2017
DOI: 10.1186/s12913-017-2280-6
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Time series modelling to forecast prehospital EMS demand for diabetic emergencies

Abstract: BackgroundAcute diabetic emergencies are often managed by prehospital Emergency Medical Services (EMS). The projected growth in prevalence of diabetes is likely to result in rising demand for prehospital EMS that are already under pressure. The aims of this study were to model the temporal trends and provide forecasts of prehospital attendances for diabetic emergencies.MethodsA time series analysis on monthly cases of hypoglycemia and hyperglycemia was conducted using data from the Ambulance Victoria (AV) elec… Show more

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Cited by 30 publications
(15 citation statements)
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“…In addition, literature analysis shows that males and older people more often use medical services which are a part of the medical emergency systems worldwide, as confirmed by Villani et al and Hawkes et al [24,25].…”
Section: Discussionmentioning
confidence: 83%
“…In addition, literature analysis shows that males and older people more often use medical services which are a part of the medical emergency systems worldwide, as confirmed by Villani et al and Hawkes et al [24,25].…”
Section: Discussionmentioning
confidence: 83%
“…Access to age-stratified data of the Victorian diabetic population for the study period was not available, thus precluding an age-adjusted rate ratio calculation. However, it is thought that the unadjusted and age-adjusted rate ratio would not differ substantially given the demographic changes during the study period were minimal [ 30 ]. In addition, DKA cases were not able to be distinguished from uncomplicated hyperglycaemia as ketone testing was not part of routine assessment.…”
Section: Discussionmentioning
confidence: 99%
“…Next, we estimate the future health stock by using an econometric method. To forecast health stock, we applied ARIMA because it is commonly and widely used in a time series analysis [16, 2527]. The ARIMA model also has the ability to use non-stationary time-series data, and many researchers use this model to forecast various health and medical phenomena [28].…”
Section: Methodsmentioning
confidence: 99%