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在一项关于儿童重症肺炎的大型国际病例对照研究(PERCH)中的数据管理与数据质量

Data Management and Data Quality in PERCH, a Large International Case-Control Study of Severe Childhood Pneumonia.

作者信息

Watson Nora L, Prosperi Christine, Driscoll Amanda J, Higdon Melissa M, Park Daniel E, Sanza Megan, DeLuca Andrea N, Awori Juliet O, Goswami Doli, Hammond Emily, Hossain Lokman, Johnson Catherine, Kamau Alice, Kuwanda Locadiah, Moore David P, Neyzari Omid, Onwuchekwa Uma, Parker David, Sapchookul Patranuch, Seidenberg Phil, Shamsul Arifin, Siazeele Kazungu, Srisaengchai Prasong, Sylla Mamadou, Levine Orin S, Murdoch David R, O'Brien Katherine L, Wolff Mark, Deloria Knoll Maria

机构信息

Emmes Corporation, Rockville, and.

Department of International Health, International Vaccine Access Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.

出版信息

Clin Infect Dis. 2017 Jun 15;64(suppl_3):S238-S244. doi: 10.1093/cid/cix080.

Abstract

The Pneumonia Etiology Research for Child Health (PERCH) study is the largest multicountry etiology study of pediatric pneumonia undertaken in the past 3 decades. The study enrolled 4232 hospitalized cases and 5325 controls over 2 years across 9 research sites in 7 countries in Africa and Asia. The volume and complexity of data collection in PERCH presented considerable logistical and technical challenges. The project chose an internet-based data entry system to allow real-time access to the data, enabling the project to monitor and clean incoming data and perform preliminary analyses throughout the study. To ensure high-quality data, the project developed comprehensive quality indicator, data query, and monitoring reports. Among the approximately 9000 cases and controls, analyzable laboratory results were available for ≥96% of core specimens collected. Selected approaches to data management in PERCH may be extended to the planning and organization of international studies of similar scope and complexity.

摘要

儿童健康肺炎病因研究(PERCH)是过去30年来开展的最大规模的多国儿童肺炎病因研究。该研究在非洲和亚洲7个国家的9个研究地点,历时2年,招募了4232例住院病例和5325名对照。PERCH数据收集的数量和复杂性带来了相当大的后勤和技术挑战。该项目选择了基于互联网的数据录入系统,以便实时访问数据,使项目能够在整个研究过程中监测和清理输入的数据,并进行初步分析。为确保数据质量,该项目制定了全面的质量指标、数据查询和监测报告。在大约9000例病例和对照中,≥96%的核心标本有可分析的实验室结果。PERCH中选定的数据管理方法可扩展到类似规模和复杂性的国际研究的规划和组织中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/35c9/5447839/c67da71767f9/cix08001.jpg

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