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Spatial Implications Associated with Using Euclidean Distance Measurements and Geographic Centroid Imputation in Health Care Research
Author(s) -
Jones Stephen G.,
Ashby Avery J.,
Momin Soyal R.,
Naidoo Allen
Publication year - 2010
Publication title -
health services research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.706
H-Index - 121
eISSN - 1475-6773
pISSN - 0017-9124
DOI - 10.1111/j.1475-6773.2009.01044.x
Subject(s) - geocoding , centroid , euclidean distance , statistics , imputation (statistics) , geographical distance , geography , computer science , zip code , geographic information system , geographic coordinate system , distance measures , data mining , cartography , mathematics , econometrics , medicine , missing data , artificial intelligence , population , environmental health
Objective. To determine the effect of using Euclidean measurements and zip‐code centroid geo‐imputation versus more precise spatial analytical techniques in health care research. Data Sources. Commercially insured members from a southeastern managed care organization. Study Design. Distance from admitting inpatient facility to member's home and zip‐code centroid (geographic placement) was compared using Euclidean straight‐line and shortest‐path drive distances (measurement technique). Data Collection. Administrative claims from October 2005 to September 2006. Principal Findings. Measurement technique had a greater impact on distance values compared with geographic placement. Drive distance from the geocoded address was highly correlated ( r =0.99) with the Euclidean distance from the zip‐code centroid. Conclusions. Actual differences were relatively small. Researchers without capabilities to produce drive distance measurements and/or address geocoding techniques could rely on simple linear regressions to estimate correction factors with a high degree of confidence.