Population‐based surveillance of congenital heart defects among adolescents and adults: surveillance methodology. Issue 19 (5th November 2018)

• Record Type: Journal Article
• Authors: Glidewell, Jill; Book, Wendy; Raskind‐Hood, Cheryl; Hogue, Carol; Dunn, Julie E.; Gurvitz, Michelle; Ozonoff, Al; McGarry, Claire; Van Zutphen, Alissa; Lui, George; Downing, Karrie; Riehle‐Colarusso, Tiffany
• Other Names: Kirby Dr. Russell guestEditor.; Browne Dr. Marilyn guestEditor.
• Is Part Of: Birth defects research. Volume 110:Issue 19(2018)
• Page Start: 1395
• Page End: 1403
• Publication Date: 2018-11-05
• Subjects: birth defects -- birth defects registry -- congenital heart defects -- surveillance; Teratology -- Periodicals; Abnormalities, Human -- Periodicals; Congenital Abnormalities; Embryo, Mammalian -- abnormalities; Teratology; Abnormalities, Human; Teratology; Periodicals; Periodicals; 616.043
• DOI: 10.1002/bdr2.1400
• Languages: English
• ISSNs: 2472-1727

Abstract

Abstract : Background: Improved treatment of congenital heart defects (CHDs) has increased survival of persons with CHDs; however, no U.S. population‐based systems exist to assess prevalence, healthcare utilization, or longer‐term outcomes among adolescents and adults with CHDs. Methods: Novel approaches identified individuals aged 11–64 years who received healthcare with ICD‐9‐CM codes for CHDs at three sites: Emory University in Atlanta, Georgia (EU), Massachusetts Department of Public Health (MA), New York State Department of Health (NY) between January 1, 2008 (2009 for MA) and December 31, 2010. Case‐finding sources included outpatient clinics; Medicaid and other claims data; and hospital inpatient, outpatient, and emergency visit data. Supplemental information came from state vital records (EU, MA), and birth defects registries (EU, NY). Demographics and diagnostic and procedural codes were linked, de‐duplicated, and shared in a de‐identified dataset. Cases were categorized into one of five mutually exclusive CHD severity groups; non‐cardiac comorbidity codes were grouped into broad categories. Results: 73, 112 individuals with CHD codes in healthcare encounters were identified. Primary data source type varied: clinics (EU, NY for adolescents), claims (MA), hospital (NY for adults). There was a high rate of missing data for some variables and data varied in format and quality. Some diagnostic codes had poor specificity for CHD ascertainment. Conclusions: To our knowledge, this is the first population‐based, multi‐site CHD surveillance among adolescents and adults in the U.S. Identification of people living with CHDs through healthcare encounters using multiple data sources was feasible, though data quality varied and linkage/de‐duplication was labor‐intensive.