Delivering enterprise-wide efficiencies at Paysafe through Intelligent Automation

about LucidAct

LucidAct is a patient care application that seamlessly integrates the patient’s journey with healthcare providers’ workflows. The application automates time-consuming tasks, such as pre-filled forms, e-signatures, voice-to-text transcription, and bridges the gap between remote patient monitoring devices and the care team’s workflows.

The Challenge

  • Bridging the Gap: LucidAct faced the challenge of connecting remote patient monitoring devices with healthcare providers’ workflows to enable proactive intervention in potential adverse events.
  • Workflow Integration: Integrating the application with existing Electronic Medical Record (EMR)/Electronic Health Record (EHR) systems and Hospital Management Systems required careful coordination and seamless data exchange.
  • Predictive Analytics: Developing algorithms for analyzing patient flow, drop-out analysis, and predicting the conversion of a new patient to test and treatment processes demanded advanced predictive analytics capabilities.

What did
Edvenswa do

  • Sole Technology Partner: Edvenswa served as LucidAct’s exclusive technology partner, providing end-to-end product engineering support.
  • Web and Mobile Application Development: Edvenswa developed and continues to maintain the comprehensive web and mobile application for LucidAct. The team leveraged Angular, Node.js, Java Spring, and Hibernate MVC technologies to ensure robust and scalable solutions.
  • Application Engineering, DevOps, and Maintenance: Edvenswa provided comprehensive support in application engineering, DevOps, and ongoing maintenance, ensuring smooth operation and optimal performance of the LucidAct application.
  • Integration with EMR/EHR and Hospital Management Systems: Edvenswa facilitated the seamless integration of LucidAct with existing EMR/EHR systems and Hospital Management Systems, enabling smooth data exchange and interoperability.
  • Predictive Analytics: Edvenswa developed advanced predictive analytics capabilities within LucidAct. This involved designing and implementing algorithms for patient flow analysis, drop-out analysis, and the prediction of new patient conversion to test and treatment processes.

The Results

The technology that we use to support LucidAct

JavaScript
Angular
Node.JS
Hibernate
Java
DevOps
MVC

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