Ying Wang1, Michele Caggana, Marilyn Sango-Jordan, Mingzeng Sun, Charlotte M Druschel. 1. Congenital Malformations Registry, Bureau of Environmental and Occupational Epidemiology, Center for Environmental Health, New York State Department of Health, Flanigan Square, 547 River Street, Troy, NY 12180-2216, USA. wxy01@health.state.ny.us
Abstract
BACKGROUND: Long-term follow-up of children identified through newborn screening is a critical process of data collection and analysis for advancing the public health understanding of the health outcomes and service uptake of the affected children. This article describes first steps toward the long-term follow-up of newborn screening children with confirmed disorders through records linkage using population-based administrative data. METHODS: The study cohort consisted of children born in 2006-2007 with confirmed disorders identified through newborn screening. Deterministic data linkage methods were used for record matching. RESULTS: The cohort was followed up to 2 years after birth by matching to data sources including vital records, hospital discharges, the Congenital Malformations Registry, and Early Intervention to monitor service utilization, comorbidities, and mortality of the affected children. Of 1215 children with confirmed conditions identified through newborn screening, 25 deaths (2.1%) were identified, 86.1% used hospital (in- or outpatient) services, 36.1% were enrolled in the Congenital Malformations Registry, and 19.9% used the services of the Early Intervention program during the 2-year follow-up period. CONCLUSIONS: Long-term follow-up of children with disorders identified through newborn screening can be initiated by using existing administrative data. This method is an inexpensive, cost-effective. and efficient approach for periodical assessment of services utilization, the efficiency of service delivery, and health outcomes for affected individuals.
BACKGROUND: Long-term follow-up of children identified through newborn screening is a critical process of data collection and analysis for advancing the public health understanding of the health outcomes and service uptake of the affected children. This article describes first steps toward the long-term follow-up of newborn screening children with confirmed disorders through records linkage using population-based administrative data. METHODS: The study cohort consisted of children born in 2006-2007 with confirmed disorders identified through newborn screening. Deterministic data linkage methods were used for record matching. RESULTS: The cohort was followed up to 2 years after birth by matching to data sources including vital records, hospital discharges, the Congenital Malformations Registry, and Early Intervention to monitor service utilization, comorbidities, and mortality of the affected children. Of 1215 children with confirmed conditions identified through newborn screening, 25 deaths (2.1%) were identified, 86.1% used hospital (in- or outpatient) services, 36.1% were enrolled in the Congenital Malformations Registry, and 19.9% used the services of the Early Intervention program during the 2-year follow-up period. CONCLUSIONS: Long-term follow-up of children with disorders identified through newborn screening can be initiated by using existing administrative data. This method is an inexpensive, cost-effective. and efficient approach for periodical assessment of services utilization, the efficiency of service delivery, and health outcomes for affected individuals.
Authors: Candace A Robledo; Edwina H Yeung; Pauline Mendola; Rajeshwari Sundaram; Nansi S Boghossian; Erin M Bell; Charlotte Druschel Journal: Matern Child Health J Date: 2017-04
Authors: Ying Wang; Gang Liu; Michele Caggana; Joseph Kennedy; Regina Zimmerman; Suzette O Oyeku; Ellen M Werner; Althea M Grant; Nancy S Green; Scott D Grosse Journal: Genet Med Date: 2014-09-25 Impact factor: 8.822
Authors: Cynthia F Hinton; Cara T Mai; Sarah K Nabukera; Lorenzo D Botto; Lisa Feuchtbaum; Paul A Romitti; Ying Wang; Kimberly Noble Piper; Richard S Olney Journal: Genet Med Date: 2013-12-05 Impact factor: 8.822
Authors: Ying Wang; Joseph Kennedy; Michele Caggana; Regina Zimmerman; Sanil Thomas; John Berninger; Katharine Harris; Nancy S Green; Suzette Oyeku; Mary Hulihan; Althea M Grant; Scott D Grosse Journal: Genet Med Date: 2012-09-27 Impact factor: 8.822