INTELERA || RPA-Powered Data Integration for Unified Healthcare Operations

Industry

Healthcare / Medical Equipment

Product

RPA-Based Data Integration Framework

Technology Stack

Python

Quick Summary

IntelERA partnered with a leading in-home respiratory care provider to implement an RPA-driven data integration solution. The project automated the consolidation of fragmented systems into a centralized database, streamlining business processes and enhancing operational efficiency across the organization.

Problem Definition / Challenges

The client, a provider of software solutions for HME and pharmacy businesses, had grown through multiple acquisitions, resulting in a scattered ecosystem of databases in various formats and versions. This fragmentation posed challenges in maintaining consistency across critical processes such as:

Payer management
Patient data
Provider and facility records
CMNs, PARs, and ILSOs
Sales order handling
Documentation workflows

Manual interventions were frequent, error-prone, and resource-intensive, leading to increased operational costs and delays in service delivery.

Our Approach / Solution

IntelERA implemented an RPA-based integration framework to automate and standardize data handling across systems. RPA bots were designed to:

Extract data from disparate databases

Transform and validate information using defined business rules

Load standardized data into a unified system

Automate routine workflows and eliminate manual touchpoints

The RPA bots operated 24/7 with high accuracy, reducing the need for manual reconciliation and allowing teams to focus on higher-value tasks.

The Result

The centralized and automated framework not only improved current operations but also established a scalable foundation for future healthcare innovations and automation initiatives. The RPA-powered solution delivered substantial improvements:

14 legacy systems consolidated into 1 unified database

72% reduction in manual data entry tasks

40% decrease in operational and IT maintenance costs

3x faster data processing and reconciliation across departments

99.2% data accuracy rate achieved across all critical workflows

Annual savings of over $500,000 in licensing, labor, and infrastructure costs

Improved turnaround time for documentation and patient onboarding by 50%