Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-27T05:56:58.501Z Has data issue: false hasContentIssue false
  • English
  • Français

Feasibility of a healthcare system-based tetralogy of Fallot patient registry

Published online by Cambridge University Press:  29 August 2017

Audrey L. Khoury ,
Eric G. Jernigan ,
Muntasir H. Chowdhury ,
Laura R. Loehr  and
Jennifer S. Nelson
Audrey L. Khoury
Affiliation:
Department of Surgery, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America
Eric G. Jernigan
Affiliation:
Department of Surgery, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America
Muntasir H. Chowdhury
Affiliation:
Department of Surgery, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America
Laura R. Loehr
Affiliation:
Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America
Jennifer S. Nelson*
Affiliation:
Department of Surgery, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America
*
Correspondence to: J. S. Nelson, MD, MS, Department of Cardiothoracic Surgery, Nemours Children’s Hospital, 13535 Nemours Parkway, Orlando, FL 32827, United States of America. Tel: 407 414 8804; Fax: 321 388 0100; E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Patient-reported outcomes and epidemiological studies in adults with tetralogy of Fallot are lacking. Recruitment and longitudinal follow-up investigation across institutions is particularly challenging. Objectives of this study were to assess the feasibility of recruiting adult patients with tetralogy of Fallot for a patient-reported outcomes study, describe challenges for recruitment, and create an interactive, online tetralogy of Fallot registry.

Methods

Adult patients living with tetralogy of Fallot, aged 18–58 years, at the University of North Carolina were identified using diagnosis code query. A survey was designed to collect demographics, symptoms, history, and birth mother information. Recruitment was attempted by phone (Part I, n=20) or by email (Part II, n=20). Data analysis included thematic grouping of recruitment challenges and descriptive statistics. Feasibility threshold was 75% for recruitment and for data fields completed per patient.

Results

In Part I, 60% (12/20) were successfully contacted and eight (40%) were enrolled. Demographics and birth mother information were obtained for all enrolled patients. In Part II, 70% (14/20) were successfully contacted; 30% (6/20) enrolled and completed all data fields linked to REDCap database; the median time for survey completion was 8 minutes. Half of the patients had cardiac operations/procedures performed at more than one hospital. Automatic electronic data entry from the online survey was uncomplicated.

Conclusions

Although recruitment (54%) fell below our feasibility threshold, enrolled individuals were willing to complete phone or online surveys. Incorrect contact information, privacy concerns, and patient-reported time constraints were challenges for recruitment. Creating an online survey and linked database is technically feasible and efficient for patient-reported outcomes research.

Keywords

Adult CHDtetralogy of Fallotregistrypatient-reported outcomes
Type
Original Articles
Information
Cardiology in the Young , Volume 28 , Issue 2 , February 2018 , pp. 269 - 275
Check for updates
Copyright
© Cambridge University Press 2017 

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.)

Footnotes

†

Current address Joan C. Edwards School of Medicine, Marshall University, Huntington, West Virginia, United States of America

‡

Current address: Nemours Children’s Hospital, Orlando, Florida, United States of America

References

1. NIH. What is tetralogy of Fallot? National Heart, Lung, and Blood Institute. Retrieved July 1, 2011, from http://www.nhlbi.nih.gov/health/health-topics/topics/tof.Google Scholar
2. Centers for Disease Control and Prevention. Facts about tetralogy of Fallot. National Center on Birth Defects and Developmental Disabilities. Retrieved July 17, 2013, from http://www.cdc.gov/ncbddd/heartdefects/tetralogyoffallot.html.Google Scholar
3. North Carolina Department of Health and Human Services. Frequency of selected birth defects in North Carolina. North Carolina State Center for Health Statistics. Retrieved July 19, 2013, from http://www.schs.state.nc.us/data/bd/frequency.htm.Google Scholar
4. Jenkins, KJ, Correa, A, Feinstein, JA, et al. Noninherited risk factors and congenital cardiovascular defects: current knowledge – a scientific statement from the American Heart Association Council on Cardiovascular Disease in the Young: endorsed by the American Academy of Pediatrics. Circulation 2007; 115: 2995–3014.Google Scholar
5. Neill, CA, Clark, EB. Tetralogy of Fallot – the first 300 years. Tex Heart Inst J 1994; 21: 272–279.Google ScholarPubMed
6. Hickey, EJ, Veldtman, G, Bradley, TJ, et al. Late risk of outcomes for adults with repaired tetralogy of Fallot from an inception cohort spanning four decades. Eur J Cardiothorac Surg 2009; 35: 156–164.Google Scholar
7. Zampi, JD, Armstrong, AK, Hirsch-Romano, JC. Hybrid perventricular pulmonary valve perforation and right ventricular outflow stent placement: a case report of a premature, 1.3-kg neonate with tetralogy of Fallot and pulmonary atresia. World J Pediatr Congenit Heart Surg 2014; 5: 338–341.Google Scholar
8. Wren, C. Prematurity, low birth weight, and cardiovascular malformations. Pediatrics 2011; 127: 385–386.Google Scholar
9. Nelson, JS, Stebbins, RC, Strassle, PD, et al. Geographic distribution of live births with tetralogy of Fallot in North Carolina 2003 to 2012. Birth Defects Res A Clin Mol Teratol 2016; 106: 881–887.Google Scholar
10. North Carolina Department of Health and Human Services. Birth defects monitoring program. North Carolina State Center for Health Statistics. Retrieved July 29, 2016, from http://www.schs.state.nc.us/units/bdmp.Google Scholar
11. Riehle-Colarusso, TJ, Bergersen, L, Broberg, CS, et al. Databases for congenital heart defect public health studies across the lifespan. J Am Heart Assoc 2016; 5: e004148.Google Scholar
12. National Center for Health Statistics. ICD-9-CM: International Classification of Diseases, 9th Revision, Clinical Modification. Medicode, Salt Lake City, UT, 1996.Google Scholar
13. StataCorp. Stata Statistical Software: Release 13. StataCorp LP, College Station, TX, 2013.Google Scholar
14. Harris, PA, Taylor, R, Thielke, R, et al. Research electronic data capture (REDCap) – a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009; 42: 377–381.Google Scholar
15. Ashley, L, Jones, H, Thomas, J, et al. Integrating patient reported outcomes with clinical cancer registry data: a feasibility study of the electronic patient-reported outcomes from cancer survivors (ePOCS) system. J Med Internet Res 2013; 15: e230.Google Scholar
16. Cavero-Carbonell, C, Gras-Colomer, E, Guaita-Calatrava, R, et al. Consensus on the criteria needed for creating a rare-disease patient registry. A Delphi study. J Public Health 2016; 38: 178–186.Google Scholar
17. Schumacher, KR, Stringer, KA, Donohue, JE, et al. Social media methods for studying rare diseases. Pediatrics 2014; 133: 1345–1353.Google Scholar