Worker Stress Prediction Model Using Activity Data
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Solution Overview
Problem
Current methods for detecting and managing worker stress in organizations, such as hospitals, are manual, costly, and provide only a snapshot view of stress, with limitations in identifying root causes and varying perceptions of stress among workers.
Innovation Solution
A computer-implemented method that receives information about a worker's activity and uses a prediction model, trained with activity data and subjective stress assessments, to predict the worker's stress state, thereby generating an indication for modifying organizational processes to alleviate stress.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual stress assessment services are used with questionnaires and interviews, then stress analysis can be performed, but the process becomes expensive and time-consuming
Solution Approach 1:
The patent replaces manual mechanical assessment processes (questionnaires, interviews, consultant analysis) with an automated computer-based system that collects activity data, processes it through algorithms, and generates stress assessments automatically, eliminating the need for human consultants while maintaining or improving assessment accuracy
Solution Approach 2:
The system creates a digital copy of the stress assessment process by collecting and analyzing activity data from various sources to generate a comprehensive stress profile, replacing the need for physical presence of assessors and manual data collection methods
2Loss of information
If manual stress analysis is performed by consultants, then root causes can be identified, but only a snapshot view is provided and it limits the number of features that can be analyzed
Solution Approach 1:
The system is designed to handle multiple types of data sources and analysis methods within a single unified platform, capable of processing activity data from various sources (electronic health records, scheduling systems, communication tools) and applying different analytical approaches to comprehensively assess worker stress
Solution Approach 2:
The patent replaces manual consultant analysis with automated computational algorithms that can process large volumes of data across multiple dimensions simultaneously, identifying patterns and root causes that would be impossible for human analysts to detect manually
3Adaptability or versatility
If different users have different perceptions about stress, then individual stress experiences are captured, but consistent organization-wide stress measurement becomes difficult
Solution Approach 1:
The system allows for individualized stress assessment by analyzing personal activity patterns and characteristics for each worker while maintaining organization-wide consistency through standardized data collection methods and uniform analytical algorithms that can be applied across all employees
Solution Approach 2:
The system incorporates feedback loops where stress assessments and activity data are continuously collected, analyzed, and used to refine the measurement model, allowing the system to adapt to individual worker patterns while maintaining consistent organizational metrics through iterative improvement
Data Source
AI summary
In an embodiment, a method (100) is described. The method comprises receiving (102) information about an activity of a worker associated with an organization. The method further comprises predicting (104), using a prediction model, a stress state of the worker based on the information and a stress assessment provided by the worker. The method further comprises generating (106) an indication of whether a process for implementation by the organization is to be modified in view of the predicted stress state of the worker.