Identifying rural–urban differences in the predictors of emergency ambulance service demand and misuse
Journal
Journal of the Formosan Medical Association
Journal Volume
118
Journal Issue
1P2
Pages
324-331
Date Issued
2019
Author(s)
Abstract
Objective: This study aims to assess rural–urban differences in the predictors of emergency ambulance service (EAS) demand and misuse in New Taipei City. Identifying the predictors of EAS demand will help the EAS service managing authority in formulating focused policies to maintain service quality. Methods: Over 160,000 electronic EAS usage records were used with a negative binomial regression model to assess rural–urban differences in the predictors of EAS demand and misuse. Results: The factors of 1) ln-transformed population density, 2) percentage of residents who completed up to junior high school education, 3) accessibility of hospitals without an emergency room, and 4) accessibility of EAS were found to be predictors of EAS demand in rural areas, whereas only the factor of percentage of people aged above 65 was found to predict EAS demand in urban areas. For EAS misuse, only the factor of percentage of low-income households was found to be a predictor in rural areas, whereas no predictor was found in the urban areas. Conclusion: Results showed that the factors predicting EAS demand and misuse in rural areas were more complicated compared to urban areas and, therefore, formulating EAS policies for rural areas based on the results of urban studies may not be appropriate. ? 2018
Subjects
Emergency ambulance service; Geographic information system; Misuse; Planning; Rural–urban difference
SDGs
Other Subjects
adult; ambulance; article; emergency ward; female; geographic information system; high school; household; human; human experiment; lowest income group; male; population density; resident; rural area; urban area; ambulance; clinical trial; comparative study; emergency health service; health care delivery; health service; multicenter study; prognosis; rural population; statistical model; statistics and numerical data; Taiwan; urban population; Ambulances; Emergency Medical Services; Health Services Accessibility; Health Services Misuse; Humans; Linear Models; Prognosis; Rural Population; Taiwan; Urban Population
Type
journal article