Does Transport Time Help Explain the High Trauma Mortality Rates in Rural Areas? New and Traditional Predictors Assessed by New and Traditional Statistical Methods

Overview

Journal Inj Prev

Specialties Emergency Medicine
Pediatrics
Public Health

Date 2015 May 15

PMID 25972600

Citations 4

Authors

Jo Roislien

Hans Morten Lossius

Thomas Kristiansen

Affiliations

Soon will be listed here.

Abstract

Background: Trauma is a leading global cause of death. Trauma mortality rates are higher in rural areas, constituting a challenge for quality and equality in trauma care. The aim of the study was to explore population density and transport time to hospital care as possible predictors of geographical differences in mortality rates, and to what extent choice of statistical method might affect the analytical results and accompanying clinical conclusions.

Methods: Using data from the Norwegian Cause of Death registry, deaths from external causes 1998-2007 were analysed. Norway consists of 434 municipalities, and municipality population density and travel time to hospital care were entered as predictors of municipality mortality rates in univariate and multiple regression models of increasing model complexity. We fitted linear regression models with continuous and categorised predictors, as well as piecewise linear and generalised additive models (GAMs). Models were compared using Akaike's information criterion (AIC).

Results: Population density was an independent predictor of trauma mortality rates, while the contribution of transport time to hospital care was highly dependent on choice of statistical model. A multiple GAM or piecewise linear model was superior, and similar, in terms of AIC. However, while transport time was statistically significant in multiple models with piecewise linear or categorised predictors, it was not in GAM or standard linear regression.

Conclusions: Population density is an independent predictor of trauma mortality rates. The added explanatory value of transport time to hospital care is marginal and model-dependent, highlighting the importance of exploring several statistical models when studying complex associations in observational data.

Citing Articles

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PMID: 32201736 PMC: 7066640. DOI: 10.1136/tsaco-2019-000405.

Effect of predicted travel time to trauma care on mortality in major trauma patients in Nova Scotia.

Tansley G, Schuurman N, Bowes M, Erdogan M, Green R, Asbridge M Can J Surg. 2019; 62(2):123-130.

PMID: 30907993 PMC: 6440889. DOI: 10.1503/cjs.004218.

Predictive accuracy of medical transport information for in-hospital mortality.

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Fatal injuries in rural and urban areas in northern Finland: a 5-year retrospective study.

Raatiniemi L, Steinvik T, Liisanantti J, Ohtonen P, Martikainen M, Alahuhta S Acta Anaesthesiol Scand. 2016; 60(5):668-76.

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