Skip to main content Accessibility help
×
Home
Hostname: page-component-59b7f5684b-npccv Total loading time: 0.32 Render date: 2022-09-29T05:06:04.100Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "useRatesEcommerce": false, "displayNetworkTab": true, "displayNetworkMapGraph": false, "useSa": true } hasContentIssue true

Data quality methods through remote source data verification auditing: results from the Congenital Cardiac Research Collaborative

Published online by Cambridge University Press:  17 March 2021

Joelle A. Pettus*
Affiliation:
Emory University School of Medicine, Department of Pediatrics, Children’s Healthcare of Atlanta, Atlanta, GA, USA
Amy L. Pajk
Affiliation:
The Heart Institute, Cincinnati Children’s Hospital and Department of Pediatrics, Cincinnati, OH, USA
Andrew C. Glatz
Affiliation:
The Cardiac Center, Department of Pediatrics, Children’s Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
Christopher J. Petit
Affiliation:
Emory University School of Medicine, Department of Pediatrics, Children’s Healthcare of Atlanta, Atlanta, GA, USA
Bryan H. Goldstein
Affiliation:
Heart Institute, UPMC Children’s Hospital of Pittsburgh and Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
Athar M. Qureshi
Affiliation:
The Lillie Frank Abercrombie Section of Cardiology, Department of Pediatrics, Texas Children’s Hospital, Baylor College of Medicine, Houston, TX, USA
George T. Nicholson
Affiliation:
Division of Cardiology, Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, TN, USA
Jeffery J. Meadows
Affiliation:
Division of Cardiology, Department of Pediatrics, University of California San Francisco School of Medicine, San Francisco, CA, USA
Jeffrey D. Zampi
Affiliation:
Division of Cardiology, Department of Pediatrics, CS Mott Children’s Hospital, University of Michigan School of Medicine, Ann Arbor, MI, USA
Mark A. Law
Affiliation:
Division of Pediatric Cardiology, Department of Pediatrics, Children’s of Alabama, University of Alabama Birmingham School of Medicine, Birmingham, AL, USA
Shabana Shahanavaz
Affiliation:
Section of Pediatric Cardiology, Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA
Michael S. Kelleman
Affiliation:
Emory University School of Medicine, Department of Pediatrics, Children’s Healthcare of Atlanta, Atlanta, GA, USA
Courtney M. McCracken
Affiliation:
Emory University School of Medicine, Department of Pediatrics, Children’s Healthcare of Atlanta, Atlanta, GA, USA
*
Author for correspondence: Joelle A. Pettus, MPH, MSW, Emory University School of Medicine, Department of Pediatrics, 2015 Uppergate Drive, Atlanta, GA30322, USA. Tel: 404-727-5198; Fax: 770-488-9015. E-mail: JPettus@emory.edu

Abstract

Background:

Multicentre research databases can provide insights into healthcare processes to improve outcomes and make practice recommendations for novel approaches. Effective audits can establish a framework for reporting research efforts, ensuring accurate reporting, and spearheading quality improvement. Although a variety of data auditing models and standards exist, barriers to effective auditing including costs, regulatory requirements, travel, and design complexity must be considered.

Materials and methods:

The Congenital Cardiac Research Collaborative conducted a virtual data training initiative and remote source data verification audit on a retrospective multicentre dataset. CCRC investigators across nine institutions were trained to extract and enter data into a robust dataset on patients with tetralogy of Fallot who required neonatal intervention. Centres provided de-identified source files for a randomised 10% patient sample audit. Key auditing variables, discrepancy types, and severity levels were analysed across two study groups, primary repair and staged repair.

Results:

Of the total 572 study patients, data from 58 patients (31 staged repairs and 27 primary repairs) were source data verified. Amongst the 1790 variables audited, 45 discrepancies were discovered, resulting in an overall accuracy rate of 97.5%. High accuracy rates were consistent across all CCRC institutions ranging from 94.6% to 99.4% and were reported for both minor (1.5%) and major discrepancies type classifications (1.1%).

Conclusion:

Findings indicate that implementing a virtual multicentre training initiative and remote source data verification audit can identify data quality concerns and produce a reliable, high-quality dataset. Remote auditing capacity is especially important during the current COVID-19 pandemic.

