Healthcare Insurer Transforms Drug Refill Process with Skan AI

  • IndustryHealthcare Payer
  • Company Size 100,000+
  • Revenue $6B+
  • Location United States
01

Our Client

This Fortune 500 company leverages technology to provide health insurance for millions of people across the U.S. For their customers, they merge the power of data with a full range of benefits to improve the healthcare experience from top to bottom.

02

Objective

The organization knew that the drug refill process was executed with a lot of variations, leading to inconsistencies and operational inefficiencies which had a negative impact on customer experience and operating costs. To tackle this challenge, the organization needed a timely, reliable way to measure process variants and analyze root causes in refill transactions. This included capturing data to understand the different transaction times associated with the variations. By quantifying the time differences, the major drivers of variation could be pinpointed.  

Additionally, there was a need to measure how long it took team members to document refill calls, and to identify any duplication of effort that was occurring. Both of these were suspected to be opportunities to streamline workflows and improve efficiency.  

Finally, user actions that often caused delays or inefficiencies must be identified through process discovery and analysis. Addressing these opportunities would enable the development of corrective measures to standardize and optimize the refill process, enhancing consistency, efficiency and the overall customer experience. 

Cost Savings
$20M+
in potential savings identified.
Saving Opportunity
$3.7M
annual savings identified through software systems development opportunities.
03

Solution

Skan AI generated data-driven insights into the end-end business process and workflows across different teams, locations, and software applications used for various case types. Skan AI identified significant process variations in how different groups handled refill cases, even for the same case type. Skan AI also pointed out redundancies in user actions that led to duplication of effort.  

Digging deeper into the root causes, Skan AI revealed that certain users were taking inefficient routes to processes cases because they lacked training on specific software applications. With Skan AI's insights, the team also uncovered suboptimal application usage patterns, where employees spent time in general-purpose applications versus tailored specialty applications that would save time.

Overall, Skan AI's process intelligence platform provided data-backed insights into process variations, redundant work, and application usage that revealed improvement opportunities across teams, locations, and software systems.  

04

Outcome

With Skan AI, the client identified $20 million in potential savings and $3.7 million in annual savings through software development opportunities. The initial assessment revealed a high dependency on generic software applications that required manual switching between multiple systems, leading to duplication of effort and wasted time. To address this inefficiency, strategic recommendations were made to streamline workflows by consolidating and integrating software systems. 

The client used Skan AI's insights to reduce time spent switching between applications by mapping out workflows and processes to determine optimal system integration points. Common actions were bundled into simplified workflows within a single application, significantly reducing time wasted navigating between multiple software windows and logins.  

By optimizing software systems and eliminating duplicative efforts, employees are spending more time on high-value tasks instead of administrative work. This resulted in greater productivity and innovation, allowing the company to develop new products and revenue streams more efficiently. 

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