50岁以上成人糖尿病患者的州级代谢合并症患病率和控制:来自5个州电子健康记录和调查数据的估计

IF 3.2 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Population Health Metrics Pub Date : 2022-12-02 DOI:10.1186/s12963-022-00298-z
Russell Mardon, Joanne Campione, Jennifer Nooney, Lori Merrill, Maurice Johnson, David Marker, Frank Jenkins, Sharon Saydah, Deborah Rolka, Xuanping Zhang, Sundar Shrestha, Edward Gregg
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引用次数: 0

摘要

背景:虽然糖尿病的治疗和控制可以预防并发症和降低发病率,但在国家一级监测糖尿病合并症和控制的数据来源很少。调查和电子健康记录(EHRs)在监测糖尿病和主要代谢合并症方面具有不同的优势和劣势。自我报告调查的数据存在认知和回忆偏差,通常不能用于监测未确诊病例。电子病历数据变得越来越容易获得,但由于患者不是随机选择的,并不是每个人都有相关的生物标志物测量值,而且这些数据往往在地理上聚集在一起,因此对人口估计提出了特别的挑战。方法:我们分析了来自全国健康和营养调查、健康和退休研究以及来自DARTNet研究所的电子病历数据,以创建各州糖尿病患病率和控制的调整估计,以及50岁及以上糖尿病人群中高血压和高胆固醇的患病率和控制:阿拉巴马州、加利福尼亚州、佛罗里达州、路易斯安那州和马萨诸塞州。结果:两项调查的估计结果大体一致。电子病历数据与许多措施的调查结果一致,但对未确诊糖尿病患病率的估计始终较低,并且在大多数州发现的合并症较少。结论:尽管存在这些局限性,电子病历可能是糖尿病监测和控制评估的一个有希望的来源,因为数据集很大,并且是在常规医疗保健提供过程中创建的。试验注册:不适用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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State-level metabolic comorbidity prevalence and control among adults age 50-plus with diabetes: estimates from electronic health records and survey data in five states.

Background: Although treatment and control of diabetes can prevent complications and reduce morbidity, few data sources exist at the state level for surveillance of diabetes comorbidities and control. Surveys and electronic health records (EHRs) offer different strengths and weaknesses for surveillance of diabetes and major metabolic comorbidities. Data from self-report surveys suffer from cognitive and recall biases, and generally cannot be used for surveillance of undiagnosed cases. EHR data are becoming more readily available, but pose particular challenges for population estimation since patients are not randomly selected, not everyone has the relevant biomarker measurements, and those included tend to cluster geographically.

Methods: We analyzed data from the National Health and Nutritional Examination Survey, the Health and Retirement Study, and EHR data from the DARTNet Institute to create state-level adjusted estimates of the prevalence and control of diabetes, and the prevalence and control of hypertension and high cholesterol in the diabetes population, age 50 and over for five states: Alabama, California, Florida, Louisiana, and Massachusetts.

Results: The estimates from the two surveys generally aligned well. The EHR data were consistent with the surveys for many measures, but yielded consistently lower estimates of undiagnosed diabetes prevalence, and identified somewhat fewer comorbidities in most states.

Conclusions: Despite these limitations, EHRs may be a promising source for diabetes surveillance and assessment of control as the datasets are large and created during the routine delivery of health care.

Trial registration: Not applicable.

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来源期刊
Population Health Metrics
Population Health Metrics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
6.50
自引率
0.00%
发文量
21
审稿时长
29 weeks
期刊介绍: Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.
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