Balance PrimeAudit

AI-driven Healthcare Data Recognition & Analysis Platform

USA Healthcare web Retrospective audits

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.

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Discover how our cutting-edge AI platform transforms healthcare audits and replaces manual analysis with instant and intelligent insights.

ClIENT & BUSINESS CHALLENGE

β€œReplacing Human Fallibility, Saving Time, and Reducing Errors”

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.Β 

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.

PROJECT DESCRIPTION

β€œEstablishing an AI-Driven Multi-Functional Tool”

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.
Project Overview

1 week

Process

  • Learning the project, understanding idea, business, scope, etc.

Deliverables

  • Project Overview

Initial
Communication

Initial
Analysis

Discovery

8 weeks

Process

  • Business process analysis
  • Analyzed key process gaps, manual activities
  • Analyzed the datasets, calculations, discrepancies and outputs
  • Defined rules for data processing automation and preventing errors, mismatches

Deliverables

  • Data flows
  • Data structuring & modeling
  • Decision modeling
  • Specification for AI model development with data rules processing

Business
Analysis

UX
Design

Development
Plan

Development phase

8 months

Process

  • Sprint 0: Preparation and requirement gathering
  • Sprint 1: System architecture design and tool conceptualization
  • Sprint 2: Design of the Data Recognition Instrument and initial ML model creation
  • Sprint 3: Advanced Machine Learning enhancement and feedback loop setup
  • Sprint 4: Creation of the Board of Linked Files
  • Sprint 5: Development of Data Audit Capabilities
  • Sprint 6: Integration of HIPAA-compliant security measures
  • Sprint 7: Platform optimization and user experience enhancement
  • Sprint 8: Testing and bug fixing, stage 1 release
  • Sprint 9 and 10: Feedback collection, further improvements, and bug fixing
  • Sprint 11: Platform scalability and expansion
  • Sprint 12: Final testing, documentation, and launch preparations

Deliverables

  • A robust and scalable AI-driven HIPAA-compliant audit platform.
  • A system that can swiftly process and recognize thousands of documents with advanced machine learning capabilities.
  • Data recognition, linking, and auditing tools to ensure accuracy and consistency.
  • Comprehensive documentation for users and administrators.
  • The platform ready to increase efficiency, minimize human error, and ensure swift financial recovery for healthcare institutions.

Iterative Process
by Sprints

Project Overview

1 week

  • Initial Communication
  • Initial Analysis

Discovery

8 weeks

  • Business Analysis
  • UX Design
  • Development Plan

Development phase

8 months

  • Iterative Process by Sprints
Skip section

Project Overview

1 week

Process

  • Learning the project, understanding idea, business, scope, etc.

Deliverables

  • Project Overview
two
one

solution

β€œRevealing the AI Tool Driving Audit Productivity”

Linkup Studio has innovatively designed and developed the HIPAA-compliant Balance PrimeAudit AI tool. This platform boasts lightning-fast automated recognition of thousands of documents, including PDFs, image files, and CSV, XLSX, and XLS formats. With its advanced Machine Learning capabilities, it can identify and categorize key-value pairs.

In essence, the platform auto-generates a frameless board that links files and tables with the same patient ID, names, invoice numbers, or other crucial parameters. This feature serves to equip audit managers with comprehensive, organized, and ready-to-analyze information, streamlining their further workflow. On top of that, the data analysis component of the product facilitates an automated check of incomplete or damaged data with a single click. This feature rectifies sporadic errors, ensuring data consistency and accuracy.Β 

Our AI platform has increased efficiency for our client, a healthcare audit company. It has freed up roughly 70% of the time previously devoted to manual research and data processing. Linkup Studio's engineering efforts have largely mitigated issues related to corrupted data in tables, substantially minimizing human error.

Technology Stack:

OpenCV

Scikit

Pytorch

Pandas

NetworkX

Azure AI

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