Geographic Discordance Between Patient Residence and Incident Location in Emergency Medical Services Responses

Study objective The location of a patient’s residence is often used for emergency medical services (EMS) system planning. Our objective is to evaluate the association between patient residence and emergency incident zip codes for 911 calls. Methods We used data from the 2013 National Emergency Medic...

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Veröffentlicht in:Annals of emergency medicine 2017-01, Vol.69 (1), p.44-51.e3
Hauptverfasser: Hsia, Renee Y., MD, MSc, Dai, Mengtao, MS, Wei, Ran, PhD, Sabbagh, Sarah, MPH, Mann, N. Clay, PhD, MS
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container_end_page 51.e3
container_issue 1
container_start_page 44
container_title Annals of emergency medicine
container_volume 69
creator Hsia, Renee Y., MD, MSc
Dai, Mengtao, MS
Wei, Ran, PhD
Sabbagh, Sarah, MPH
Mann, N. Clay, PhD, MS
description Study objective The location of a patient’s residence is often used for emergency medical services (EMS) system planning. Our objective is to evaluate the association between patient residence and emergency incident zip codes for 911 calls. Methods We used data from the 2013 National Emergency Medical Services Information System (NEMSIS) Public-Release Research Dataset. We studied all 911 calls with a valid complaint by dispatch, identifying zip codes for both the residence and incident locations (n=12,376,784). The primary outcomes were geographic and distance discordances between patient residence and incident zip codes. We used a multivariate logistic regression model to determine geographic discordance between residence and incident zip codes by dispatch complaint, age, and sex. We also measured distances between locations with geospatial processing. Results The overall proportion of geographic discordance for all 911 calls was 27.7% (95% confidence interval [CI] 27.7% to 27.8%) and the median distance discordance was 11.5 miles (95% CI 11.5 to 11.5 miles). Lower geographic discordance rates were found among patients aged 65 to 79 years (20.2%; 95% CI 20.1% to 20.2%) and 80 years and older (14.5%; 95% CI 14.5% to 14.6%). Motor vehicle crashes (63.5%; 95% CI 63.5% to 63.6%), industrial accidents (59.3%; 95% CI 58.0% to 60.6%), and mass casualty incidents (50.6%; 95% CI 49.6% to 51.5%) were more likely to occur outside a patient’s residence zip code. Median network distance between home and incident zip centroid codes ranged from 8.6 to 23.5 miles. Conclusion In NEMSIS, there was geographic discordance between patient residence zip code and call location zip code in slightly more than one quarter of EMS responses records. The geographic discordance rates between residence and incident zip codes were associated with dispatch complaints and age. Although a patient’s residence might be a valid proxy for incident location for elderly patients, this relationship holds less true for other age groups and among different complaints. Our findings have important implications for EMS system planning, resource allocation, and injury surveillance.
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Clay, PhD, MS</creator><creatorcontrib>Hsia, Renee Y., MD, MSc ; Dai, Mengtao, MS ; Wei, Ran, PhD ; Sabbagh, Sarah, MPH ; Mann, N. Clay, PhD, MS</creatorcontrib><description>Study objective The location of a patient’s residence is often used for emergency medical services (EMS) system planning. Our objective is to evaluate the association between patient residence and emergency incident zip codes for 911 calls. Methods We used data from the 2013 National Emergency Medical Services Information System (NEMSIS) Public-Release Research Dataset. We studied all 911 calls with a valid complaint by dispatch, identifying zip codes for both the residence and incident locations (n=12,376,784). The primary outcomes were geographic and distance discordances between patient residence and incident zip codes. We used a multivariate logistic regression model to determine geographic discordance between residence and incident zip codes by dispatch complaint, age, and sex. We also measured distances between locations with geospatial processing. Results The overall proportion of geographic discordance for all 911 calls was 27.7% (95% confidence interval [CI] 27.7% to 27.8%) and the median distance discordance was 11.5 miles (95% CI 11.5 to 11.5 miles). Lower geographic discordance rates were found among patients aged 65 to 79 years (20.2%; 95% CI 20.1% to 20.2%) and 80 years and older (14.5%; 95% CI 14.5% to 14.6%). Motor vehicle crashes (63.5%; 95% CI 63.5% to 63.6%), industrial accidents (59.3%; 95% CI 58.0% to 60.6%), and mass casualty incidents (50.6%; 95% CI 49.6% to 51.5%) were more likely