How an Agile Development Pod Revolutionized Healthcare Data Management

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Dynamic Data in a Stagnant System

Our client, a prominent player in the healthcare sector, specializes in brokering large medical healthcare-related purchases and curating valuable healthcare data.

Their revenue streams involve securing cost-effective deals for aggregated hospital equipment purchases and repackaging categorized healthcare information for resale to members.

With so much data to parse and so many disparate customer systems to send reports to, the company found it challenging to efficiently deliver relevant and timely data to its members.

The existing process involved manual requests, manual data pulls, and manual downloads…a hugely cumbersome and time-consuming experience. The need for a more streamlined and user-friendly approach prompted the company to seek innovative solutions.

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Already connected in an eight-year partnership with this company, Launch responded to their challenge by proposing a new approach: a software engineering “pod” of developers. By using a dedicated team to rapidly churn out new and improved features, we believed we could spearhead an evolution of the company’s data exchange platform.

Our client agreed—though they were surprised by our proposed six-month delivery—and we leaped into action. Our Software Engineering Studio rapidly assembled a Scrum-centered pod and built a feature list. The pod’s objectives: improve flexibility, accelerate time to market, optimize resource utilization, and elevate quality standards.

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Dynamic Delivery for an Agile Platform

Using an Agile approach to facilitate quick adaptations to evolving business needs, the pod leaned into our customer’s focus on member-centric delivery while accelerating the development cycles. And sure enough, in just six months, the pod successfully delivered a streamlined, user-friendly experience with powerful intelligence and processing abilities. Here's how it works.

1. Customers log into a query-building app that knows who they are and what subscription and access they have. The customer can drag, drop, and filter data queries and simply hit submit - just like shopping online.
2. Once a customer submits a query, the data processor we built kicks in, parsing the request and fetching the data from various systems.
3. The processed dataset is then delivered automatically through one of two channels, depending on size. There's one channel for larger datasets (which auto-sends the member a notification with a link), and another that's like an email inbox for the specific customer.
4. We also built a dashboard that allows customers to schedule regular automatic data deliveries - whether they need that information monthly, quarterly, or whenever the dataset refreshes.
   

Immediately, our client’s data management capabilities—and their customer experience—soared. A couple of key points:

• The Agile framework enabled adaptability, swift delivery, and significant value creation for not only our client, but for their customers.
• The modular architecture of the solution allowed for easy integration with existing systems—whether our client’s customers wanted a turnkey solution or preferred to customize based on their specific requirements, the data exchange platform offered flexibility and scalability.
• As a result, customers noted that their user experiences had vastly improved.

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Dynamic Platform for an Ever-Evolving Era

Encouraged by the success of the initial deployment, Launch is poised to extend Agile pods across our client’s departments and business needs. For a company that delivers important healthcare data to so many healthcare organizations, the ability to move swiftly, deliver accurately, and foster growth across clinical environments is key to their success.

This data exchange platform—delivered in only six months and prepared for ongoing in-house maintenance—not only addresses the company’s immediate challenges. It also positions the organization for sustained and scaling performance in the critical, competitive healthcare data management market.

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Data maturity is the key to good organizational decisions, growth trajectory, and AI readiness. Is your data doing everything it can for your organization? Take the Data Maturity Self-Assessment to find any gaps - so you're ready for your next bold move.