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

نویسندگان

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

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.

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عنوان ژورنال:

دوره 64  شماره 

صفحات  -

تاریخ انتشار 2017