AI Analytics Platform for Automated Hospital Performance Testing

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Solution Overview

Problem

Hospitals lack an effective method to evaluate their performance in customer interactions, such as scheduling and user experience, leading to inefficiencies and increased costs due to manual data collection and subjective assessment.

Innovation Solution

An analytics gathering, analysis, and recommendation platform using artificial intelligence for automated data collection, analysis, and recommendation generation, which conducts testing calls to gather metrics and provide objective recommendations for improving hospital operations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual data collection and subjective assessment methods are used, then implementation simplicity is maintained, but measurement precision and reliability of performance evaluation deteriorate

Engineering Contradiction:

Improveperformance evaluation accuracyVSAvoiddata collection system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system performs automated self-assessment through robotic agents that independently conduct testing calls, collect data, and generate performance evaluations without requiring human intervention for each assessment cycle

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual data collection and subjective human assessment are replaced with automated robotic agents using AI and machine learning algorithms to perform testing calls and objectively analyze performance metrics

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If manual data collection methods are used, then device complexity is low, but productivity and time efficiency deteriorate

Engineering Contradiction:

Improvedata collection efficiencyVSAvoidtime for performance evaluation

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system pre-generates multiple robotic agents with different user profiles before assessment campaigns begin, allowing them to be immediately deployed for testing calls without preparation delays

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

Multiple robotic agents operate simultaneously and continuously conduct testing calls across different time periods, eliminating idle time and maintaining constant data collection flow

Inventive Principle:

Principle #20Continuity of useful action

3Reliability

If subjective assessment methods are used, then ease of operation is maintained, but reliability and objectivity of evaluation deteriorate

Engineering Contradiction:

Improveevaluation objectivityVSAvoidsystem operation simplicity

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system implements closed-loop feedback where robotic agents collect performance data, the machine learning model analyzes results, and actionable insights are fed back to organizations for improvement, creating continuous objective evaluation cycles

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

Robotic agents serve as intermediaries between organizations and the assessment system, conducting testing calls objectively without human bias while collecting and transmitting data through the AI analysis platform

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS10264120B2Automated data collection and analytics

Publication Date: 2019.04.16 ACCENTURE GLOBAL SOLUTIONS LTD

AI summary

A device may generate a call plan for a set of testing calls. The device may initiate a testing call to a communication device associated with a target, of the set of targets, using a user profile of the set of user profiles. The device may initiate monitoring for the testing call to identify information associated with the target during the testing call. The device may generate one or more responses to one or more queries based on the user profile. The device may transmit the one or more responses to the one or more queries based on generating the one or more responses to the one or more queries. The device may process stored data regarding testing calls to generate a recommendation relating to the set of targets for the set of testing calls. The device may communicate with one or more other devices to implement the recommendation.