i3Claim: End to end Claims Processing Automation solution

With increasing complexities and evolving consumer demands, digitisation of the claims process has become essential for insurers to ensure fast settlement & payment of claims as well as drive customer satisfaction and set standards of service.

However, traditional claims processes involve intensive document-driven operations and the processing of non-structured data in multiple formats/nomenclature, making it difficult for insurers to process claims efficiently and quickly.

i3claim helps in capturing significantly more data-points in much lesser handling time. It reduces the extent of manual data capture and human errors in the entire claims process by more than 60%, making it much faster and extremely scalable.

i3claim accepts data input from a variety of sources like Hospitals, Pharmacies and Diagnostic centres. It extracts, classifies, and standardizes non-structured data present across multiple documents.

i3claim reduces the claims process to a single queue, by automating several parallel activities. This improves efficiency and leads to a reduction in cashless discharge time from 4 hours to less than 30 minutes for 90% of the cases. AI-assisted processing covers accurate capture of Non-payable and tariff comparison on 60% of the line-items. This has led to an average of USD 200-5000 savings per claim compared to manual processing.

Medical Informatics Corp.’s (MIC) mission is to deliver next-generation technologies to unify patient monitoring workflows for healthcare systems. MIC’s decade of innovation with its clinical platform, Sickbay, integrates over 30,000 vendor-neutral signals on two percent of hospital beds with over 10,000 clinical users in the United States. Most hospital systems lack native resolution data aggregated through a single source, instead deploying a multi-device strategy that silos data and data access time frames. The Sickbay Clinical Platform stands alone as the only FDA-cleared platform to aggregate time-series waveform data across disparate devices at native resolution. Current bedside devices delete data on average after 72 hours, while Sickbay saves the data indefinitely. Sickbay provides a portal through which care providers can review aggregated, time-synchronized data, annotate it, and collaborate to create algorithms (including ML & AI) and evaluate post-event care. Those algorithms and care models can then be reintroduced into the platform to advance care and innovation. Simply put, Sickbay provides the hospital teams their data from anywhere, anytime, to optimize workflows, analysis, and risk stratification across the patient care spectrum. The diverse team at MIC is fundamentally unlocking a blue ocean of new patient monitoring capabilities for ourselves, our partners, and our clients. MIC’s Sickbay saves lives, improves outcomes, streamlines strategy and technologies, and reduces the overall caring cost for hospital patients nationwide.

The EHR is intended to be a point of care reference to support billing. Traditionally, only documenting discreet vitals from patient monitoring devices at single points.

Sickbay Clinical Platform:

• captures consolidated, persistent, time-series waveform data from networked and non-networked bedside devices at its native resolution
• re-displays near real-time, time aligned signals at an average latency of <25 mSec
• integration of risk scores and analytics

Sickbay is a single, interconnected platform that is designed to support dozens of use cases, therefore competition is dependent upon the use case. In addition to the data agggregation, consolidation, and visualilzation differences referenced under EHR functionality, key differentiators in patient monitoring & virtual care include: 

• vendor neutral device integration
• web-based to support monitoring on any PC, tablet, phone or embedded EHR workflow
• flexible, modular design to enable ability to monitor 50+ patients across units, facilities, and vendors
• unlimited retrospective data, from one second to one year+, to support building and sharing of trends, CDI documentation support, quality reporting
• integration, development and deployment of near real-time risk scores and analytics into established workflows
• automated documentation of vitals, ECG strips, and event trends into the EHR