Patient Risk Assessment via Multi-Source Data Analytics
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Solution Overview
Problem
Current healthcare systems face challenges in timely and widespread assessment of patient risks, such as sepsis, pressure injuries, and falls, due to sporadic risk assessments and limited availability of information to caregivers.
Innovation Solution
A system comprising an analytics engine that collects data from various medical equipment, including patient support apparatus, physiological monitors, and incontinence detection pads, to calculate real-time risk scores for sepsis, falls, and pressure injuries, and adjusts caregiver rounding intervals based on these scores, with data displayed on multiple platforms for caregivers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If risk assessments are performed sporadically with prolonged periods between assessments, then the complexity of continuous monitoring is reduced, but the timeliness of risk information is deteriorated
Solution Approach 1:
The system enables automatic self-assessment by integrating data collection from existing medical equipment (physiological monitors, patient support apparatus, locating systems) that continuously track patient status without requiring manual intervention. The analytics engine automatically processes this data to generate risk scores, eliminating the need for sporadic manual assessments while maintaining system simplicity through automated self-monitoring.
Solution Approach 2:
The system establishes continuous risk assessment by continuously collecting data from multiple equipment sources and continuously analyzing this data to update risk scores in real-time. This continuous action replaces sporadic assessments, ensuring timely risk information is always available without requiring complex intermittent monitoring protocols.
2Ease of operation
If risk assessment information is available only at limited locations such as EMR computers or master nurse station computers, then the system complexity is reduced, but the accessibility of risk information to caregivers is deteriorated
Solution Approach 1:
The system makes risk assessment information universally accessible across multiple device types and locations including EMR computers, master nurse station computers, room computers, and mobile devices. Each device type serves multiple functions by displaying risk scores and enabling caregiver interactions, eliminating the limitation of single-location access while maintaining manageable system complexity through standardized information delivery protocols.
Solution Approach 2:
The system adds spatial dimensions to information accessibility by distributing risk assessment data across multiple physical locations and device platforms simultaneously. Instead of confining information to a single location, the system projects risk scores across the entire healthcare facility through networked devices, enabling caregivers to access information at the point of care without increasing operational complexity.
3Productivity
If caregiver rounding intervals are fixed, then the ease of scheduling is improved, but the responsiveness to changing patient risk levels is deteriorated
Solution Approach 1:
The system implements dynamic caregiver rounding intervals that automatically adjust based on real-time patient risk scores. When risk scores increase, rounding intervals are shortened to increase monitoring frequency; when risk scores decrease, intervals are extended. This dynamic adjustment optimizes caregiver productivity by focusing attention on high-risk patients while reducing unnecessary visits to low-risk patients, without requiring complex manual scheduling changes.
Solution Approach 2:
The system establishes a feedback loop where patient risk scores continuously inform caregiver rounding interval adjustments. The analytics engine monitors risk score changes and automatically modifies rounding intervals in response, creating a responsive system that adapts to changing patient conditions. This feedback mechanism enhances productivity by aligning caregiver presence with actual patient needs without requiring complex manual intervention.
Data Source
AI summary
Apparatus for assessing medical risks of a patient includes an analytics engine and equipment that provides data to the analytics engine. The analytics engine analyzes the data from the equipment to determine a sepsis risk score, a falls risk score, and a pressure injury score. The apparatus further include displays that are communicatively coupled to the analytics engine and that display the sepsis, falls, and pressure injury risk scores. The displays include a status board display located at a master nurse station, an in-room display provided by a room station of a nurse call system, an electronic medical records (EMR) display of an EMR computer, and a mobile device display of a mobile device of a caregiver assigned to the patient.