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

Näslund, Chloe LU (2016) In Student thesis series INES NGEK01 20161
Dept of Physical Geography and Ecosystem Science
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... (More)
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. (Less)
Popular Abstract (Swedish)
Nätverksanalys med hjälp av GIS applikationer har ofta använts inom sjukvården för att planera och undersöka en populations tillgång till professionell vård. I detta kandidatarbete har en nätverksanalys genomförts för att beräkna dem kortaste färdvägarna från varje demografisk avgränsat område (”Small Area for Market Statistics” eller SAMS) inom Skåne län till det närmaste kirurgiska sjukhuset för att undersöka fördelningen av barn (i åldern 0-18) per kirurgisk sjukhus upptagningsområde. En nätverksanalysmetod, med användning av data från Sveriges nationella vägdatabas (NVDB), presenteras liksom en statistisk analys per upptagningsområde för varje kirurgisk sjukhus. Resultaten visar att endast ett relativt lågt antal barn (10.537 eller 4%)... (More)
Nätverksanalys med hjälp av GIS applikationer har ofta använts inom sjukvården för att planera och undersöka en populations tillgång till professionell vård. I detta kandidatarbete har en nätverksanalys genomförts för att beräkna dem kortaste färdvägarna från varje demografisk avgränsat område (”Small Area for Market Statistics” eller SAMS) inom Skåne län till det närmaste kirurgiska sjukhuset för att undersöka fördelningen av barn (i åldern 0-18) per kirurgisk sjukhus upptagningsområde. En nätverksanalysmetod, med användning av data från Sveriges nationella vägdatabas (NVDB), presenteras liksom en statistisk analys per upptagningsområde för varje kirurgisk sjukhus. Resultaten visar att endast ett relativt lågt antal barn (10.537 eller 4%) bor i SAMS med restider på 30 minuter eller längre till närmaste kirurgiska sjukhus. Det finns också stora skillnader i antalet barn potentiellt försedda av varje sjukhus. Universitetssjukhuset i Malmö omfattar det största antalet potentiella pediatriska patienter (81,750 barn eller 28% av alla skånska barn i åldern 0-18) medan Trelleborg sjukhus täcker det minsta antalet barn (14.075), vilket motsvarar endast 5% av befolkningen 0 -18 år i Skåne. De olika sjukhusupptagningsområden skiljer sig inte från varandra väsentligt på egenskaper såsom vuxen utbildningsnivå, köpkraft eller medianinkomsten eftersom variabiliteten i varje upptagningsområde var mycket stor. Denna studie pekade på vissa intressanta resultat, men hade också flera viktiga begränsningar på grund av de antaganden som görs vid modellering. Restiden beräknad från en viss SAMS till närmaste sjukhus var generellt representativt för alla patienter som bor i till arean mindre SAMS. Lokaliseringskänslighetsanalyen visade dock att den uppskattade restiden var mindre generellt tillförlitlig för alla invånare inom större, rurala SAMS, där befolknings vägda mittpunkten var mindre tillförlitlig eftersom befolkning bor glesare och längre ifrån varandra. Ändå kan resultaten härifrån vara till hjälp i planeringen och att förbättra sjukvården i Skåne. Denna studie kan också vara till hjälp som en del av en mer grundlig undersökning av socioekonomiska faktorer som kan påverka var, när, varför och hur olika pediatriska patienter i Skåne söker vård. (Less)
Please use this url to cite or link to this publication:
author
Näslund, Chloe LU
supervisor
organization
alternative title
Tillgång till skyndsam barnhälsovård : pediatriska patienters beräknade körtider till kirurgiskt utrustade sjukhus i Skåne län
course
NGEK01 20161
year
type
M2 - Bachelor Degree
subject
keywords
health planning, hospitals, shortest route, GIS, pediatric surgery, network analysis, accessibility, healthcare, travel time, Scania, Physical Geography and Ecosystem Science
publication/series
Student thesis series INES
report number
386
language
English
id
8883078
date added to LUP
2016-07-06 19:25:50
date last changed
2016-07-06 19:25:50
@misc{8883078,
  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.},
  author       = {Näslund, Chloe},
  keyword      = {health planning,hospitals,shortest route,GIS,pediatric surgery,network analysis,accessibility,healthcare,travel time,Scania,Physical Geography and Ecosystem Science},
  language     = {eng},
  note         = {Student Paper},
  series       = {Student thesis series INES},
  title        = {Prompt Pediatric Care Pediatric patients’ estimated travel times to surgically-equipped hospitals in Sweden’s Scania County},
  year         = {2016},
}