ArticleBMC health services research2005
Hospital service areas -- a new tool for health care planning in Switzerland.
Article in BMC health services research, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
42 citing papers in PubMed.
- Study on edge villages based on cross-region healthcare-seeking behavior.International journal of health geographics · 2025Article
- Development and Evaluation of Pediatric Acute Care Hospital Referral Regions in Eight States.The Journal of pediatrics · 2025Article
- Article
- Article
- Mental health service areas in Switzerland.International journal of methods in psychiatric research · 2023Article
- The Swiss health care atlas-relaunch in scale.Research in health services & regions · 2023Article
- Delineating natural catchment health districts with routinely collected health data from women's travel to give birth in Ghana.BMC health services research · 2022Article
- Delineation of Cancer Service Areas Anchored by Major Cancer Centers in the United States.Cancer research communications · 2022Article
- Research on Maternal Service Area and Referral System in Hubei Province, China.International journal of environmental research and public health · 2022Article
- Creating accountable hospital service areas in China: a case analysis of health expenditure in the metropolis of Chengdu.BMJ open · 2022Article
- GIS-Automated Delineation of Hospital Service Areas in Florida: From Dartmouth Method to Network Community Detection Methods.Annals of GIS · 2022Article
- Presence of Thrombectomy-capable Stroke Centers Within Hospital Service Areas Explains Regional Variation in the Case Fatality Rate of Acute Ischemic Stroke in Korea.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2021Observational
- Regional variation of potentially avoidable hospitalisations in Switzerland: an observational study.BMC health services research · 2021Observational
- Network Optimization Approach to Delineating Health Care Service Areas: Spatially Constrained Louvain and Leiden Algorithms.Transactions in GIS : TG · 2021Article
- Automated delineation of hospital service areas as a new tool for health care planning.Health services research · 2020Article
- Automated delineation of cancer service areas in northeast region of the United States: A network optimization approach.Spatial and spatio-temporal epidemiology · 2020Article
- Article
- Regional variation in hip and knee arthroplasty rates in Switzerland: A population-based small area analysis.PloS one · 2020Article
- Teaming up census and patient data to delineate fine-scale hospital service areas and identify geographic disparities in hospital accessibility.Environmental monitoring and assessment · 2019Article
- Using Weighted Hospital Service Area Networks to Explore Variation in Preventable Hospitalization.Health services research · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe description of patient travel patterns and variations in health care utilization may guide a sound health care planning process. In order to accurately describe these differences across regions with homogeneous populations, small area analysis (SAA) has proved as a valuable tool to create appropriate area models. This paper presents the methodology to create and characterize population-based hospital service areas (HSAs) for Switzerland.
methodsWe employed federal hospital discharge data to perform a patient origin study using small area analysis. Each of 605 residential regions was assigned to one of 215 hospital provider regions where the most frequent number of discharges took place. HSAs were characterized geographically, demographically, and through health utilization indices and rates that describe hospital use. We introduced novel planning variables extracted from the patient origin study and investigated relationships among health utilization indices and rates to understand patient travel patterns for hospital use. Results were visualized as maps in a geographic information system (GIS).
resultsWe obtained 100 HSAs using a patient origin matrix containing over four million discharges. HSAs had diverse demographic and geographic characteristics. Urban HSAs had above average population sizes, while mountainous HSAs were scarcely populated but larger in size. We found higher localization of care in urban HSAs and in mountainous HSAs. Half of the Swiss population lives in service areas where 65% of hospital care is provided by local hospitals.
conclusionHealth utilization indices and rates demonstrated patient travel patterns that merit more detailed analyses in light of political, infrastructural and developmental determinants. HSAs and health utilization indices provide valuable information for health care planning. They will be used to study variation phenomena in Swiss health care.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.