Identifying the Uncertainty in Physician Practice Location through Spatial Analytics and Text Mining
Xuan Shi,
Bowei Xue and
Imam M. Xierali
Additional contact information
Xuan Shi: Department of Geoscience, University of Arkansas, Fayetteville, AR 72701, USA
Bowei Xue: Department of Geoscience, University of Arkansas, Fayetteville, AR 72701, USA
Imam M. Xierali: Association of American Medical Colleges, Washington, DC 20001, USA
IJERPH, 2016, vol. 13, issue 9, 1-15
Abstract:
In response to the widespread concern about the adequacy, distribution, and disparity of access to a health care workforce, the correct identification of physicians’ practice locations is critical to access public health services. In prior literature, little effort has been made to detect and resolve the uncertainty about whether the address provided by a physician in the survey is a practice address or a home address. This paper introduces how to identify the uncertainty in a physician’s practice location through spatial analytics, text mining, and visual examination. While land use and zoning code, embedded within the parcel datasets, help to differentiate resident areas from other types, spatial analytics may have certain limitations in matching and comparing physician and parcel datasets with different uncertainty issues, which may lead to unforeseen results. Handling and matching the string components between physicians’ addresses and the addresses of the parcels could identify the spatial uncertainty and instability to derive a more reasonable relationship between different datasets. Visual analytics and examination further help to clarify the undetectable patterns. This research will have a broader impact over federal and state initiatives and policies to address both insufficiency and maldistribution of a health care workforce to improve the accessibility to public health services.
Keywords: spatial uncertainty; physician distribution; spatial analytics; text mining; visual examination (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://www.mdpi.com/1660-4601/13/9/930/pdf (application/pdf)
https://www.mdpi.com/1660-4601/13/9/930/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:13:y:2016:i:9:p:930-:d:78623
Access Statistics for this article
IJERPH is currently edited by Ms. Jenna Liu
More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().