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Finding temporal order in discharge summaries
Philip Bramsen1, Pawan Deshpande, Yoong Keok Lee
1Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.
Abstract:
A method for automatic analysis of time-oriented clinical narratives would be of significant practical import for medical decision making, data modeling and biomedical research. This paper proposes a robust corpus-based approach for temporal analysis of medical discharge summaries. We characterize temporal organization of clinical narratives in terms of temporal segments and their ordering. We consider a temporal segment to be a fragment of text that does not exhibit abrupt changes in temporal focus. Our method derives temporal order based on a range of linguistic and contextual features that are integrated in a supervised machine-learning framework. Our learning method achieves 83% F-measure in tempo-ral segmentation, and 78.3% accuracy in inferring pairwise temporal relations.
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Here's a detailed look at the key components and guidelines for preparing a discharge summary:
Flow Sheet
Here's a closer look at the examples of flowsheets commonly used by nurses:
Graphic Sheet Documentation:
Guidelines for Nursing Documentation II
Timely documentation is crucial to ensure continuity of care for patients. Any delays in recording or reporting medical information can result in medical errors and even adverse patient outcomes. From medication administration to diagnostic test results, every detail must be accurately and promptly documented to provide the best possible care for patients.
Methods of Documentation I: Source-Oriented Records
In an SOR, each discipline involved in patient care maintains a separate medical record section. This record-keeping method enables easy tracking of patient progress and ensures healthcare staff have access to up-to-date information.
Key Attributes include the following:
Methods of Documentation IV: Focus Charting
It typically involves three columns for recording information:
Planning Nursing Care I