Evaluation of the quality of clinical data collection for a pan-Canadian cohort of children affected by inherited metabolic diseases: lessons learned from the Canadian Inherited Metabolic Diseases Research Network

Autor: Ashley Wilson, Erica Langley, Mariya Kozenko, Aizeddin A. Mhanni, Matthew A. Lines, Annette Feigenbaum, Sharan Goobie, Beth K. Potter, Valerie Austin, Andrea C. Yu, Suzanne Ratko, Saadet Mercimek-Andrews, Rebecca Sparkes, Natalya Karp, Hilary Vallance, Anthony Vandersteen, Alette Giezen, Kylie Tingley, Komudi Siriwardena, Melanie Napier, Kumanan Wilson, Julian Little, Chitra Prasad, Bruno Maranda, Brenda Wilson, Cheryl R. Greenberg, Yannis Trakadis, Grant A. Mitchell, Doug Coyle, Amy Pender, Nataliya Yuskiv, Sylvia Stockler-Ipsiroglu, Jagdeep S. Walia, Murray A. Potter, Alicia K. J. Chan, Michal Inbar-Feigenberg, Clara D.M. van Karnebeek, Michael Pugliese, Jonathan B. Kronick, Shailly Jain Ghai, Andreas Schulze, Catherine Brunel-Guitton, Laura Nagy, Monica Lamoureux, Michael T. Geraghty, Sarah Dyack, Ramona Salvarinova, Connie M Mohan, Jennifer MacKenzie, Pranesh Chakraborty, Daniela Buhas, John J. Mitchell, Michael Kowalski, Lesley Turner, Neal Sondheimer
Přispěvatelé: University of Manitoba
Rok vydání: 2019
Předmět:
Zdroj: Orphanet Journal of Rare Diseases
Paediatrics Publications
Orphanet Journal of Rare Diseases, Vol 15, Iss 1, Pp 1-12 (2020)
ISSN: 1750-1172
Popis: Background The Canadian Inherited Metabolic Diseases Research Network (CIMDRN) is a pan-Canadian practice-based research network of 14 Hereditary Metabolic Disease Treatment Centres and over 50 investigators. CIMDRN aims to develop evidence to improve health outcomes for children with inherited metabolic diseases (IMD). We describe the development of our clinical data collection platform, discuss our data quality management plan, and present the findings to date from our data quality assessment, highlighting key lessons that can serve as a resource for future clinical research initiatives relating to rare diseases. Methods At participating centres, children born from 2006 to 2015 who were diagnosed with one of 31 targeted IMD were eligible to participate in CIMDRN’s clinical research stream. For all participants, we collected a minimum data set that includes information about demographics and diagnosis. For children with five prioritized IMD, we collected longitudinal data including interventions, clinical outcomes, and indicators of disease management. The data quality management plan included: design of user-friendly and intuitive clinical data collection forms; validation measures at point of data entry, designed to minimize data entry errors; regular communications with each CIMDRN site; and routine review of aggregate data. Results As of June 2019, CIMDRN has enrolled 798 participants of whom 764 (96%) have complete minimum data set information. Results from our data quality assessment revealed that potential data quality issues were related to interpretation of definitions of some variables, participants who transferred care across institutions, and the organization of information within the patient charts (e.g., neuropsychological test results). Little information was missing regarding disease ascertainment and diagnosis (e.g., ascertainment method – 0% missing). Discussion Using several data quality management strategies, we have established a comprehensive clinical database that provides information about care and outcomes for Canadian children affected by IMD. We describe quality issues and lessons for consideration in future clinical research initiatives for rare diseases, including accurately accommodating different clinic workflows and balancing comprehensiveness of data collection with available resources. Integrating data collection within clinical care, leveraging electronic medical records, and implementing core outcome sets will be essential for achieving sustainability.
Databáze: OpenAIRE
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