TY - JOUR
T1 - Evaluation of the quality of clinical data collection for a pan-Canadian cohort of children affected by inherited metabolic diseases
T2 - Lessons learned from the Canadian Inherited Metabolic Diseases Research Network
AU - Canadian Inherited Metabolic Diseases Research Network
AU - Tingley, Kylie
AU - Lamoureux, Monica
AU - Pugliese, Michael
AU - Geraghty, Michael T.
AU - Kronick, Jonathan B.
AU - Potter, Beth K.
AU - Coyle, Doug
AU - Wilson, Kumanan
AU - Kowalski, Michael
AU - Austin, Valerie
AU - Brunel-Guitton, Catherine
AU - Buhas, Daniela
AU - Chan, Alicia K.J.
AU - Dyack, Sarah
AU - Feigenbaum, Annette
AU - Giezen, Alette
AU - Goobie, Sharan
AU - Greenberg, Cheryl R.
AU - Ghai, Shailly Jain
AU - Inbar-Feigenberg, Michal
AU - Karp, Natalya
AU - Kozenko, Mariya
AU - Langley, Erica
AU - Lines, Matthew
AU - Little, Julian
AU - MacKenzie, Jennifer
AU - Maranda, Bruno
AU - Mercimek-Andrews, Saadet
AU - Mohan, Connie
AU - Mhanni, Aizeddin
AU - Mitchell, Grant
AU - Mitchell, John J.
AU - Nagy, Laura
AU - Napier, Melanie
AU - Pender, Amy
AU - Potter, Murray
AU - Prasad, Chitra
AU - Ratko, Suzanne
AU - Salvarinova, Ramona
AU - Schulze, Andreas
AU - Siriwardena, Komudi
AU - Sondheimer, Neal
AU - Sparkes, Rebecca
AU - Stockler-Ipsiroglu, Sylvia
AU - Trakadis, Yannis
AU - Turner, Lesley
AU - Van Karnebeek, Clara
AU - Vallance, Hilary
AU - Vandersteen, Anthony
AU - Walia, Jagdeep
N1 - Funding Information:
10.3390/ijerph15081644 Kodra Y, Weinbach J, Posada-De-La-Paz M, Coi A, Lemonnier SL, van Enckevort D, et al. Recommendations for improving the quality of rare disease registries. Int J Environ Res Public Health. 2018;15:1644. 20. Gliklich RE, Dreyer NA, Leavy MB. Registries for evaluating patient outcomes: a user’s guide. Third edition. Two volumes. (Prepared by the Outcome DEcIDE Center [Outcome Sciences, Inc., a Quintiles company] under Contract No. 290 2005 00351 TO7.) [Internet]. AHRQ Publ. No. 13(14)-EHC111. Rockville, MD; 2014. Available from: http://www.effectivehealthcare.ahrq.gov/registries-guide-3.cfm 21.
Publisher Copyright:
© 2020 The Author(s).
PY - 2020/4/10
Y1 - 2020/4/10
N2 - 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.
AB - 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.
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U2 - 10.1186/s13023-020-01358-z
DO - 10.1186/s13023-020-01358-z
M3 - Article
C2 - 32276663
AN - SCOPUS:85083218829
SN - 1750-1172
VL - 15
JO - Orphanet Journal of Rare Diseases
JF - Orphanet Journal of Rare Diseases
IS - 1
M1 - 89
ER -