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Data Management and Data Quality in PERCH, a Large International Case-Control Study of Severe Childhood Pneumonia
by
Onwuchekwa, Uma
, Hammond, Emily
, Siazeele, Kazungu
, Park, Daniel E.
, Levine, Orin S.
, Wolff, Mark
, Prosperi, Christine
, Awori, Juliet O.
, Sapchookul, Patranuch
, Driscoll, Amanda J.
, Neyzari, Omid
, O'Brien, Katherine L.
, Watson, Nora L.
, Goswami, Doli
, Shamsul, Arifin
, Sylla, Mamadou
, Kamau, Alice
, Srisaengchai, Prasong
, Parker, David
, Moore, David P.
, Murdoch, David R.
, Kuwanda, Locadiah
, Johnson, Catherine
, Knoll, Maria Deloria
, DeLuca, Andrea N.
, Sanza, Megan
, Higdon, Melissa M.
, Hossain, Lokman
, Seidenberg, Phil
in
Africa
/ Asia
/ Case-Control Studies
/ Child
/ Clinical Laboratory Techniques
/ Data Accuracy
/ Data Collection
/ Database Management Systems
/ Humans
/ Internationality
/ Methodological Papers
/ Pneumonia - diagnosis
/ Pneumonia - etiology
/ Pneumonia, Bacterial - diagnosis
/ Pneumonia, Viral - diagnosis
/ Supplement
2017
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Data Management and Data Quality in PERCH, a Large International Case-Control Study of Severe Childhood Pneumonia
by
Onwuchekwa, Uma
, Hammond, Emily
, Siazeele, Kazungu
, Park, Daniel E.
, Levine, Orin S.
, Wolff, Mark
, Prosperi, Christine
, Awori, Juliet O.
, Sapchookul, Patranuch
, Driscoll, Amanda J.
, Neyzari, Omid
, O'Brien, Katherine L.
, Watson, Nora L.
, Goswami, Doli
, Shamsul, Arifin
, Sylla, Mamadou
, Kamau, Alice
, Srisaengchai, Prasong
, Parker, David
, Moore, David P.
, Murdoch, David R.
, Kuwanda, Locadiah
, Johnson, Catherine
, Knoll, Maria Deloria
, DeLuca, Andrea N.
, Sanza, Megan
, Higdon, Melissa M.
, Hossain, Lokman
, Seidenberg, Phil
in
Africa
/ Asia
/ Case-Control Studies
/ Child
/ Clinical Laboratory Techniques
/ Data Accuracy
/ Data Collection
/ Database Management Systems
/ Humans
/ Internationality
/ Methodological Papers
/ Pneumonia - diagnosis
/ Pneumonia - etiology
/ Pneumonia, Bacterial - diagnosis
/ Pneumonia, Viral - diagnosis
/ Supplement
2017
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Do you wish to request the book?
Data Management and Data Quality in PERCH, a Large International Case-Control Study of Severe Childhood Pneumonia
by
Onwuchekwa, Uma
, Hammond, Emily
, Siazeele, Kazungu
, Park, Daniel E.
, Levine, Orin S.
, Wolff, Mark
, Prosperi, Christine
, Awori, Juliet O.
, Sapchookul, Patranuch
, Driscoll, Amanda J.
, Neyzari, Omid
, O'Brien, Katherine L.
, Watson, Nora L.
, Goswami, Doli
, Shamsul, Arifin
, Sylla, Mamadou
, Kamau, Alice
, Srisaengchai, Prasong
, Parker, David
, Moore, David P.
, Murdoch, David R.
, Kuwanda, Locadiah
, Johnson, Catherine
, Knoll, Maria Deloria
, DeLuca, Andrea N.
, Sanza, Megan
, Higdon, Melissa M.
, Hossain, Lokman
, Seidenberg, Phil
in
Africa
/ Asia
/ Case-Control Studies
/ Child
/ Clinical Laboratory Techniques
/ Data Accuracy
/ Data Collection
/ Database Management Systems
/ Humans
/ Internationality
/ Methodological Papers
/ Pneumonia - diagnosis
/ Pneumonia - etiology
/ Pneumonia, Bacterial - diagnosis
/ Pneumonia, Viral - diagnosis
/ Supplement
2017
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Data Management and Data Quality in PERCH, a Large International Case-Control Study of Severe Childhood Pneumonia
Journal Article
Data Management and Data Quality in PERCH, a Large International Case-Control Study of Severe Childhood Pneumonia
2017
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Overview
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.
Publisher
Oxford University Press
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