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Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
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Multiple imputation in trauma disparity research.

Tolulope A Oyetunji1, Joseph G Crompton, Imudia D Ehanire

  • 1Department of Surgery, Howard University College of Medicine, Washington, DC 20060, USA. toyetunji@howard.edu

The Journal of Surgical Research
|November 12, 2010
PubMed
Summary

Multiple imputation (M.IMP) effectively addresses missing race and insurance data in trauma research. This method proved feasible for the National Data Trauma Bank, yielding results comparable to complete datasets.

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Area of Science:

  • Trauma research
  • Data science
  • Biostatistics

Background:

  • Missing data, particularly race and insurance information, presents a significant challenge in trauma outcomes research.
  • Multiple imputation (M.IMP) is a statistical technique recommended for addressing such data deficiencies.

Purpose of the Study:

  • To evaluate the feasibility and impact of multiple imputation (M.IMP) on handling missing race and insurance data within the National Data Trauma Bank (NTDB).
  • To compare the results of multivariate analyses performed on complete versus imputed datasets.

Main Methods:

  • A complete dataset was created from the NTDB by removing cases with missing variables.
  • An incomplete dataset was simulated via random deletion, followed by five rounds of M.IMP.
  • Multivariate analyses were conducted on both datasets to assess the effect of race and insurance on mortality.

Main Results:

  • The study identified missing data proportions for key covariates: age (4%), gender (0.4%), race (8%), insurance (17%), injury severity score (6%), revised trauma score (20%), and trauma type (3%).
  • The results derived from the multiple imputation dataset were qualitatively similar to those from the original, complete dataset.

Conclusions:

  • Multiple imputation (M.IMP) is a practical and effective method for managing missing race and insurance data in the National Data Trauma Bank.
  • The use of M.IMP can help mitigate data disparities and improve the reliability of trauma outcomes research.