Clinical versus statistical significance: interpreting P values and confidence intervals related to measures of association to guide decision making.
Clinical versus statistical significance: interpreting P values and confidence intervals related to measures of association to guide decision making.
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DOI：
10.1177/0897190009358774
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发表时间：
2010-08-01
影响因子：
1.3
通讯作者：
Kyle, Jeffrey A
中科院分区：
文献类型：
--
作者：
Ferrill, Mary J;Brown, Dana A;Kyle, Jeffrey A
药剂师需要应用研究结果来降低风险并改善患者护理。结果的解释基于各种评估工具，如P值和置信区间（CI）。P值决定数据的统计学显著性，而CI则表明临床应用的程度。许多卫生保健提供者可能没有仔细检查和解释统计结果所需的技能，然后需要假设研究人员正确解释和呈现统计结果。不愿意检查统计数据往往反映了一种误解，即P值和CI等概念难以理解，而实际上，一旦理解了基本定义和应用，就可以解释这两个概念。相关性的测量，如需要治疗的数量，可以作为量化最终影响患者护理的重要参数的有效工具。对如何解释和应用P值和CI的基本理解增强了有效评估文献结果有效性的能力。一位消息灵通的读者，配备了批判性分析的工具，最有能力评估研究，从而辨别哪些信息适用于特定的患者护理决策。
Pharmacists need to apply outcomes from studies to reduce risk and improve patient care. Interpretation of outcomes is based on a variety of assessment tools, such as P values and confidence intervals (CIs). P values determine statistical significance of data, while CIs suggest the degree of clinical application. Many health care providers might not have the skill set required to carefully examine and interpret statistical results and then are required to assume that the researchers of the study correctly interpreted and presented the statistical results. The reluctance to examine statistical data often reflects a misconception that concepts such as P values and CIs are difficult to understand, while in reality, both can be interpreted once basic definitions and applications are understood. Measures of association such as number needed to treat can serve as effective tools for quantifying important parameters that ultimately affect patient care. A basic understanding of how to interpret and apply P values and CIs enhances one's ability to effectively assess the validity of results from the literature. An informed reader, armed with tools for critical analysis, is in the best position to evaluate studies and thereby discern which information is applicable to a specific patient care decision.