Risk-Value Reimbursement System for Healthcare Resource Allocation
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Solution Overview
Problem
Current healthcare reimbursement models, such as fee-for-service, often incentivize unnecessary services and redundancy, whereas value-based care models focus on quality but may not effectively allocate resources to patients at highest risk, leading to inefficiencies in care delivery.
Innovation Solution
A risk-value reimbursement system that computes patient risk scores based on health data, including diagnoses, vitals, demographics, and lab values, to prioritize resource allocation and reimbursement towards higher-risk patients, encouraging providers to deliver higher-quality care.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If fee-for-service reimbursement model is used, then providers receive higher payment for more services, but this leads to redundancy and service inflation
Solution Approach 1:
The patent changes the reimbursement parameter from quantity-based (fee-for-service) to value-based (quality and outcomes), thereby reducing redundant services while maintaining appropriate care volume through risk-adjusted payments
2Loss of substance
If value-based care model is used, then overcharging and service inflation are reduced, but resources are not effectively allocated to patients at highest risk
Solution Approach 1:
The patent applies local quality by differentiating reimbursement rates based on individual patient risk profiles and specific quality metrics, allowing resources to be concentrated on high-risk patients while maintaining value-based care principles across the entire population
3Ease of operation
If traditional care delivery models are used, then providers can deliver services, but quality measurement and resource prioritization are inefficient
Solution Approach 1:
The patent implements feedback mechanisms through quality metrics and risk-adjusted reimbursement that provide continuous information to providers about their performance, enabling improved quality measurement and informed resource allocation decisions
Data Source
AI summary
The system determines reimbursements to healthcare providers that provide care based on a novel risk-value reimbursement model, wherein the care is based on a patient risk score and the quality of care delivered. The system and method may include the process of obtaining variables of patient health data for a patient; determining a rank order correlation of the variables with an adverse health outcome; determining a risk score for the patient; sorting patient panels based on the risk score for each patient in the patient panel; determining a lower amount of time on a timer for a chart for the patient, in response to the risk score for the patient being higher than other risk scores for other patients in the patient panel; and resetting the timer, in response to an action by a provider.