Readmission Risk Algorithm for Patient Segmentation
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Solution Overview
Problem
Hospitals face challenges in identifying and managing patients at risk for unplanned readmissions due to the complexity of determining appropriate inpatient treatments and post-discharge care, leading to increased costs and reduced quality of care.
Innovation Solution
A computerized method using a generic readmission risk algorithm applied to all patients, which assesses readmission risk based on patient profiles and generates a user interface for clinicians to manage patients at risk, incorporating clinical, social, and historical data to identify high-risk patients and provide targeted interventions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a generic readmission risk algorithm is applied to all patients, then readmission risk identification accuracy is improved, but system complexity increases
Solution Approach 1:
The readmission risk algorithm segments patients into different risk categories (low, medium, high risk) based on multiple factors including clinical data, social determinants, and historical information. This segmentation allows the system to manage complexity by treating different patient groups differently, focusing intensive resources on high-risk patients while using simpler approaches for low-risk patients.
Solution Approach 2:
The patent implements a universal readmission risk algorithm that can be applied to all patients regardless of their specific condition or demographics. This multi-functional algorithm integrates multiple data sources (clinical, social, historical) and can identify readmission risk across diverse patient populations, eliminating the need for separate algorithms for different patient groups.
2Measurement precision
If comprehensive patient data is collected for risk assessment, then prediction accuracy is improved, but data processing time increases
Solution Approach 1:
The system performs preliminary data collection and risk assessment activities during the patient's hospital stay, rather than waiting until discharge. Risk factors are identified and assessed in real-time as patient data becomes available, allowing the system to prepare risk assessments in advance of when they are most needed, reducing last-minute processing delays.
Solution Approach 2:
The patent replaces manual data processing and risk assessment with an automated computerized algorithm that can rapidly analyze comprehensive patient data. This substitution of mechanical/computational processing for manual analysis enables the system to handle large volumes of diverse data (clinical, social, historical) quickly and efficiently without proportionally increasing processing time.
3Reliability
If targeted interventions are provided to high-risk patients, then readmission prevention effectiveness is improved, but resource allocation complexity increases
Solution Approach 1:
The system applies different levels and types of interventions based on the specific needs and risk factors of individual patients or patient groups. Rather than implementing a uniform intervention approach for all high-risk patients, the system tailors interventions to local conditions and patient characteristics, such as providing different discharge planning intensities or follow-up care frequencies based on identified risk factors.
Solution Approach 2:
The patent dynamically adjusts intervention parameters (such as frequency of follow-up contacts, intensity of discharge planning, or type of post-discharge monitoring) based on the patient's risk level and changing conditions. This allows the system to optimize resource allocation by intensifying interventions for highest-risk patients while using lighter approaches for moderate-risk patients, reducing overall resource complexity while maintaining effectiveness.
Data Source
AI summary
Readmission risk of patients admitted to a healthcare facility are determined using a generic readmission risk algorithm. The readmission risk assessment of patients may be based on portions of a patient's profile and may be performed before, during, and after their index admission. Based on the readmission risk assessment of patients, those patients that are at a greater risk for readmission may be identified. A readmission prevention worklist may be provide that identifies those patients and facilitates managing the risk of readmission for those patients.