Large Language Models for Efficient Medical Information Extraction.

Extracting valuable insights from unstructured clinical narrative reports is a challenging yet crucial task in the healthcare domain as it allows healthcare workers to treat patients more efficiently and improves the overall standard of care. We employ ChatGPT, a Large language model (LLM), and compare its performance to manual reviewers. The review focuses on four key conditions: family history of heart disease, depression, heavy smoking, and cancer. The evaluation of a diverse sample of History and Physical (H&P) Notes, demonstrates ChatGPT's remarkable capabilities. Notably, it exhibits exemplary results in sensitivity for depression and heavy smokers and specificity for cancer. We identify areas for improvement as well, particularly in capturing nuanced semantic information related to family history of heart disease and cancer. With further investigation, ChatGPT holds substantial potential for advancements in medical information extraction.

Development and Implementation of Physical Education State-Level Accountability for Student Learning and Performance.

Background: The purpose of this study was to explore the development and implementation of state level accountability policy and systems. Methods: The study was conducted using an explanatory multiple-case study design using the SWOT analysis (strengths, weaknesses, opportunities to improve, and threats). Ten leaders from three states participated in the study (State A n = 3; State B n = 4; State C n = 3 [female n = 1, 1, 2, respectively]). Semi-structured interviews and document analysis were used to collect data. The data was analyzed using the structural narrative analysis method. Results: All ten state leaders discussed that the high obesity rate within the state was one of the motives of adopting an accountability system. The commonly identified strengths of the system were having legislation and using existing resources to help facilitate the process. Some weaknesses included the lack of accessibility to individual data at the state level and the absence of a reflexive cycle for future improvement. For opportunities to improve, all state leaders mentioned having an assessment system enhanced the status of physical education in schools. Consistently discussed threats were turnover of associated personnel and teacher pushbacks. Conclusion: This study revealed that there are several factors to consider making an accountability policy and system meaningful and valuable. Physical educators are all policy actors. Everyone has a responsibility to act as stewards of the field to be critically reflective in what we do, and to understand the why behind our actions.