-Time Data

3 Minute Read

Discovery Health, originating in South Africa, has transcended borders to extend its services to over 40 million customers across more than 40 global markets, encompassing regions in Asia, EMEA, and the Americas. Since its inception in 1992, the company has remained steadfast in its core purpose: “to make people healthier and to enhance and protect their lives.”

As a multifaceted financial services organization, Discovery Health operates in various sectors including healthcare, life insurance, short-term insurance, long-term savings, banking, and wellness. Through its diversified portfolio, Discovery Health aims to provide comprehensive support and services to individuals and communities worldwide, fostering a culture of health and well-being.

Challenges

The primary obstacle for Discovery Health was the sheer scale of data across disparate systems and technologies. This complexity led to significant delays in data processing, impacting their ability to make timely decisions and adversely affecting the customer experience. The integration of these various data sources was cumbersome, with daily ETL (Extract, Transform, Load) processes that delayed actionable insights for up to 24 hours. Such delays were untenable in a field where real-time data could mean the difference in enhancing health outcomes and operational efficiency.

Striim’s Solution

In response to these challenges, Striim stepped in with its cutting-edge Change Data Capture (CDC) technology, which revolutionized the way Discovery Health approached data integration. Transitioning from daily ETL processes, Striim’s CDC technology facilitated seamless integration of disparate systems, reducing data processing delays from 24 hours to seconds. Endorsed by Oracle, Striim provided reliability and scalability while leveraging expertise in logical database replication. Through continuous improvement and optimization, Discovery Health streamlined its data infrastructure, empowering informed decision-making and enhancing customer experiences globally.

"We have a significant software portfolio and the ability to tie that into modern ML use cases where we need to do that is important for us. We are a highly data-driven organization and the ability to tie in predictive models or propensity models is really critical to our strategy. The objective with Striim and CDC usage was to simplify pipelines and minimize latency for real-time decision support."
Nick Alexander
Senior System Architect at Discovery Health

Results

The implementation of Striim’s solution had a profound impact on multiple aspects of Discovery Health’s operations:

  • Reduction in data processing delays from 24 hours to seconds: Real-time decision making allowed prompt responses to evolving market dynamics, such as changes in customer behavior or healthcare trends.
  • Enhanced operational efficiency and cost-savings: Real-time data processing capabilities streamlined workflows and minimized manual interventions, resulting in significant operational cost savings.
  • Personalized customer engagement: Predictive analytics helped incentivize healthier choices among members, leading to deeper engagement and loyalty.
  • Improved health outcomes: Real-time intelligence analyzed data to promote healthier lifestyles among members, encouraging active participation in wellness activities and ultimately increasing life expectancy and enhancing overall well-being.

Real-Time Data’s Role in Modern Healthcare

Striim’s implementation at Discovery Health represents a significant advancement in the use of real-time data within the healthcare industry. By reducing data processing times from 24 hours to mere seconds, Striim has empowered Discovery Health to make quicker and more effective decisions, improving both operational efficiency and the quality of customer service. This has led to more personalized interactions with clients and notably better health outcomes for individuals under their care. Striim demonstrates a practical application of real-time data processing that other healthcare providers can look to as a model for enhancing service delivery and patient care globally.

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