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Research Article

Predictors of Nontransport of Older Fallers Who Receive Ambulance Care

, MScM (ClinEpi), BEd, BHSc, , MM (ClinEpi), MBBS, PhD, , BStatEc, , BSc, PhD, , PhD & , MD
Pages 342-349 | Published online: 24 Jan 2014
 

Abstract

Objectives. To identify patient, clinical, and operational factors associated with nontransport of older people who have fallen and received ambulance care; and to develop a nontransport prediction tool that could be utilized during the dispatch process to rationalize allocation of emergency ambulance resources. Methods. The study was a planned subanalysis using data collected during a prospective observational cohort study of nonconsecutive emergency responses to older people aged 65 years or more who had fallen between October 1, 2010 and June 30, 2011. The data consisted of routinely collected ambulance dispatch and clinical records, combined with prospectively collected fall-specific information. Missing data were managed using multiple imputation. Multivariate logistic regression modeling was undertaken to identify predictors of nontransport. Results are described for original and imputated data sets, presented as odds ratios (OR) with 95%CI (confidence interval). Receiver operating curve (ROC) statistics were generated, with model discrimination determined by the area under the curve (AUC). Results. There were 1,484 cases eligible for this subanalysis of which 419 (28.2%) were recorded as nontransport. Multivariate regression including dispatch and clinical variables identified a 6-item final model. Younger age group, nonurgent response priority, and presence of a personal alarm were predictors of nontransport, along with clinical variables, including normal vital signs, absence of injury, and unchanged functional status post-fall. The AUC was 0.88 (95% CI 0.86–0.90; p < 0.0001) (imputed data AUC 0.86 (95% CI 0.84–0.88)). Multivariate modeling of dispatch variables only identified a 3-item final model, which included response nonurgent response priority, younger age, and the presence of a personal alarm. The AUC was 0.68 (95% CI 0.64–0.71; p < 0.0001) (imputed data AUC 0.69 (95% CI 0.66–0.72)). Conclusion. In this population of confirmed older fallers attended to by paramedics, determination of the prehospital transport outcome is greatly influenced by on-scene findings resulting from paramedic assessment. The presence of new pain, abnormal physiology, and altered function post-fall were strongly associated with increased odds of transport. Conversely the presence of a personal alarm and allocation of a nonurgent dispatch priority increased the odds of nontransport. Accurate discrimination between older fallers who were and were not transported using dispatch data only was not possible.

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