to occur outside a patient’s residence zip code. Median network distance between home and incident zip centroid codes ranged from 8.6 to 23.5 miles. Conclusion In NEMSIS, there was geographic discordance between patient residence zip code and call location zip code in slightly more than one quarter of EMS responses records. The geographic discordance rates between residence and incident zip codes were associated with dispatch complaints and age. Although a patient’s residence might be a valid proxy for incident location for elderly patients, this relationship holds less true for other age groups and among different complaints. Our findings have important implications for EMS system planning, resource allocation, and injury surveillance.</description><identifier>ISSN: 0196-0644</identifier><identifier>EISSN: 1097-6760</identifier><identifier>DOI: 10.1016/j.annemergmed.2016.05.025</identifier><identifier>PMID: 27497673</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Accidents - statistics &amp; numerical data ; Adolescent ; Adult ; Age Factors ; Aged ; Aged, 80 and over ; Child ; Child, Preschool ; Emergencies ; Emergency ; Emergency Medical Services - statistics &amp; numerical data ; Female ; Geography ; Humans ; Infant ; Infant, Newborn ; Male ; Mass Casualty Incidents - statistics &amp; numerical data ; Middle Aged ; Residence Characteristics - statistics &amp; numerical data ; Sex Factors ; United States ; Young Adult</subject><ispartof>Annals of emergency medicine, 2017-01, Vol.69 (1), p.44-51.e3</ispartof><rights>American College of Emergency Physicians</rights><rights>2016 American College of Emergency Physicians</rights><rights>Copyright © 2016 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c498t-6072fba740a43cfd06240a88203460b0be99163851fb32b2dea757d0f3de98af3</citedby><cites>FETCH-LOGICAL-c498t-6072fba740a43cfd06240a88203460b0be99163851fb32b2dea757d0f3de98af3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.annemergmed.2016.05.025$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,778,782,3539,27907,27908,45978</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27497673$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hsia, Renee Y., MD, MSc</creatorcontrib><creatorcontrib>Dai, Mengtao, MS</creatorcontrib><creatorcontrib>Wei, Ran, PhD</creatorcontrib><creatorcontrib>Sabbagh, Sarah, MPH</creatorcontrib><creatorcontrib>Mann, N. Clay, PhD, MS</creatorcontrib><title>Geographic Discordance Between Patient Residence and Incident Location in Emergency Medical Services Responses</title><title>Annals of emergency medicine</title><addtitle>Ann Emerg Med</addtitle><description>Study objective The location of a patient’s residence is often used for emergency medical services (EMS) system planning. Our objective is to evaluate the association between patient residence and emergency incident zip codes for 911 calls. Methods We used data from the 2013 National Emergency Medical Services Information System (NEMSIS) Public-Release Research Dataset. We studied all 911 calls with a valid complaint by dispatch, identifying zip codes for both the residence and incident locations (n=12,376,784). The primary outcomes were geographic and distance discordances between patient residence and incident zip codes. We used a multivariate logistic regression model to determine geographic discordance between residence and incident zip codes by dispatch complaint, age, and sex. We also measured distances between locations with geospatial processing. Results The overall proportion of geographic discordance for all 911 calls was 27.7% (95% confidence interval [CI] 27.7% to 27.8%) and the median distance discordance was 11.5 miles (95% CI 11.5 to 11.5 miles). Lower geographic discordance rates were found among patients aged 65 to 79 years (20.2%; 95% CI 20.1% to 20.2%) and 80 years and older (14.5%; 95% CI 14.5% to 14.6%). Motor vehicle crashes (63.5%; 95% CI 63.5% to 63.6%), industrial accidents (59.3%; 95% CI 58.0% to 60.6%), and mass casualty incidents (50.6%; 95% CI 49.6% to 51.5%) were more likely to occur outside a patient’s residence zip code. Median network distance between home and incident zip centroid codes ranged from 8.6 to 23.5 miles. Conclusion In NEMSIS, there was geographic discordance between patient residence zip code and call location zip code in slightly more than one quarter of EMS responses records. The geographic discordance rates between residence and incident zip codes were associated with dispatch complaints and age. Although a patient’s residence might be a valid proxy for incident location for elderly patients, this relationship holds less true for other age groups and among different complaints. Our findings have important implications for EMS system planning, resource allocation, and injury surveillance.