
Culbertson developed the foundational Virtual Check-In System for the umgc/2025_fall repository, focusing on backend architecture and robust data persistence. He designed and implemented a comprehensive data model using Java, Hibernate, and Spring Data JPA, supporting entities such as Question, CheckIn, Answer, and QuestionType. His work included creating repositories and cross-file JPA mappings, enabling structured capture of patient-reported data and caregiver-selected check-in flows. The system’s schema supports future analytics and flexible onboarding of new workflows, reducing manual data entry and standardizing information. Throughout the project, Culbertson maintained clear traceability and delivered a complete, end-to-end feature without reported bugs.

October 2025: Delivered the foundational Virtual Check-In System and the associated data persistence layer in the umgc/2025_fall project. Implemented a complete data model for virtual patient check-ins (Question, CheckIn, Answer, QuestionType) with repositories, enabling reliable capture of structured patient-reported data. Established caregiver-selected check-in support via the check_in_questions table and cross-file JPA mappings. This work lays the groundwork for scalable data analytics, improved care coordination, and faster onboarding of virtual care workflows. Key business impact includes reduced manual data entry, standardized data for analytics, and a flexible schema for future questions and check-in flows. Technologies demonstrated: Java, JPA/Hibernate, repository pattern, and database design. No major bugs reported; all changes focused on feature development and data model robustness.
October 2025: Delivered the foundational Virtual Check-In System and the associated data persistence layer in the umgc/2025_fall project. Implemented a complete data model for virtual patient check-ins (Question, CheckIn, Answer, QuestionType) with repositories, enabling reliable capture of structured patient-reported data. Established caregiver-selected check-in support via the check_in_questions table and cross-file JPA mappings. This work lays the groundwork for scalable data analytics, improved care coordination, and faster onboarding of virtual care workflows. Key business impact includes reduced manual data entry, standardized data for analytics, and a flexible schema for future questions and check-in flows. Technologies demonstrated: Java, JPA/Hibernate, repository pattern, and database design. No major bugs reported; all changes focused on feature development and data model robustness.
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