AI Patient Assessment Portal for Video-Based Risk Screening
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Solution Overview
Problem
Current healthcare systems face challenges in efficiently identifying and addressing asymptomatic risk factors, leading to increased healthcare expenditures and inefficiencies due to fragmented care delivery and lack of access to comprehensive patient data, particularly for vulnerable populations.
Innovation Solution
An AI-driven platform for medical data collection and analysis that allows patients to perform assessments through a patient portal, using a camera to capture physical activities, analyze key points, and provide automated diagnoses and risk assessments for musculoskeletal injuries, leveraging machine learning algorithms to identify previously undetected risk factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional healthcare systems rely on physician judgment and experiential models for diagnosis, then clinical decisions can be made with available information, but asymptomatic risk factors remain undetected and healthcare expenditures increase
Solution Approach 1:
The system performs preliminary analysis of patient data using AI algorithms before clinical decisions are made. The platform proactively identifies asymptomatic risk factors by analyzing electronic health records, claims data, and other patient information in advance, enabling early intervention before conditions deteriorate or become symptomatic.
Solution Approach 2:
An AI-driven platform serves as an intermediary between fragmented healthcare data sources and clinical decision-makers. The system aggregates and analyzes data from multiple siloed systems (EHRs, claims databases, wearable devices) to provide comprehensive risk assessments that neither physicians nor payers could obtain independently.
2Productivity
If healthcare delivery systems remain fragmented and siloed, then existing organizational structures are maintained, but efficient and cost-effective care is prevented
Solution Approach 1:
The platform merges previously siloed healthcare data sources including electronic health records, claims data, wearable device data, and social determinants of health into a unified analytical system. This integration enables comprehensive patient risk assessment while maintaining connections to existing organizational structures through standardized data interfaces.
Solution Approach 2:
The AI platform serves multiple functions across different stakeholder groups: it provides risk assessments to physicians, cost analysis to payers, preventive recommendations to patients, and population health insights to healthcare systems. This multi-functionality addresses fragmentation by providing a single system that serves diverse needs.
3Adaptability or versatility
If employers are shielded from employee healthcare data by payers, then employee privacy is protected, but employers cannot leverage data to improve workforce health and productivity
Solution Approach 1:
The AI platform acts as a confidential intermediary that processes employee health data without requiring direct access to individual patient records. The system aggregates anonymized data to provide employers with population-level risk assessments and preventive health recommendations, enabling workforce health improvement while maintaining employee privacy through de-identification protocols.
4Measurement precision
If vulnerable populations cannot access care due to socioeconomic factors, then provider resources are preserved, but undiagnosed conditions deteriorate over time
Solution Approach 1:
The platform enables patients to perform self-assessments using mobile devices and wearable technology, eliminating the need for in-person clinical visits for initial screenings. Patients can complete medical assessments, upload data, and receive risk evaluations independently, making healthcare access feasible for vulnerable populations with limited transportation or provider availability.
Solution Approach 2:
The system replaces traditional mechanical healthcare delivery (in-person clinic visits, physical examinations) with digital alternatives including mobile app-based assessments, telehealth consultations, and AI-driven analysis of patient-submitted data. This substitution removes geographic and temporal barriers to care access while maintaining diagnostic capability.
Data Source
AI summary
A computer system for automatically performing medical diagnoses having a main portal configured to allow data communication with a user device, an AI bot in data communication with the main portal, the AI bot being configured to guide the user through a medical assessment, perform the medical assessment and diagnose the patient, wherein the AI bot is further configured to receive video data of the patient performing a physical activity, analyze each individual frame of the video using a custom trained model in order to diagnose the patient, a patient portal in data communication with a processing and communication module and the AI bot, a central database in data communication with the processing and communication module, an internal database, the AI bot and the patient portal, the central database being configured to facilitate an interconnection of the AI bot with the internal database and an external database.