National Data on “Unexpected” Newborn Complications

Background: MCH directors and perinatal leaders are charged with monitoring perinatal outcomes and quality across their state, region and nationally. Analytic tools that help focus their attention and align limited quality improvement resources with the greatest need should always be welcomed.  Most outcome surveillance revolves around high risk mothers and newborns especially given their immediate and long-term impact.  A relatively new metric looks at a population where adverse outcomes are least expected—the low risk, term newborns.  The Unexpected Newborn Complication(UNC) rate can be calculated at the hospital, system or statewide level using readily available discharge data sets giving MCH leaders a way to monitor outcomes for the majority of the newborn population.

Method This analysis is based on the work of the California Maternal Quality Care Collaborative (CMQCC).  It measures those newborns without preexisting complications that have an unexpectedmoderate or severe complication.

Results:  The data covers the period 1/1/2012-12/31/2012 and 333,963 newborn/ inborn discharges from the National Perinatal Information Center Perinatal Center Data Base.

• The overall rate of UNC was 3.6%, 38.9 % were coded with severe complications, 61.1 % with moderate complications.

• For infants with moderate complications, 63.6% were admitted to a special care nursery, 78.1 % with severe complications were admitted.

Conclusion: The UNC rate provides perinatal leaders a relatively easy way to monitor unexpected adverse outcomes in a population that is generally not the focus of their attention.

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Learning Areas:

Administration, management, leadership
Other professions or practice related to public health
Public health administration or related administration

Learning Objectives:
Define the Unexpected Newborn Complication (UNC) rate Explain the rate algorithm as well as numerator and deominator inclusions and exclusions Identify readily available data sources that can be used to calculate the UNC rate at the hospital, system and statewide level

Keyword(s): Birth Outcomes, Performance Measurement

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am the President of the National Perinatal Information Center and have worked with administrative data sets for the past 30 years. The analysis presented was developed on our Perinatal Center Data Base and has been a metric that we include in all of our standard quarterly reports to our member hospitals. We are also using it as part of a panel of outcome metrics on a national quality improvement initiative with RTI.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

Back to: 4149.0: Current Topics in Infant & Child Health