Prompt Pediatric Care Pediatric patients’ estimated travel times to surgically-equipped hospitals in Sweden’s Scania County

Abstract: Health and emergency services aim to provide patients with urgent care according to an accessibility policy that is characterized by “proper service at the proper time and place” (Jordan et al. 2004; Murad 2007). Network analysis using geographical information system (GIS) applications has frequently been used in healthcare planning to investigate a population's accessibility to professional care, e.g. how easy or difficult is it for members of the population to reach a hospital. This network analysis has been conducted to investigate the distribution of possible pediatric patients (children age 0-18) per surgical hospital and these patients’ estimated travel times to the nearest hospital within the county of Scania, Sweden by utilizing data that has been collected per Small Area for Market Statistics (SAMS) in Scania, Sweden. A methodology for the implementation of data from Sweden’s national road database (Nationell vägdatabas, NVDB) is presented as well as a statistical analysis of each surgical hospital’s catchment (i.e. the total area served by each surgical hospital). The results show that only a relatively small number of children (10,537 or 4%) reside in underserved SAMS associated with travel times of 30 minutes or more to the nearest surgical hospital. In addition, there were large differences in the number of children potentially served by each hospital. Adult residents residing within the catchments of the different surgical hospitals did not differ from each other significantly on attributes such as level of education, purchasing power or median income, as the variability among residents within each catchment was very large. This study revealed some interesting information, but also had several important limitations due to the assumptions made when modeling. The travel time estimated from SAMS with a smaller area to the nearest hospital was generally representative for all patients residing in that particular SAMS. However, the locational sensitivity analysis showed that the travel time estimate was less generally reliable for all residents within larger, rural SAMS, where the population-weighted centroid was less reliable since dwellings were more sparse and further apart. Nevertheless, the results herein may prove helpful in planning and improving healthcare in Scania. This study may also prove helpful as part of a more thorough investigation of socioeconomic factors that may affect where, when, why and how various pediatric patients in Scania seek medical care.