Type
Original Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Petit, CJ, Qureshi, AM, Glatz, AC, et al. Comprehensive comparative outcomes in children with congenital heart disease: the rationale for the Congenital Catheterization Research Collaborative. Congenit Heart Dis 2019; 14: 341349. doi: 10.1111/chd.12737.CrossRefGoogle ScholarPubMed
Petit, CJ, Glatz, AC, Qureshi, AM, et al. Outcomes after decompression of the right ventricle in infants with pulmonary atresia with intact ventricular septum are associated with degree of tricuspid regurgitation: results from the Congenital Catheterization Research Collaborative. Circ Cardiovasc Interv 2017; 10: e004428. doi: 10.1161/CIRCINTERVENTIONS.116.004428. Erratum in: Circ Cardiovasc Interv. 2017 Jun;10(6).CrossRefGoogle ScholarPubMed
Petit, CJ, Gao, K, Goldstein, BH, et al. Relation of aortic valve morphologic characteristics to aortic valve insufficiency and residual stenosis in children with congenital aortic stenosis undergoing balloon valvuloplasty. Am J Cardiol 2016; 117: 972979. doi: 10.1016/j.amjcard.2015.12.034 CrossRefGoogle ScholarPubMed
Glatz, AC, Petit, CJ, Goldstein, BH, et al. A Comparison Between Patent Ductus Arteriosus Stent and Modified Blalock-Taussig Shunt as Palliation for Infants with Ductal-Dependent Pulmonary Blood Flow: insights from the Congenital Catheterization Research Collaborative. Circulation 2018; 137: 589601. 10.1161/CIRCULATIONAHA.CrossRefGoogle ScholarPubMed
Goldstein, BH, Petit, CJ, Qureshi, AM, et al. Comparison of Management Strategies for the Neonate with Symptomatic Tetralogy of Fallot: A Study from the Congenital Cardiac Research Collaborative. J Am Coll Cardiol 2021; 77: 10931106.CrossRefGoogle Scholar
Giganti, MJ, Shepherd, BE, Caro-Vega, Y, et al. The impact of data quality and source data verification on epidemiologic inference: a practical application using HIV observational data. BMC Public Health 2019; 19: 1748. doi: 10.1186/s12889-019-8105-2.CrossRefGoogle ScholarPubMed
Harris, PA, Taylor, R, Thielke, R, Payne, J, Gonzalez, N, Conde, JG Research Electronic Data Capture (REDCap): a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009; 42: 377381. doi: 10.1016/j.jbi.2008.08.010.CrossRefGoogle ScholarPubMed
Daniels, K, Lawson, E Enhancing Clinical Librarian Work Processes and Communicating Service Impact with REDCap and Data Visualization. Med Ref Serv Q 2019; 38: 187196. doi: 10.1080/02763869.2019.CrossRefGoogle ScholarPubMed
Gaies, M, Donohue, JE, Willis, GM, et al. Data integrity of the Pediatric Cardiac Critical Care Consortium (PC4) clinical registry. Cardiol Young 2016; 26: 10901096. doi: 10.1017/S1047951115001833.CrossRefGoogle ScholarPubMed
Houston, L, Probst, Y, Humphries, A. Measuring data quality through a source data verification audit in a clinical research setting. Stud Health Technol Inform 2015; 214: 107113.Google Scholar
Messenger, JC, Ho, KK, Young, CH, et al. NCDR Science and Quality Oversight Committee Data Quality Workgroup. The National Cardiovascular Data Registry (NCDR) Data Quality Brief: the NCDR Data Quality Program in 2012. J Am Coll Cardiol 2012; 60: 14841488. doi: 10.1016/j.jacc.2012.07.020.CrossRefGoogle ScholarPubMed
Gaies, M, Cooper, DS, Tabbutt, S, et al. Collaborative quality improvement in the cardiac intensive care unit: development of the Paediatric Cardiac Critical Care Consortium (PC4). Cardiol Young 2015; 25: 951957. doi: 10.1017/S1047951114001450.CrossRefGoogle Scholar
Overman, DM, Jacobs, ML, O’Brien, JE, et al. Ten Years of Data Verification: the Society of Thoracic Surgeons Congenital Heart Surgery Database Audits. World J Pediatr Congenit Heart Surg 2019; 10: 454463. doi: 10.1177/2150135119845256.CrossRefGoogle Scholar
Andersen, JR, Byrjalsen, I, Bihlet, A, et al. Impact of source data verification on data quality in clinical trials: an empirical post hoc analysis of three phase 3 randomized clinical trials. Br J Clin Pharmacol 2015; 79: 660668. doi: 10.1111/bcp.12531.CrossRefGoogle ScholarPubMed
Mealer, M, Kittelson, J, Thompson, BT, et al. Remote source document verification in two national clinical trials networks: a pilot study. PLoS One 2013; 8: e81890. doi: 10.1371/journal.pone.0081890.CrossRefGoogle ScholarPubMed
Supplementary material: File

Pettus et al. supplementary material

Table S2

Download Pettus et al. supplementary material(File)
File 22 KB
Supplementary material: File

Pettus et al. supplementary material

Table S1

Download Pettus et al. supplementary material(File)
File 24 KB
1
Cited by

Save article to Kindle

To save this article to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Data quality methods through remote source data verification auditing: results from the Congenital Cardiac Research Collaborative
Available formats
×

Save article to Dropbox

To save this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about saving content to Dropbox.

Data quality methods through remote source data verification auditing: results from the Congenital Cardiac Research Collaborative
Available formats
×

Save article to Google Drive

To save this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about saving content to Google Drive.

Data quality methods through remote source data verification auditing: results from the Congenital Cardiac Research Collaborative
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *