H T Wong1, P C Lai. 1. Department of Geography, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, PR China. frankwong@graduate.hku.hk
Abstract
AIM: To examine weather effects on the daily demand for ambulance services in Hong Kong. METHODS: Over 6 million cases of emergency attendance from May 2006 through April 2009 (3 years) were obtained from the Hospital Authority in Hong Kong. These cases were further stratified by age, triage levels, hospital admission status, comprehensive social security assistance (CSSA) recipients and gender. The stratification was used to correlate against weather factors to assess the dependency of these variables and their effects on the daily number of ambulance calls. Adjusted-R(2) values obtained from the regression analysis were used as a measure for evaluating predictability. RESULTS: The adjusted-R(2) of emergency cases by age groups showed proportional correlation with weather factors, which was more significant in older patients (0.76, p<0.01) than young patients (0.10, p<0.05). Furthermore, patients with more severe conditions were shown to have a higher adjusted-R(2) (0.63, p<0.05 for critical as opposed to 0 for non-urgent patients). Weather effects were also found more significant in women (0.50, p<0.01) and CSSA recipients (0.54, p<0.01) when compared against their corresponding reference groups (respectively men at 0.46, p<0.01 and non-CSSA recipients at 0.45, p<0.01). Moreover, average temperature appeared to be a major weather effect. CONCLUSIONS: The presence of strong weather effects among different target groups indicates possibility for the development of a short-term forecast system of daily ambulance demand using weather variables. The availability of such a forecast system would render more effective deployment of the ambulance services to meet the unexpected increase in service demands.
AIM: To examine weather effects on the daily demand for ambulance services in Hong Kong. METHODS: Over 6 million cases of emergency attendance from May 2006 through April 2009 (3 years) were obtained from the Hospital Authority in Hong Kong. These cases were further stratified by age, triage levels, hospital admission status, comprehensive social security assistance (CSSA) recipients and gender. The stratification was used to correlate against weather factors to assess the dependency of these variables and their effects on the daily number of ambulance calls. Adjusted-R(2) values obtained from the regression analysis were used as a measure for evaluating predictability. RESULTS: The adjusted-R(2) of emergency cases by age groups showed proportional correlation with weather factors, which was more significant in older patients (0.76, p<0.01) than young patients (0.10, p<0.05). Furthermore, patients with more severe conditions were shown to have a higher adjusted-R(2) (0.63, p<0.05 for critical as opposed to 0 for non-urgent patients). Weather effects were also found more significant in women (0.50, p<0.01) and CSSA recipients (0.54, p<0.01) when compared against their corresponding reference groups (respectively men at 0.46, p<0.01 and non-CSSA recipients at 0.45, p<0.01). Moreover, average temperature appeared to be a major weather effect. CONCLUSIONS: The presence of strong weather effects among different target groups indicates possibility for the development of a short-term forecast system of daily ambulance demand using weather variables. The availability of such a forecast system would render more effective deployment of the ambulance services to meet the unexpected increase in service demands.
Authors: Jone Vencloviene; Ruta M Babarskiene; Paulius Dobozinskas; Gintare Sakalyte; Kristina Lopatiene; Nerijus Mikelionis Journal: Int J Environ Res Public Health Date: 2015-02-27 Impact factor: 3.390
Authors: Ho Ting Wong; Vico Chung Lim Chiang; Kup Sze Choi; Alice Yuen Loke Journal: Int J Environ Res Public Health Date: 2016-10-17 Impact factor: 3.390