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What do students learn in this course?
What do students learn in this course?
Students in Problem-Solving with People, Information and Technology worked in teams to identify, scope and investigate an information-related project and propose recommendations based on their work with a specific focus area and client. Each course section worked with a different client project. Students investigated an array of challenges relevant to the future of work, including rural broadband access, workforce development, artificial intelligence, alternative credentialing, and workplace wellness.
Course Overview:
Many problems facing society today involve information, from the small and mundane to the large and socially complex. Students learn and apply interdisciplinary problem-solving and team-based techniques to identify problems involving information, investigate them, and design potential solutions. This course develops foundational skills essential for future information professionals.
Fall 2024 faculty: Melissa Chalmers (head instructor), Maggie Brodbeck, Brenna Davidson, Adam Freed, Katie LaPlant, Mustafa Naseem, Chelsea Peterson-Salahuddin, Alissa Talley-Pixley, Angie Zill
Project Outcomes
Empowering Local Healthcare Providers: Customized Automation Solutions for Enhanced Efficiency and Patient Care
Student(s): Graciela Lagraba, Zoe Corser, Alina Faisal, CJ Schwartz, Stanley Chen
Project Overview:
We addressed inefficiencies in local hospital workflows by designing AI-driven automation solutions to reduce administrative burden and improve patient-practitioner interactions. We focused our recommendations on insurance processing, data interoperability, and wearable data integration.
This project challenged our team to think critically about how AI can be implemented in various healthcare settings. Throughout the process we explored how the evolution of conventional workflows can reduce burden in ways that support patient centered care for small hospitals -- who often have limited resources to invest in new infrastructure. By interviewing frontline practitioners, IT staff, and product leaders, we learned firsthand how much time is lost to manual data entry, insurance processing, and outdated Electronic Medical Record systems. We were able to translate real clinical needs into scalable recommendations.
Our team focused on identifying practical automation opportunities that could improve efficiency without requiring high cost or complex implementation. Making healthcare workflows more efficient and accessible has the potential to improve care quality, reduce administrative burden, and allow practitioners to focus more fully on delivering high-quality care to their patients.
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