The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
A three-step floating catchment area method for analyzing spatial access to health services
Abstract
Gravity-based spatial access models have been widely used to estimate spatial access to healthcare services in an attempt to capture the interaction of various factors. However, these models are inadequate in informing health resource allocation work due to their inappropriate assumption of healthcare demand. For the purpose of effective healthcare resource planning, this article proposes a three-step floating catchment area (3SFCA) method to minimize the healthcare-demand overestimation problem. Specifically, a spatial impedance-based competition scheme is incorporated into the enhanced two-step floating catchment area (E2SFCA) method to account for a reasonable model of healthcare supply and demand. A case study of spatial access to primary care physicians along the Austin–San Antonio corridor area in central Texas showed that the proposed method effectively minimizes the overestimation of healthcare demand and reflects a more balanced geographic pattern of spatial access than E2SFCA. In addition, by using an adjusted spatial access index, the 3SFCA method indicates strong potential for identifying health professional shortage areas. The study concludes that 3SFCA is a promising method to provide health professionals and decision makers with useful healthcare accessibility information.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Density Estimation for Statistics and Data Analysis
Silverman, B. W. (2018) · Routledge eBooks · doi:10.1201/9781315140919 · Cited by 15,796
Density Estimation for Statistics and Data Analysis
(1986) · Springer eBooks · doi:10.1007/978-1-4899-3324-9 · Cited by 8,525
A framework for the study of access to medical care.
(1974) · PubMed Central · Cited by 2,419
Luo, W., & Wang, F. (2003) · Environment and Planning B: Planning and Design · doi:10.1068/b29120 · Cited by 1,789
Spatial accessibility of primary care: concepts, methods and challenges
Guagliardo, M. F. (2004) · International Journal of Health Geographics · doi:10.1186/1476-072x-3-3 · Cited by 1,533
Luo, W., & Qi, Y. (2009) · Health & Place · doi:10.1016/j.healthplace.2009.06.002 · Cited by 1,220
Kwan, M. (1998) · Geographical Analysis · doi:10.1111/j.1538-4632.1998.tb00396.x · Cited by 1,156
Spatial Interaction Models:Formulations and Applications
Fotheringham, A. S., & O’Kelly, M. E. (1988) · Medical Entomology and Zoology · Cited by 731
Wang, F., & Luo, W. (2005) · Health & Place · doi:10.1016/j.healthplace.2004.02.003 · Cited by 664
Delayed Access to Health Care: Risk Factors, Reasons, and Consequences
Weissman, J. S., Stern, R., Fielding, S. L., & Epstein, A. M. (1991) · Annals of Internal Medicine · doi:10.7326/0003-4819-114-4-325 · Cited by 613
Cited by
Measuring spatial accessibility to primary health care services: Utilising dynamic catchment sizes
McGrail, M. R., & Humphreys, J. S. (2014) · Applied Geography · doi:10.1016/j.apgeog.2014.08.005 · Cited by 332
Population-based geographic access to endocrinologists in the United States, 2012
Lu, H., Holt, J. B., Cheng, Y. J., Zhang, X., Onufrak, S., & Croft, J. B. (2015) · BMC Health Services Research · doi:10.1186/s12913-015-1185-5 · Cited by 121
Higgs, G., Langford, M., & Norman, P. (2015) · Geoforum · doi:10.1016/j.geoforum.2015.04.010 · Cited by 95
Metadata
- Authors
- Wan, N., Zou, B., & Sternberg, T.
- Venue
- International Journal of Geographical Information Science
- Publisher
- Informa UK Limited
- Published
- 2012-01-03
- Volume
- 26
- Issue
- 6
- Pages
- 1073-1089
- ISSN
- 0269-3798 (ISSN-L)
- 1365-8816
- 1362-3087
- OpenAlex
- W2027468979
- Cited by
- 473
- References
- 31
- FWCI
- 15.22
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A three-step floating catchment area method for analyzing spatial access to health services. https://app.cochat.ai/papers/10.1080/13658816.2011.624987
- The paper
- Wan, N., Zou, B., & Sternberg, T. (2012). A three-step floating catchment area method for analyzing spatial access to health services. International Journal of Geographical Information Science. https://doi.org/10.1080/13658816.2011.624987
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.