ParaDocs Health offers an AI-driven chronic disease management platform that integrates with existing electronic medical records (EMRs) to automate patient data collection and streamline administrative tasks. This solution reduces the reliance on spreadsheets and manual processes, enabling primary care providers to efficiently manage population health and close care gaps, ultimately improving their risk adjustment factor (RAF) scores.
Funding
$280K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Primary care providers often struggle with inefficient chronic disease management due to reliance on manual data collection, spreadsheets, and fragmented electronic medical record (EMR) systems. This leads to difficulties in identifying active patients, understanding disease prevalence, and closing care gaps, ultimately impacting risk adjustment factor (RAF) scores.
Solution
ParaDocs Health offers an AI-driven chronic disease management platform, ParaDocs Relay, designed to integrate with existing EMRs and streamline population health management. The platform automates patient data collection, provides comprehensive visibility into patient populations, and identifies open care gaps. By offering a single source of truth for population health data, ParaDocs Relay enables providers to improve RAF scores, optimize quality care, and reduce administrative burdens associated with manual processes. The system also offers AI-driven nudges to providers, delivered through a side-loaded EMR application, to improve care gap closure.
Target Audience
The primary target audience includes primary care organizations and providers seeking to improve chronic disease management, optimize RAF scores, and enhance population health outcomes.
Features
- Integration with existing EMR systems for automated patient data collection
- Comprehensive dashboards displaying active patients, disease prevalence, and open care gaps
- RAF score prediction and tracking of recapture rate progress
- AI-driven provider nudges for improved care gap closure
- Side-loaded EMR application for receiving and approving insights
- Identification of suspect care gaps and opportunities to recapture HCC codes
- Secure data handling that respects native clinical workflows