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Primary care promotes wellness and prevents disease. This care includes health promotion, education, protection (such as immunizations), early disease screening, and environmental considerations. Settings providing this type of healthcare include physician offices, public health clinics, school nursing, and community health nursing.
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Health promotion allows a person to control the determinants of health, resulting in an improved health status. It enhances the quality of life and reduces premature deaths. Health promotion and illness prevention programs help people make beneficial choices to reduce the risk of disease and disabilities. There are three health promotion and illness prevention levels: primary, secondary, and tertiary prevention.
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Preventive healthcare services keep people healthy via frequent check-ups, screening, and counseling. They primarily aid in disease prevention rather than treating an acute or chronic illness. Preventive treatment also keeps individuals productive and energetic, allowing them to work well into their retirement years. Examples of preventive care services include:
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Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
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公共卫生 公共卫生

Jeffrey Wing1, Jenna Rajczyk1, Julie Strominger1

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概括
此摘要是机器生成的。

行政索赔低估了阿尔茨海默氏症和相关痴呆症 (ADRD) 的患病率,特别是在阿帕拉契山县. 这些地区诊断敏感度较低可能会显著扩大真正的流行率差距.

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科学领域:

  • 老年学和流行病学.
  • 医疗保健服务研究 医疗服务研究
  • 生物统计学 生物统计学

背景情况:

  • 行政索赔数据虽然具有广泛的代表性,但受到阿尔茨海默病和相关痴呆症 (ADRD) 等疾病的不完善病例检测算法的限制.
  • 众所周知,医疗保险和医疗补助服务中心 (CMS) 的ADRD算法低估了与人口估计相比的患病率.
  • 差异错误分类,其中低估因人口或地理因素 (例如,阿巴拉契亚山区指定) 而有所不同,可能会导致流行率差异偏差.

研究的目的:

  • 为了调查ADRD患病率在阿巴拉契亚县被系统地低估的假设,由于诊断护理获取的潜在差异.
  • 量化潜在的ADRD错误分类对阿巴拉契亚和非阿巴拉契亚县之间估计的患病率差异的影响.

主要方法:

  • 利用CMS地理变异公共使用文件,通过阿巴拉契亚县的指定来估计ADRD的患病率.
  • 使用简单偏差分析 (SBA) 和概率偏差分析 (PBA) 来评估错误分类的影响.
  • 在各种非差异性和差异性错误分类场景下,纳入了ADRD算法灵敏度和特异性的文献估计.

主要成果:

  • 非差异性偏差场景始终将结果偏向于零.
  • 大多数差异性错误分类场景在阿巴拉契亚县指定观察到的ADRD诊断中没有显著差异.
  • 然而,如果ADRD诊断灵敏度在阿巴拉契亚县下降了10-20%,那么真正的患病率差异在1.3%-2.8%之间,比例在1.14-1.35.

结论:

  • 使用行政索赔数据来估计ADRD患病率本质上是不完美的.
  • 在像阿巴拉契亚县这样资源不足的地区,诊断灵敏度较低,可能会导致真正的流行差异被大大低估.