Department of Neurology, University of Pennsylvania Perelman School of Medicine, Blockley Hall, 723, 423 Guardian Drive, Philadelphia, PA, 19104, USA.
Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Blockley Hall, 723, 423 Guardian Drive, Philadelphia, PA, 19104, USA.
Curr Neurol Neurosci Rep. 2015 Nov;15(11):75. doi: 10.1007/s11910-015-0595-4.
The fields of neurodegenerative disease and dementia research have grown considerably in the last several decades. Due to tremendous efforts of basic and clinical research scientists, we know a great deal about dementia risk factors and have multiple treatment options. Clinician recognition of cognitive impairment has increased considerably, national policies which support screening for and documenting cognitive dysfunction now exist, and public awareness of neurodegenerative disease has never been greater. These conditions promote (and demand) the growth of translational epidemiology and health services research, which focuses on examining outcomes in groups of individuals as a function of health care experiences. This review discusses the use of administrative data to answer health care outcomes and disparities questions in dementia. Of particular interest are publically available datasets that contain varying amounts of diagnostic, clinical, pharmacy, and patient information. Methodological challenges that are frequently encountered and must be understood to minimize biased inference are also discussed.
在过去的几十年中，神经退行性疾病和痴呆症研究领域有了长足的发展。由于基础和临床研究科学家的巨大努力，我们对痴呆症的风险因素有了很多了解，并且有多种治疗选择。临床医生对认知障碍的认识有了很大提高，现在有支持对认知功能障碍进行筛查和记录的国家政策，公众对神经退行性疾病的认识也从未如此之高。这些情况促进（并要求）转化流行病学和卫生服务研究的发展，该研究侧重于根据医疗保健经验检查个体群体的结果。本文回顾了使用行政数据回答痴呆症医疗保健结果和差异问题的方法。特别感兴趣的是包含不同数量的诊断、临床、药物和患者信息的公开可用数据集。还讨论了经常遇到且必须理解以最小化有偏推断的方法学挑战。
