概括
过度诊断,即对一种没有净益处的疾病进行标记,是"过多的药物"的关键部分. 像选择明智这样的倡议旨在减少过度诊断和提高医疗保健价值.
科学领域:
- 卫生经济学 卫生经济学
- 医学伦理 医学伦理
- 公共卫生 公共卫生
背景情况:
- 显著的医疗保健支出被认为是浪费.
- 过度诊断,包括过度检测和过度定义,是"太多药"的主要组成部分.
- 由经济因素驱动的疾病传播是过度定义的一个例子.
研究的目的:
- 在更广泛的问题"太多的药物"中定义和语境化过度诊断.
- 为了突出与诊断和治疗益处的重点相比,过度诊断的伤害不足.
- 探索像"明智选择"这样的倡议在缓解过度诊断方面的潜力.
主要方法:
- 对"太多的药物",过度诊断,过度检测,过度定义,疾病传播,过度测试和过度治疗的概念分析.
- 审查医疗研究中关于益处与危害的重点.
- 审查国际和国家活动的影响和潜力,如"明智选择".
主要成果:
- 过度诊断,与过度检测和过度治疗不同,是医疗保健浪费的一个关键方面.
- 医学研究不成比例地强调好处,导致对诊断和治疗优势的高估.
- "明智选择"网络在改变诊断范式方面取得了成功,并为解决"过多的药物"提供了一个模型.
结论:
- 过度诊断是医疗保健系统中浪费的重要来源.
- 研究重点转向过度诊断和其他危害是必要的,以平衡对医疗益处的看法.
- 宣传明智使用医疗资源的运动对于打击"过多的药物"和过度诊断至关重要.
相关概念视频
Documentation of Nursing Diagnosis
1.3K
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...
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...
1.3K
Formulating and Validating Nursing Diagnosis II
2.8K
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...
Risk nursing diagnoses represent clinical judgments of an individual, family, or community more vulnerable to developing the health problem than others...
2.8K
Nursing Diagnosis
2.7K
Following assessment, a nursing diagnosis is the next step in the nursing process. It begins after the nurse has collected and recorded the patient data. The purpose of diagnosing is to identify how the client responds to actual or potential health processes, identify factors that bestow or that cause health problems, the etiologies, and identify resources or strengths the individual, group, or community can draw on to prevent or resolve problems.
The nursing diagnosis focuses on evidence-based...
The nursing diagnosis focuses on evidence-based...
2.7K
Diagnostic and Statistical Manual of Mental Disorders (DSM)
59
The Diagnostic and Statistical Manual of Mental Disorders (DSM) serves as the primary classification system for mental health disorders, providing standardized diagnostic criteria for clinicians and researchers. First published by the American Psychiatric Association (APA) in 1952, the DSM has undergone several revisions to reflect evolving psychiatric understanding. The fifth edition, DSM-5, released in 2013, introduced key updates that expanded diagnostic categories and modified diagnostic...
59
Formulating and Validating Nursing Diagnosis I
2.7K
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...
There are thirteen domains...
2.7K
Receiver Operating Characteristic Plot
240
A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
240


