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.
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.
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