Establishing a Multicentre Trauma Registry in India: An Evaluation of Data Completeness

World J Surg. 2019 Oct;43(10):2426-2437. doi: 10.1007/s00268-019-05039-2.

Abstract

Background: The completeness of a trauma registry's data is essential for its valid use. This study aimed to evaluate the extent of missing data in a new multicentre trauma registry in India and to assess the association between data completeness and potential predictors of missing data, particularly mortality.

Methods: The proportion of missing data for variables among all adults was determined from data collected from 19 April 2016 to 30 April 2017. In-hospital physiological data were defined as missing if any of initial systolic blood pressure, heart rate, respiratory rate, or Glasgow Coma Scale were missing. Univariable logistic regression and multivariable logistic regression, using manual stepwise selection, were used to investigate the association between mortality (and other potential predictors) and missing physiological data.

Results: Data on the 4466 trauma patients in the registry were analysed. Out of 59 variables, most (n = 51; 86.4%) were missing less than 20% of observations. There were 808 (18.1%) patients missing at least one of the first in-hospital physiological observations. Hospital death was associated with missing in-hospital physiological data (adjusted OR 1.4; 95% CI 1.02-2.01; p = 0.04). Other significant associations with missing data were: patient arrival time out of hours, hospital of care, 'other' place of injury, and specific injury mechanisms. Assault/homicide injury intent and occurrence of chest X-ray were associated with not missing any of first in-hospital physiological variables.

Conclusion: Most variables were well collected. Hospital death, a proxy for more severe injury, was associated with missing first in-hospital physiological observations. This remains an important limitation for trauma registries.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Female
  • Hospital Mortality
  • Humans
  • India / epidemiology
  • Logistic Models
  • Male
  • Middle Aged
  • Registries*
  • Wounds and Injuries / epidemiology*
  • Wounds and Injuries / mortality