Data management and data quality in PERCH, a large international case-control study of severe childhood pneumonia

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

doi:10.1093/cid/cix080

Data management and data quality in PERCH, a large international case-control study of severe childhood pneumonia

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 SeidenbergArifin Shamsul, Kazungu Siazeele, Prasong Srisaengchai, Mamadou Sylla, Orin S. Levine, David R. Murdoch, Katherine L. O'Brien, Mark Wolff, Maria Deloria Knoll

Bloomberg School of Public Health

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

The Pneumonia Etiology Research for Child Health (PERCH) study is the largest multicountry etiology study of pediatric pneumonia undertaken in the past decades. The study enrolled 423hospitalized cases and 532controls over years across research sites in 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 900cases 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.

Original language	English (US)
Pages (from-to)	S238-S244
Journal	Clinical Infectious Diseases
Volume	64
DOIs	https://doi.org/10.1093/cid/cix080
State	Published - 2017

Keywords

Data management
Data quality
Electronic data capture
PERCH

ASJC Scopus subject areas

Microbiology (medical)
Infectious Diseases

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10.1093/cid/cix080

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Watson, N. L., Prosperi, C., Driscoll, A. J., Higdon, M. M., Park, D. E., Sanza, M., DeLuca, A. N., Awori, J. O., Goswami, D., Hammond, E., Hossain, L., Johnson, C., Kamau, A., Kuwanda, L., Moore, D. P., Neyzari, O., Onwuchekwa, U., Parker, D., Sapchookul, P., ... Knoll, M. D. (2017). Data management and data quality in PERCH, a large international case-control study of severe childhood pneumonia. Clinical Infectious Diseases, 64, S238-S244. https://doi.org/10.1093/cid/cix080

Watson, NL, Prosperi, C, Driscoll, AJ, Higdon, MM, Park, DE, Sanza, M, DeLuca, AN, Awori, JO, Goswami, D, Hammond, E, Hossain, L, Johnson, C, Kamau, A, Kuwanda, L, Moore, DP, Neyzari, O, Onwuchekwa, U, Parker, D, Sapchookul, P, Seidenberg, P, Shamsul, A, Siazeele, K, Srisaengchai, P, Sylla, M, Levine, OS, Murdoch, DR, O'Brien, KL, Wolff, M & Knoll, MD 2017, 'Data management and data quality in PERCH, a large international case-control study of severe childhood pneumonia', Clinical Infectious Diseases, vol. 64, pp. S238-S244. https://doi.org/10.1093/cid/cix080

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title = "Data management and data quality in PERCH, a large international case-control study of severe childhood pneumonia",

abstract = "The Pneumonia Etiology Research for Child Health (PERCH) study is the largest multicountry etiology study of pediatric pneumonia undertaken in the past decades. The study enrolled 423hospitalized cases and 532controls over years across research sites in 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 900cases 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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doi = "10.1093/cid/cix080",

language = "English (US)",

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pages = "S238--S244",

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AU - Watson, Nora L.

AU - Prosperi, Christine

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AU - Higdon, Melissa M.

AU - Park, Daniel E.

AU - Sanza, Megan

AU - DeLuca, Andrea N.

AU - Awori, Juliet O.

AU - Goswami, Doli

AU - Hammond, Emily

AU - Hossain, Lokman

AU - Johnson, Catherine

AU - Kamau, Alice

AU - Kuwanda, Locadiah

AU - Moore, David P.

AU - Neyzari, Omid

AU - Onwuchekwa, Uma

AU - Parker, David

AU - Sapchookul, Patranuch

AU - Seidenberg, Phil

AU - Shamsul, Arifin

AU - Siazeele, Kazungu

AU - Srisaengchai, Prasong

AU - Sylla, Mamadou

AU - Levine, Orin S.

AU - Murdoch, David R.

AU - O'Brien, Katherine L.

AU - Wolff, Mark

AU - Knoll, Maria Deloria

PY - 2017

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Data management and data quality in PERCH, a large international case-control study of severe childhood pneumonia

Abstract

Keywords

ASJC Scopus subject areas

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