This project aims to develop an automated message prioritization and response system integrated with the OSF Community Connect (OCC) platform, utilizing a customized ChatGPT API. OSF receives a high volume of patient messages that are time-sensitive and varied, making manual handling by health care workers difficult. The proposed system will automate multi-class message classification and responses, alleviating the burden on health- care workers and allowing them to focus more on patient care. Early research showed that a zero-shot ChatGPT model didn't perform well for multi-class classification tasks. Therefore, the project team plans to create their own labeled data and fine-tune the GPT-4 model for better performance. Once optimized, the customized model’s API will be integrated into the OCC platform, benefiting both patients and health care providers. The project will focus on four main objectives: automating message prioritization, categorizing messages for automated or human responses, generating tentative responses for human review, and possibly developing a chatbot-like interface for patient communication to gather additional information.
This project aims to integrate digital neurological exam tools, including the digital neurological exam (DNE), into physical therapy practices to improve clinical care. The first goal is to correlate the DNE with physical therapists' assessments of patients, especially in areas like gait, balance and fall risk. The second objective is to evaluate the feasibility and acceptance of these digital tools in physical therapy settings. By digitizing and automating assessments, therapists can deliver more efficient, objective care, addressing the growing patient load due to an aging population and a shortage of physical therapists. The project will focus on four main objectives:
With the collaboration of Bradley University’s Physical Therapy Clinic, this project will help enhance physical therapy practices and provide valuable insights into the use of digital health technologies in rehabilitation care.
This proposal aims to enhance surgical preparation and reduce patient risk by using 3D virtual reality (VR) models and 3D printed anatomical models for complex surgeries. Traditionally, surgeons rely on 2D images like CTs and MRIs, leading to variability in how they mentally visualize complex patient anatomy. By creating a 3D VR model, the process of understanding and planning surgeries becomes more accurate and uniform. OSF HealthCare has already had success in congenital heart surgeries and oncology using this approach, resulting in better surgical plans and increased surgeon confidence. The proposal seeks to expand this technology to other departments and institutions, with Bradley University students leading the feasibility and marketing research. By developing a sustainable business model, the goal is to extend this life-saving technology nationwide, improving patient care with more precise, efficient and safer surgeries. This approach aligns with the mission of precision medicine and expands access to quality care.