Information Builders Case Studies RCM Brain Weds AI and Predictive Analytics

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	RCM Brain Weds AI and Predictive Analytics Information Builders

RCM Brain Weds AI and Predictive Analytics

Information Builders

Technology Category	Analytics & Modeling - Predictive Analytics Analytics & Modeling - Real Time Analytics Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries	Healthcare & Hospitals
Applicable Functions	Business Operation
Use Cases	Predictive Maintenance Process Control & Optimization Root Cause Analysis & Diagnosis
Services	Data Science Services System Integration
Challenge	RCM Brain needed a flexible analytics solution with comprehensive data management, data visualization, and predictive analytics capabilities that could be embedded into a larger software platform. The revenue cycle management (RCM) process that medical providers use to track revenue from patient visits is complex and error-prone, leading to high administrative costs and revenue leakage. RCM data is spread among various systems, making it difficult to create comprehensive reports. The challenge was to automate this process and reduce the costs associated with inaccurate medical claims. Read More
About Customer	RCM Brain is an AI-driven revenue cycle rules engine and workflow automation platform. It uses artificially intelligent workflow bots to connect data and execute tasks across legacy billing systems, clearinghouses, and payer websites. The company was founded to simplify the revenue cycle management (RCM) workflow with the help of BETH, an AI system that leverages machine learning technology and Information Builders’ WebFOCUS business intelligence (BI) and analytics platform to boost the efficiency and productivity of claims-processing staff. The system combines an AI rules engine and robotic process automation with data processing and analytics technology from Information Builders. Read More
Solution	RCM Brain used WebFOCUS Portal to build a series of analytics dashboards that permit RCM workers to visualize and drill into claims data through dynamic charts. The system can reverse-engineer payer denials and discover patterns in the data, gradually building a predictive layer to intercept and interrogate errant claims prior to submission to the payer. WebFOCUS also performs root-cause analysis to surface errors in the claims billing process. It provides visual controls over the AI processing engine, allowing managers and executives to monitor RCM workflows and obtain a holistic view of RCM activities. The company plans to enhance the system with new types of analytics, including summarized content and an ad hoc analytics environment anchored by InfoAssist. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Analytics & Modeling - Real Time Analytics

Application Infrastructure & Middleware - Data Exchange & Integration

Applicable Industries

Healthcare & Hospitals

Applicable Functions

Business Operation

Use Cases

Predictive Maintenance

Process Control & Optimization

Root Cause Analysis & Diagnosis

Services

Data Science Services

System Integration

Challenge

RCM Brain needed a flexible analytics solution with comprehensive data management, data visualization, and predictive analytics capabilities that could be embedded into a larger software platform. The revenue cycle management (RCM) process that medical providers use to track revenue from patient visits is complex and error-prone, leading to high administrative costs and revenue leakage. RCM data is spread among various systems, making it difficult to create comprehensive reports. The challenge was to automate this process and reduce the costs associated with inaccurate medical claims.

About Customer

RCM Brain is an AI-driven revenue cycle rules engine and workflow automation platform. It uses artificially intelligent workflow bots to connect data and execute tasks across legacy billing systems, clearinghouses, and payer websites. The company was founded to simplify the revenue cycle management (RCM) workflow with the help of BETH, an AI system that leverages machine learning technology and Information Builders’ WebFOCUS business intelligence (BI) and analytics platform to boost the efficiency and productivity of claims-processing staff. The system combines an AI rules engine and robotic process automation with data processing and analytics technology from Information Builders.

Solution

RCM Brain used WebFOCUS Portal to build a series of analytics dashboards that permit RCM workers to visualize and drill into claims data through dynamic charts. The system can reverse-engineer payer denials and discover patterns in the data, gradually building a predictive layer to intercept and interrogate errant claims prior to submission to the payer. WebFOCUS also performs root-cause analysis to surface errors in the claims billing process. It provides visual controls over the AI processing engine, allowing managers and executives to monitor RCM workflows and obtain a holistic view of RCM activities. The company plans to enhance the system with new types of analytics, including summarized content and an ad hoc analytics environment anchored by InfoAssist.

Impact #1	By automating workflows and surfacing errors in the claims billing process, claims processing staff are three to ten times more productive.
Impact #2	WebFOCUS allows managers to monitor RCM workflow and obtain a holistic view of RCM activities.
Impact #3	The system can reverse-engineer payer denials and discover patterns in the data, gradually building a predictive layer to intercept and interrogate errant claims prior to submission to the payer.

Impact #1

By automating workflows and surfacing errors in the claims billing process, claims processing staff are three to ten times more productive.

Impact #2

WebFOCUS allows managers to monitor RCM workflow and obtain a holistic view of RCM activities.

Impact #3

The system can reverse-engineer payer denials and discover patterns in the data, gradually building a predictive layer to intercept and interrogate errant claims prior to submission to the payer.

Benefit #1	15 percent of healthcare expenditures go towards the administrative aspects of billing and paying claims.
Benefit #2	Annual revenue leakage of 5 to 11 percent due to underpayments that aren’t identified.
Benefit #3	Inaccurate medical claims cost the U.S. healthcare system billions per year.

Benefit #1

15 percent of healthcare expenditures go towards the administrative aspects of billing and paying claims.

Benefit #2

Annual revenue leakage of 5 to 11 percent due to underpayments that aren’t identified.

Benefit #3

Inaccurate medical claims cost the U.S. healthcare system billions per year.

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Overview

RCM Brain Weds AI and Predictive Analytics

Operational Impact

Quantitative Benefit