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Case Study

enGen streamlines care for better member outcomes

  • Annual medical cost savings of $17 million
  • 2.5X increase in members served with case management
  • Average reported Net Promoter Score of 80

“We've cut down costs, but we're also taking care of more patient members. And if more people are getting the care they need, we're getting better health outcomes. We're bringing down medical costs and it all ties together.”

The Business Issue

As a wholly owned subsidiary of Highmark, enGen boasts a versatile ecosystem of innovative solutions infused with smart automation to help health plans and partners streamline the intricacies of their day-to-day operations. The company collaborates with 12 healthcare plans that serve more than 11 million members across the United States.

With an astonishing annual processing of 225 million claims a year, enGen needed the ability to deliver personalized care and coordinate complex cases at scale while keeping costs down and continually improving the member experience.

Disconnected systems and processes made that a challenge. enGen recognized the need to simplify the healthcare journey so members could focus on their health without the burden of insurance-related anxieties.

Beyond this, enGen recognized the evolution of care management practices over the past two decades. A heightened emphasis on return on investment (ROI), virtual solutions, value-based outcomes, and enhanced engagement with providers underscored the need for a holistic transformation approach. The objective extended beyond merely streamlining processes – it was about making healthcare more accessible, efficient, and member-centric.

The Solution

enGen employed a multi-product approach to deliver on its transformation goals. First, it created the Member Engagement Hub. Built on Pega Customer Decision Hub™, it orchestrates between channels and systems and provides next best actions thanks to an integration with the Member Listening System (MLS), which receives member health data and insights in real time. It enables members to move effortlessly between mobile devices, web, virtual assistants, the customer service support team, and their clinicians.

Clinicians using enGen’s clinical platform, Predictal™, access information from the Member Engagement Hub, which allows them to provide outreach to the right members at the right time. Built on Pega Care Management™, Predictal™ is an integrated, omni-channel platform across care management, utilization management, provider service, and engagement.

Crucial to the project’s success, enGen implemented AI-powered solutions, leveraging natural language processing (NLP) to automate formerly manual processes like authorization requests. This empowered clients with self-service capabilities, reducing reliance on IT departments and expediting tasks.

The Results

Recognizing the importance of value-based outcomes, enGen prioritized better engagement with healthcare providers, fostering collaborative efforts toward improved patient care. This omni-channel access to consistent, near-real-time data, results in better service, improved quality of care, healthier members, and a reduction in costs associated with systemic waste.

This approach yielded tangible results, including:

  • Annual medical cost savings of $17 million – a $1.72 million reduction in per month per member (PMPM) medical costs
  • 2.5X increase in members served with case management
  • Average reported Net Promoter Score of 80
  • Improved employee experience and productivity
  • Reduction in unnecessary emergency department visits by over 1%

Notably, administrative cost savings were achieved without an increase in staff, and the system facilitated the care of more patients within the measured timeframe. enGen's journey exemplified a strategic blend of technology, member-centric design, and proactive adaptation to the evolving healthcare landscape, positioning them for future success.

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Desafio: Excelência operacional Industry: Saúde Área do produto: Customer Decision Hub Área do produto: Plataforma
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