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Data Validation01:03

Data Validation

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Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
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Nursing diagnoses represent a problem validated by major defining characteristics. There are four categories of nursing diagnoses: problem-focused, risk, health promotion or wellness, and syndrome. The anatomy of a nursing diagnosis includes three components: problem statement or diagnostic label, defining characteristics, and related factors.
Risk nursing diagnoses represent clinical judgments of an individual, family, or community more vulnerable to developing the health problem than others...
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The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
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Case Studies01:22

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There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it.
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Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
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使用行政数据验证跨性别成年人的案例定义.

Chantal L Rytz1,2, James A King1,3,4, Nathalie Saad5

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概括
此摘要是机器生成的。

这项研究开发并验证了案例定义,以在行政卫生数据中识别跨性别成年人. 这些定义,使用诊断代码和激素处方,准确地确定跨性别人口的健康研究.

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科学领域:

  • 医疗信息学 医疗信息学
  • 流行病学 流行病学
  • 跨性别者健康 跨性别者健康

背景情况:

  • 行政健康数据对于研究跨性别健康至关重要,因为自我报告数据无法获得.
  • 开发准确的方法来识别健康记录中的跨性别个人对于人口层面的研究至关重要.

研究的目的:

  • 开发和验证案例定义,用于在行政卫生数据中识别跨性别女性和男性.
  • 将这些定义的准确性与自我报告的性别认同进行比较.

主要方法:

  • 加拿大阿尔伯塔省的一项队列研究将多个行政健康数据来源联系起来.
  • 针对跨性别女性 (9) 和跨性别男性 (6),开发和测试了15个案例定义.
  • 计算了灵敏度,特异性,正预测值 (PPV) 和负预测值 (NPV).

主要成果:

  • 对于跨性别女性,将注册表识别和激素处方或诊断码结合在一起的定义实现了86.6%的灵敏度和62.5%的特异性.
  • 对于跨性别男性,将注册表识别和激素处方或诊断码结合在一起的定义实现了78.2%的灵敏度和89.2%的特异性.
  • 这项研究包括超过530万个人,有相当大的队列被确定为跨性别女性和男性.

结论:

  • 结合跨性别相关诊断代码和性别确认激素处方的案例定义对于在行政数据中识别跨性别人口是有效的.
  • 这些验证的定义可以促进对跨性别健康,疾病负担和医疗保健利用的研究.
  • 这种方法提高了对变性人群进行人口级健康研究的能力.