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

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

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

Author(s) -

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 E. Hammond,

Lokman Hossain,

Catherine O. 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

Publication year - 2017

Publication title -

clinical infectious diseases

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.44

H-Index - 336

eISSN - 1537-6591

pISSN - 1058-4838

DOI - 10.1093/cid/cix080

Subject(s) - medicine , data quality , etiology , scope (computer science) , quality (philosophy) , data collection , data management , pneumonia , control (management) , quality management , environmental health , intensive care medicine , operations management , database , pathology , management system , computer science , metric (unit) , philosophy , statistics , mathematics , epistemology , artificial intelligence , economics , programming language

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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