Details

Autor(en) / Beteiligte

• 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
• Knoll, Maria Deloria

Titel

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

Ist Teil von

• Clinical infectious diseases, 2017-06, Vol.64 (suppl_3), p.S238-S244

Ort / Verlag

United States: Oxford University Press

Erscheinungsjahr

2017

Quelle

Oxford Journals 2020 Medicine

Beschreibungen/Notizen

• 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.