https://www.selleckchem.com/products/az-33.html We believe that this theoretical and methodological improvement in the model can improve comparisons of redundancy in different social-ecological systems. We also highlight some limitations of the URM (and our Uredit), and we believe that conscious reasons behind people's decisions should be incorporated into future studies on the subject. The ability to compose a concise summary statement about a patient is a good indicator for the clinical reasoning abilities of healthcare students. To assess such summary statements manually a rubric based on five categories - use of semantic qualifiers, narrowing, transformation, accuracy, and global rating has been published. Our aim was to explore whether computer-based methods can be applied to automatically assess summary statements composed by learners in virtual patient scenarios based on the available rubric in real-time to serve as a basis for immediate feedback to learners. We randomly selected 125 summary statements in German and English composed by learners in five different virtual patient scenarios. Then we manually rated these statements based on the rubric plus an additional category for the use of the virtual patients' name. We implemented a natural language processing approach in combination with our own algorithm to automatically assess 125 randomly selected summary statements and compaupposedly incorrect assessments, which will also help us to further improve the rating algorithms. Embedding patient accommodation need in the electronic health record (EHR) has been proposed as one means to improve health care delivery to patients with disabilities. Accommodation need is not a standard field in commercial EHR software. However, some medical practices ask about accommodation need and store it in the EHR. Little is known about how the information is used, or barriers to its use. This exploratory-descriptive study examines whether and how information about patients' di