Automated Workload Mitigation for Diminished Capacity
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Solution Overview
Problem
Medical events, such as illnesses or medical procedures, can diminish an individual's working capacity, leading to disruptions in the workplace, and existing solutions lack effective methods to mitigate these disruptions efficiently.
Innovation Solution
A computer-implemented system that receives prescription information, uses machine learning to determine the impact of medical conditions and medication side effects on job roles, and generates mitigation instructions to minimize disruptions, including rescheduling meetings, updating communication statuses, and rebalancing workloads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If an automated system is implemented to detect and mitigate diminished working capacity, then productivity is improved through automatic mitigation actions, but device complexity increases due to the need for prescription information processing and machine learning integration
Solution Approach 1:
The patent introduces a pharmacy system as an intermediary that already stores prescription information, which is then accessed by the automated mitigation system. This intermediary approach allows the system to obtain necessary medical data without directly integrating with complex medical record systems, thereby reducing overall system complexity while enabling automated detection and mitigation of diminished working capacity
Solution Approach 2:
The system performs multiple functions through a single integrated platform: detecting diminished working capacity, determining its cause (condition or side effect), predicting duration, and executing mitigation actions. This multi-functionality consolidates what would otherwise require separate systems into one unified solution, improving productivity without proportionally increasing complexity
2Measurement precision
If comprehensive prescription information is processed to determine working capacity impact, then measurement precision is improved in assessing diminished capacity, but loss of time increases due to data processing requirements
Solution Approach 1:
The system pre-processes and structures prescription information when it is first received from the pharmacy system, organizing data about medications, conditions, and side effects into an accessible format. This preliminary action ensures that when a diminished working capacity event is detected, the system can quickly retrieve and analyze relevant information without time-consuming processing delays, thereby maintaining both precision and speed
Data Source
AI summary
A computer-implemented method comprising: receiving, by a computing device, prescription information for an individual identifying a medication and a condition; identifying, by the computing device, job roles impacted by the condition; identifying, by the computing device, job roles impacted by side effects of the medication; determining, by the computing device, that a working capacity of the individual is diminished by the condition or the side effects of the medication based on job roles of the individual; generating, by the computing device, mitigation instructions in response to the determining; and executing, by the computing device, the mitigation instructions.