Linguistically Selective Web Forms for Accurate Case Data
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Solution Overview
Problem
Existing systems lack efficient and linguistically-selective methods for generating web forms, particularly in the pharmacovigilance industry, leading to low response rates and inaccurate data collection due to language barriers and manual processing inefficiencies.
Innovation Solution
A system and method for generating linguistically-selective web forms that determine case data criteria, select appropriate web form templates, and generate forms in the language of the recipient, thereby improving data accuracy and response rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual processing is used for web form generation, then flexibility and adaptability are maintained, but productivity and processing time are reduced
Solution Approach 1:
The system enables self-service web form generation by automatically selecting appropriate templates and populating them with case data without requiring manual intervention. The automated form generator retrieves case data, determines the appropriate web form template based on case characteristics, and generates the final form automatically, eliminating manual processing while maintaining operational flexibility.
Solution Approach 2:
The system implements universality by creating a multi-functional automated form generation platform that handles various web form types through a single unified system. The platform stores multiple web form templates and automatically selects the appropriate one based on case data characteristics, allowing the same system to generate different forms for different cases without requiring separate manual processes for each form type.
2Reliability
If web forms are generated in a single language, then system simplicity is maintained, but response rates and data accuracy deteriorate due to language barriers
Solution Approach 1:
The system applies local quality by customizing web form language to match the specific case characteristics and recipient preferences. Instead of using a single language for all forms, the system determines the appropriate language based on case data and generates the form in that specific language, ensuring optimal communication and response rates for each individual case while maintaining overall system functionality.
3Adaptability or versatility
If multiple web form templates are stored and selected automatically, then productivity and language appropriateness are improved, but device complexity and data management requirements increase
Solution Approach 1:
The system implements preliminary action by pre-storing multiple web form templates in a database before they are needed. The templates are prepared and organized in advance, allowing the automated form generator to quickly retrieve and select the appropriate template based on case data without requiring complex real-time decisions or manual template creation during the form generation process.
Data Source
AI summary
A method for generating a web form. The method include receiving a source file and determining case data based on the source file. The method further includes generating a case dataset including the case data. The method further includes selecting a rule including a rule criteria and determining the case data of the case dataset fulfills the rule criteria. The method further includes selecting a web form template. The method further includes generating the web form including at least a portion of the case data of the case dataset. The method further includes generating a link associated with the web form. The method further includes outputting the link to the destination address of the rule. The method further includes receiving a request to access the web form, and outputting the web form based on the request. The method further includes receiving follow-up case data.