Developing a suite of analytic and reporting tools to ensure that newborn screening is as effective as possible
Newborn screening ensures early identification of metabolic and hereditary disorders for an estimated 12,500 infants in the United States each year.
In Virginia, the Division of Consolidated Laboratory Services is responsible for screening and partnering with the Virginia Department of Health to follow up on potential cases of infants with disorders in the screening panel.
Although screening is in its fifth decade, many hospitals do not submit quality samples in a timely manner, increasing the risk that potentially life-threatening disorders will not be discovered in time to provide appropriate interventions. In addition, many of the Division of Consolidated Laboratory Services’ analytics and reporting procedures are manual and time-intensive, limiting understanding of key metrics and impeding optimization of screening and follow-up protocols.
The approach of the researchers, MSDS students Chris Patrick and Hampton Leonard, was to provide the state with a suite of analytic and reporting tools, including:
- automated hospital report cards with improved visualizations and information on diagnoses,
- mapping of disease diagnoses for a given time period, and
- modeling of the relationship between various infant and sample factors and the likelihood that a test result will be abnormal or critical when no disease is present.
These tools will help the state better target underperforming hospitals, direct services to areas with greater concentrations of disease and ensure that screening protocols are as effective as possible, all in support of the larger goal of keeping Virginia’s infants healthy.