Chatbot-Mediated Medical Data Processing With Privacy Masking
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Solution Overview
Problem
There is a need for improved methods and systems for processing medical data in radiotherapy that allow users to process data more easily while ensuring the privacy and protection of patient data.
Innovation Solution
The system employs a client application and a chatbot to process medical data. The client application receives user commands in natural language, masks personal information, and then invokes the chatbot to determine actions or arguments. The chatbot processes the pre-processed user command to identify actions and arguments, which the client application then uses to process the medical data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If medical data is processed using traditional methods, then data processing capability is maintained, but ease of use deteriorates and user accessibility is reduced
Solution Approach 1:
A chatbot intermediary is introduced between the user and the medical data processing system. The chatbot receives natural language queries from users, translates them into appropriate data processing commands, and executes the operations. This mediator simplifies the interaction interface, allowing users to access complex data processing capabilities through simple conversational commands without needing to understand the underlying system complexity.
Solution Approach 2:
The traditional mechanical interface for data processing (requiring specific commands, filters, and parameters) is replaced with a natural language-based conversational interface. Users can query medical data using everyday language instead of technical commands, significantly improving ease of operation while the system automatically interprets and executes the requested operations.
2Reliability
If personal information is not masked, then data processing accuracy is maintained, but patient privacy protection deteriorates
Solution Approach 1:
The system performs preliminary masking of personal information in medical data before it is processed or stored. Identifiable patient information such as names, addresses, and other direct identifiers are replaced with anonymized values or tokens in advance. This preliminary action ensures that even if data is accessed or processed, patient privacy is protected while the medical information remains intact for analysis.
Solution Approach 2:
The chatbot system extracts and separates personal information from medical data, then masks or removes these identifiers before processing. By extracting PII (personally identifiable information) from the broader medical records, the system can process the medical information while discarding or anonymizing the sensitive personal data, thus protecting privacy without losing medical accuracy.
3Productivity
If comprehensive data processing is enabled, then productivity is improved, but ease of operation deteriorates due to increased system complexity
Solution Approach 1:
The chatbot enables self-service data processing where users can independently query, filter, and analyze medical data without requiring technical expertise or system training. The chatbot automatically handles complex data processing tasks, interpretation of results, and presentation of information, allowing users to perform comprehensive analysis through simple conversational interactions rather than manual system operation.
Data Source
AI summary
A method for processing medical data by a client application and a chatbot, includes: receiving, by the client application, a user command comprising natural language, the user command further comprising personal information; pre-processing, by the client application, the user command to mask the personal information; invoking the chatbot to determine an action and/or an argument from the pre-processed user command; and processing the medical data, by the client application, using a feature of the client application to perform the chatbot-determined action and/or argument on the medical data.