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使用不同数据库和“回顾”间隔来定义新诊断高血压患者的合并症概况的影响:对卫生服务研究人员的启示

Influence of Using Different Databases and 'Look Back' Intervals to Define Comorbidity Profiles for Patients with Newly Diagnosed Hypertension: Implications for Health Services Researchers.

作者信息

Chen Guanmin, Lix Lisa, Tu Karen, Hemmelgarn Brenda R, Campbell Norm R C, McAlister Finlay A, Quan Hude

机构信息

Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada.

Institute of Public Health, University of Calgary, Calgary, Alberta, Canada.

出版信息

PLoS One. 2016 Sep 1;11(9):e0162074. doi: 10.1371/journal.pone.0162074. eCollection 2016.

DOI:10.1371/journal.pone.0162074
PMID:27583532
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5008755/
Abstract

OBJECTIVE

To determine the data sources and 'look back' intervals to define comorbidities.

DATA SOURCES

Hospital discharge abstracts database (DAD), physician claims, population registry and death registry from April 1, 1994 to March 31, 2010 in Alberta, Canada.

STUDY DESIGN

Newly-diagnosed hypertension cases from 1997 to 2008 fiscal years were identified and followed up to 12 years. We defined comorbidities using data sources and duration of retrospective observation (6 months, 1 year, 2 years, and 3 years). The C-statistics for logistic regression and concordance index (CI) for Cox model of mortality and cardiovascular disease hospitalization were used to evaluate discrimination performance for each approach of defining comorbidities.

PRINCIPAL FINDINGS

The comorbidities prevalence became higher with a longer duration. Using DAD alone underestimated the prevalence by about 75%, compared to using both DAD and physician claims. The C-statistic and CI were highest when both DAD and physician claims were used, and model performance improved when observation duration increased from 6 months to one year or longer.

CONCLUSION

The comorbidities prevalence is greatly impacted by the data source and duration of retrospective observation. A combination of DAD and physicians claims with at least one year observation duration improves predictions for cardiovascular disease and one-year mortality outcome model performance.

摘要

目的

确定用于定义合并症的数据来源和“回顾”间隔。

数据来源

加拿大艾伯塔省1994年4月1日至2010年3月31日的医院出院摘要数据库(DAD)、医生索赔数据、人口登记册和死亡登记册。

研究设计

确定1997财年至2008财年新诊断的高血压病例,并随访12年。我们使用数据来源和回顾性观察持续时间(6个月、1年、2年和3年)来定义合并症。使用逻辑回归的C统计量和Cox死亡率及心血管疾病住院模型的一致性指数(CI)来评估每种定义合并症方法的判别性能。

主要发现

随着持续时间延长,合并症患病率升高。与同时使用DAD和医生索赔数据相比,仅使用DAD会使患病率低估约75%。同时使用DAD和医生索赔数据时,C统计量和CI最高,且当观察持续时间从6个月增加到1年或更长时,模型性能有所改善。

结论

合并症患病率受数据来源和回顾性观察持续时间的极大影响。将DAD和医生索赔数据相结合,且观察持续时间至少为一年,可改善对心血管疾病和一年死亡率结局模型性能的预测。

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本文引用的文献

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Comparative ability of comorbidity classification methods for administrative data to predict outcomes in patients with chronic obstructive pulmonary disease.比较基于医疗行政资料的共病分类方法对预测慢性阻塞性肺病患者结局的能力。
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Performance of comorbidity measures for predicting outcomes in population-based osteoporosis cohorts.基于人群的骨质疏松队列中预测结局的合并症测量的性能。
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