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Related Concept Videos

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Related Experiment Video

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Infant Auditory Processing and Event-related Brain Oscillations
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Using Infant Mortality Data to Improve Maternal and Child Health Programs: An Application of Statistical Process

Patricia Finnerty1, Lloyd Provost2, Emily O'Donnell3

  • 1Education Development Center, 43 Foundry Ave, Waltham, MA, 02453, USA. pfinnerty@edc.org.

Maternal and Child Health Journal
|January 11, 2019
PubMed
Summary

Statistical process control (SPC) charts, specifically T and G charts, effectively identify special cause variations in infant mortality rates (IMR) for rare events. These charts offer valuable insights for public health departments analyzing infant death data.

Keywords:
Infant mortalityQuality improvementRare eventsStatistical process control (SPC)

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Area of Science:

  • Public Health
  • Biostatistics
  • Maternal and Child Health (MCH)

Background:

  • The United States faces a higher infant mortality rate (IMR) compared to other developed nations.
  • Analyzing IMR is crucial for public health departments to understand and address disparities.
  • Infrequent infant deaths present analytical challenges for traditional methods.

Purpose of the Study:

  • To evaluate the utility of statistical process control (SPC) charts for analyzing rare events in IMR data.
  • To support state public health departments in data display and analysis for improved learning.
  • To identify methods for effectively analyzing IMR in population subsets with infrequent deaths.

Main Methods:

  • Utilized state vital records data on live births and infant deaths.
  • Created U, T, and G charts for Kansas and Alaska, focusing on specific populations and regions.
  • Analyzed IMR, days between deaths, and births between deaths for the periods 2013-2016 and 2011-2016.

Main Results:

  • T and G charts for Kansas, and G charts for Alaska, showed points outside the upper control limit.
  • These points indicated special cause variation and periods with increased days or births between infant deaths.
  • Special cause variations were detected that might be missed by U charts or traditional methods.

Conclusions:

  • T and G charts are valuable for examining rare events in IMR data.
  • SPC charts can identify special causes of variation not detectable by traditional analytic methods.
  • SPC holds potential for understanding drivers of rare outcomes and informing interventions in MCH.