After a dedicated year of hard work, Linkup Studio delivered an AI-based HIPAA-compliant platform from scratch that greatly simplifies the healthcare audit process. With just a couple of clicks, this innovative platform recognizes, links, and verifies vast quantities of documents from healthcare providers' archives. This accelerates the process of identifying additional revenue from \"zero balance\" accounts, enabling swift and efficient financial recovery.

Our solution has transformed the audit process, reducing countless hours of manual document analysis to mere seconds. Managers can now swiftly identify up to 5% of underpaid contracts from various insurance companies. This allows for the recovery of millions of dollars to medical centers, hospitals, clinics, and other healthcare facilities across the US. It's not just a step towards efficiency – it's a leap towards profitability and fair compensation in healthcare.

Our client is dedicated to delivering retrospective audits to healthcare facilities throughout the US. As of January 2023, Definitive Healthcare HospitalView indicates over 7,000 medical providers in the country. Many of these providers struggle with underpaid "zero balance" care accounts. This issue largely stems from various insurance company policies and other factors. Even though the industry boasted an impressive total revenue of $2.829 trillion in 2022, many US healthcare facilities lose millions yearly. The reason is difficulties in identifying and collecting underpayments from managed care payers.

Our client specializes in auditing and examining healthcare providers "zero balance" accounts up to two years old. They successfully retrieve additional revenue.

They reached out to Linkup Studio with a request to develop a comprehensive AI system that could automate their complex processes. Their goal was to shorten the time their managers often spent on a single project and reduce the inevitable human errors that can occur when dealing with work on such a large scale.

Linkup Studio team tackled a set of pivotal tasks to create this robust solution:

Creating a System Architecture: Our solution features a robust system architecture that supports efficient processing and data storage. We meticulously identified and designed system components, defined their interfaces and relationships, and implemented design patterns and tactics for an optimal user experience and enhanced performance.
Developing a Data Recognition Instrument: We crafted a data recognition tool to simplify the complex task of data extraction. By aggregating data from various files into single, user-friendly tables, this instrument effectively streamlines data management, enhancing efficiency and readability.
Designing Advanced Machine Learning: We detected and analyzed gaps and errors after initial automated processing. Therefore, our advanced machine learning tool improves the accuracy of the data tables. It's trained to spot and understand keys and values in healthcare invoices and other provided documents, reducing the need for manual checks and making corrections after data recognition.
Producing a Board of Linked Files: To alleviate the labor-intensive process for audit managers, we developed an automated feature to link files and tables sharing the same patient ID, names, invoice numbers, or other key parameters. This feature allows users to operate with matched projects, streamlining the initial phase of data investigation and its management.
Creating Data Audit Capabilities: Given the immense volumes of data from insurance and healthcare institutions, occasional errors are inevitable. To mitigate these instances, we created a data audit capability. This feature of Linkup Studio’s solution automatically analyzes similar documents and suggests options that could replace incorrect entries, alleviating the need to manually trace the error's source.