A comparison of geocoding baselayers for electronic medical record data analysis
dc.contributor.advisor | Wilson, Jeffrey S. (Jeffrey Scott), 1967- | |
dc.contributor.author | Severns, Christopher Ray | |
dc.contributor.other | Johnson, Daniel P. (Daniel Patrick), 1971- | |
dc.contributor.other | Martin, Pamela A. | |
dc.date.accessioned | 2014-01-16T15:54:36Z | |
dc.date.available | 2014-01-16T15:54:36Z | |
dc.date.issued | 2014-01-16 | |
dc.degree.date | 2013 | en_US |
dc.degree.discipline | Department of Geography | en |
dc.degree.grantor | Indiana University | en_US |
dc.degree.level | M.S. | en_US |
dc.description | Indiana University-Purdue University Indianapolis (IUPUI) | en_US |
dc.description.abstract | Identifying spatial and temporal patterns of disease occurrence by mapping the residential locations of affected people can provide information that informs response by public health practitioners and improves understanding in epidemiological research. A common method of locating patients at the individual level is geocoding residential addresses stored in electronic medical records (EMRs) using address matching procedures in a geographic information system (GIS). While the process of geocoding is becoming more common in public health studies, few researchers take the time to examine the effects of using different address databases on match rate and positional accuracy of the geocoded results. This research examined and compared accuracy and match rate resulting from four commonly-used geocoding databases applied to sample of 59,341 subjects residing in and around Marion County/ Indianapolis, IN. The results are intended to inform researchers on the benefits and downsides to their selection of a database to geocode patient addresses in EMRs. | en_US |
dc.identifier.uri | https://hdl.handle.net/1805/3841 | |
dc.identifier.uri | http://dx.doi.org/10.7912/C2/776 | |
dc.language.iso | en_US | en_US |
dc.subject | GIS | en_US |
dc.subject | Geocode | en_US |
dc.subject.lcsh | Geographic information systems -- Research -- Methodology -- Evaluation | en_US |
dc.subject.lcsh | Epidemiology -- Mathematical models -- Methodology | en_US |
dc.subject.lcsh | Geodatabases -- Research | en_US |
dc.subject.lcsh | Spatial analysis (Statistics) | en_US |
dc.subject.lcsh | Public health surveillance -- Indiana -- Statistical methods | en_US |
dc.subject.lcsh | Medical records -- Data processing -- Research -- Indiana -- Marion County | en_US |
dc.subject.lcsh | Medical records -- Data processing -- Research -- Indiana -- Indianapolis | en_US |
dc.subject.lcsh | Geographical location codes -- Data processing | en_US |
dc.subject.lcsh | Graphical user interfaces (Computer systems) -- Indiana -- Indianapolis | en_US |
dc.subject.lcsh | Graphical user interfaces (Computer systems) -- Indiana -- Marion County | en_US |
dc.subject.lcsh | Digital mapping -- Software | en_US |
dc.subject.lcsh | Indiana Network for Patient Care | en_US |
dc.subject.lcsh | Streets -- Indiana -- Indianapolis -- Maps -- Databases | en_US |
dc.subject.lcsh | Streets -- Indiana -- Marion County -- Maps -- Databases | en_US |
dc.subject.lcsh | United States. Bureau of the Census. Data User Services Division | en_US |
dc.subject.lcsh | Indianapolis (Ind.). Department of Metropolitan Development | en_US |
dc.subject.lcsh | Environmental Systems Research Institute (Redlands, Calif.) | en_US |
dc.title | A comparison of geocoding baselayers for electronic medical record data analysis | en_US |
dc.type | Thesis | en |