Literature DB >> 10259646

Estimating need and demand for prehospital care.

R D Kamenetzky, L J Shuman, H Wolfe.   

Abstract

Models estimating demand and need for emergency transportation services are developed. These models can provide reliable estimates which can be used for planning purposes, by complementing and/or substituting for historical data. The model estimating demand requires only four independent variables: population in the area, employment in the area, and two indicators of socioeconomic status which can be obtained from census data. The model can be used to estimate demand according to 4 operational categories and 11 clinical categories. The parameters of the model are calibrated with 1979 data from 82 ambulance services covering over 200 minor civil divisions in Southwestern Pennsylvania. This model was tested with data from another 55 minor civil divisions, also in Southwestern Pennsylvania, and it provided good estimates to total demand. The model to estimate need evolves from the demand model. It enables planners to estimate unmet need occurring in the region. The effect of emergency transportation service (ETS) provider characteristics on demand was also investigated. Statistical tests show that, for purposes of forecasting demand, when the sociodemographic factors are taken into account, provider characteristics are not significant.

Mesh:

Year:  1982        PMID: 10259646     DOI: 10.1287/opre.30.6.1148

Source DB:  PubMed          Journal:  Oper Res        ISSN: 0030-364X            Impact factor:   3.310


  2 in total

1.  The application of forecasting techniques to modeling emergency medical system calls in Calgary, Alberta.

Authors:  Nabil Channouf; Pierre L'Ecuyer; Armann Ingolfsson; Athanassios N Avramidis
Journal:  Health Care Manag Sci       Date:  2007-02

2.  Daily volume of cases in emergency call centers: construction and validation of a predictive model.

Authors:  Damien Viglino; Aurelien Vesin; Stephane Ruckly; Xavier Morelli; Rémi Slama; Guillaume Debaty; Vincent Danel; Maxime Maignan; Jean-François Timsit
Journal:  Scand J Trauma Resusc Emerg Med       Date:  2017-08-29       Impact factor: 2.953

  2 in total

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