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Formulating and Validating Nursing Diagnosis I01:26

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A nursing diagnosis is written when the nurse recognizes a cluster of essential patient data indicating health problems treated with independent nursing interventions. The standardized terminologies of a nursing diagnosis help nurses identify and treat patients' problems. Every electronic health record that uses nursing diagnosis must employ standard diagnostic terminology. Developing an efficient, individualized care plan begins with accurate nursing diagnoses.
There are thirteen domains...
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Documentation of Nursing Diagnosis01:10

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The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...
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Local anesthetics (LAs) block the sodium channels of nerve trunks, sensory nerve endings, and neuromuscular junctions. Although LAs can block all kinds of nerves, the sensitivity of nerve fibers differs according to nerve types and structures. LAs are known to block myelinated fibers faster than unmyelinated ones. Also, they block pain or sensory neurons at low concentrations without affecting the motor neurons involved in muscle contractions. This helps relieve labor pain without affecting the...
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An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP
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自然语言处理与诊断对比 基于代码的方法用于后神经疼痛识别:算法开发和验证.

Chengyi Zheng1, Bradley Ackerson2, Sijia Qiu1

  • 1Department of Research & Evaluation, Kaiser Permanente Southern California, 100 S Los Robles Ave, 2nd Floor, Pasadena, CA, 91101, United States, 1 626-986-8665, 1 626-564-7872.

JMIR medical informatics
|September 10, 2024
PubMed
概括
此摘要是机器生成的。

一个新的自然语言处理 (NLP) 算法可以从电子健康记录中准确识别后神经疼痛 (PHN). 这种自动化方法为PHN研究提供了一种更有效的替代手动图表查看.

关键词:
欧洲人权理事会 欧洲人权理事会欧洲人机数据 欧洲人机数据算法算法是一种算法.人工智能的人工智能是人工智能.发展发展发展发展发展.诊断 诊断 诊断 诊断 诊断 诊断电子健康记录 电子健康记录疹子 疹子 疹子自然语言处理自然语言处理.神经疼痛是一种神经疼痛.术后性神经疼痛 术后性神经痛现实世界的数据数据.复合性疹疫苗复合性疹疫苗灵敏度 灵敏度 灵敏度 灵敏度 灵敏度特殊性的特异性验证验证的时间验证数据的验证数据.

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科学领域:

  • 医疗信息学 医疗信息学
  • 计算语言学 计算语言学
  • 流行病学 流行病学

背景情况:

  • 后神经痛 (PHN) 是疹 (HZ) 的一个痛苦的并发症.
  • 目前使用诊断码和处方数据在电子健康记录 (EHR) 中识别PHN的方法具有可疑的准确性.
  • 手动查看图表是准确的,但成本高且耗时.

研究的目的:

  • 开发和验证一种自然语言处理 (NLP) 算法,用于从非结构化EHR数据中自动识别PHN.
  • 将NLP算法的性能与传统的基于代码的方法进行比较.

主要方法:

  • 一项回顾性研究利用了来自南加州凯泽永久医院的电子健康记录数据.
  • 开发和验证数据集是随机抽取的,来自50岁以上的患者,有HZ和抗病毒处方.
  • 性能指标包括灵敏度,特异性,PPV,NPV,F-score和MCC被评估与手动图表审查作为参考标准.

主要成果:

  • 该NLP算法表现出高精度,达到90.9%的灵敏度,98.5%的特异性,82%的PPV和99.3%的NPV.
  • 在NLP算法中,复合分数为0.89 (F-score) 和0.85 (MCC).
  • 基于代码的方法显示性能明显较低,F分数和MCC分别在0.45-0.59和0.32-0.61之间.

结论:

  • 一种基于NLP的自动化方法可以准确地从EHR中识别PHN病例.
  • 这种NLP方法为基于人群的PHN研究提供了可行的和高效的工具.