| Title |
Developing a public health-tracking system for follow-up of newborn screening metabolic conditions: a four-state pilot project structure and initial findings
|
|---|---|
| Published in |
Genetics in Medicine, December 2013
|
| DOI | 10.1038/gim.2013.177 |
| Pubmed ID | |
| 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 |
| Abstract |
Purpose:The aim of this study was to describe the methods, cases, and initial results of a pilot project using existing public health data collection programs (birth defect surveillance or newborn screening) to conduct long-term follow-up of children with metabolic disorders.Methods:California, Iowa, New York, and Utah expanded birth defect surveillance or newborn screening programs to collect long-term follow-up data on 19 metabolic disorders. Data elements to monitor health status and services delivered were identified, and record abstraction and data linkages were conducted. Children were followed up through to the age of 3 years.Results:A total of 261 metabolic cases were diagnosed in 1,343,696 live births (19.4 cases/100,000; 95% confidence interval = 17.1-21.8). Four deaths were identified. Children with fatty acid oxidation disorders had a higher percentage of health service encounters compared with children with other disorders of at least one health service encounter (hospitalization, emergency room, metabolic clinic, genetic service provider, or social worker) except for hospitalizations; children with organic acid disorders had a higher percentage of at least one hospitalization during their third year of life than children with other disorders.Conclusion:Existing public health data programs can be leveraged to conduct population-based newborn screening long-term follow-up. This approach is flexible according to state needs and resources. These data will enable the states in assessing health burden, assuring access to services, and supporting policy development.Genet Med 16 6, 484-490. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 67% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 3% |
| Unknown | 38 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 7 | 18% |
| Researcher | 7 | 18% |
| Student > Bachelor | 3 | 8% |
| Other | 3 | 8% |
| Professor > Associate Professor | 3 | 8% |
| Other | 6 | 15% |
| Unknown | 10 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 12 | 31% |
| Engineering | 4 | 10% |
| Nursing and Health Professions | 3 | 8% |
| Agricultural and Biological Sciences | 2 | 5% |
| Social Sciences | 2 | 5% |
| Other | 5 | 13% |
| Unknown | 11 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 December 2013.
All research outputs
#15,518,326
of 25,377,790 outputs
Outputs from Genetics in Medicine
#2,465
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Outputs of similar age
#183,138
of 320,227 outputs
Outputs of similar age from Genetics in Medicine
#19
of 26 outputs
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