</description><subject>Accidents - statistics &amp; numerical data</subject><subject>Adolescent</subject><subject>Adult</subject><subject>Age Factors</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Emergencies</subject><subject>Emergency</subject><subject>Emergency Medical Services - statistics &amp; numerical data</subject><subject>Female</subject><subject>Geography</subject><subject>Humans</subject><subject>Infant</subject><subject>Infant, Newborn</subject><subject>Male</subject><subject>Mass Casualty Incidents - statistics &amp; numerical data</subject><subject>Middle Aged</subject><subject>Residence Characteristics - statistics &amp; numerical data</subject><subject>Sex Factors</subject><subject>United States</subject><subject>Young Adult</subject><issn>0196-0644</issn><issn>1097-6760</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkcFu1DAQhiMEokvhFZC5cUkYO4kdX5BgKaXSIhCFs-XYk-Ila2_tbNG-Pba2lRAnTrZn_n_G801VvaLQUKD8zbbR3uMO480ObcNyqIG-AdY_qlYUpKi54PC4WgGVvAbedWfVs5S2ACA7Rp9WZ0x0UnDRrip_ieEm6v1PZ8gHl0yIVnuD5D0uvxE9-aoXh34h3zA5iyWjvSVX3pTXQjbBZEHwxHlyUT6UJUfyGa0zeibXGO-cwVTc--ATpufVk0nPCV_cn-fVj48X39ef6s2Xy6v1u01tOjksNQfBplGLDnTXmskCZ_k6DAzajsMII0pJeTv0dBpbNjKLWvTCwtRalIOe2vPq9anuPobbA6ZF7fJwOM_aYzgkRbOVcSHkkKXyJDUxpBRxUvvodjoeFQVVcKut-gu3KrgV9Crjzt6X920OY8k9OB_4ZsH6JMA87J3DqJJxBaN1Ec2ibHD_1ebtP1XM7HxB_AuPmLbhEH2mqahKTIG6Lnsva8-IgEEP7R9bKqzQ</recordid><startdate>20170101</startdate><enddate>20170101</enddate><creator>Hsia, Renee Y., MD, MSc</creator><creator>Dai, Mengtao, MS</creator><creator>Wei, Ran, PhD</creator><creator>Sabbagh, Sarah, MPH</creator><creator>Mann, N. 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Clay, PhD, MS</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c498t-6072fba740a43cfd06240a88203460b0be99163851fb32b2dea757d0f3de98af3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Accidents - statistics &amp; numerical data</topic><topic>Adolescent</topic><topic>Adult</topic><topic>Age Factors</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>Emergencies</topic><topic>Emergency</topic><topic>Emergency Medical Services - statistics &amp; numerical data</topic><topic>Female</topic><topic>Geography</topic><topic>Humans</topic><topic>Infant</topic><topic>Infant, Newborn</topic><topic>Male</topic><topic>Mass Casualty Incidents - statistics &amp; numerical data</topic><topic>Middle Aged</topic><topic>Residence Characteristics - statistics &amp; numerical data</topic><topic>Sex Factors</topic><topic>United States</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hsia, Renee Y., MD, MSc</creatorcontrib><creatorcontrib>Dai, Mengtao, MS</creatorcontrib><creatorcontrib>Wei, Ran, PhD</creatorcontrib><creatorcontrib>Sabbagh, Sarah, MPH</creatorcontrib><creatorcontrib>Mann, N. Clay, PhD, MS</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Annals of emergency medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hsia, Renee Y., MD, MSc</au><au>Dai, Mengtao, MS</au><au>Wei, Ran, PhD</au><au>Sabbagh, Sarah, MPH</au><au>Mann, N. Clay, PhD, MS</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Geographic Discordance Between Patient Residence and Incident Location in Emergency Medical Services Responses</atitle><jtitle>Annals of emergency medicine</jtitle><addtitle>Ann Emerg Med</addtitle><date>2017-01-01</date><risdate>2017</risdate><volume>69</volume><issue>1</issue><spage>44</spage><epage>51.e3</epage><pages>44-51.e3</pages><issn>0196-0644</issn><eissn>1097-6760</eissn><abstract>Study objective The location of a patient’s residence is often used for emergency medical services (EMS) system planning. Our objective is to evaluate the association between patient residence and emergency incident zip codes for 911 calls. Methods We used data from the 2013 National Emergency Medical Services Information System (NEMSIS) Public-Release Research Dataset. We studied all 911 calls with a valid complaint by dispatch, identifying zip codes for both the residence and incident locations (n=12,376,784). The primary outcomes were geographic and distance discordances between patient residence and incident zip codes. We used a multivariate logistic regression model to determine geographic discordance between residence and incident zip codes by dispatch complaint, age, and sex. We also measured distances between locations with geospatial processing. Results The overall proportion of geographic discordance for all 911 calls was 27.7% (95% confidence interval [CI] 27.7% to 27.8%) and the median distance discordance was 11.5 miles (95% CI 11.5 to 11.5 miles). Lower geographic discordance rates were found among patients aged 65 to 79 years (20.2%; 95% CI 20.1% to 20.2%) and 80 years and older (14.5%; 95% CI 14.5% to 14.6%). Motor vehicle crashes (63.5%; 95% CI 63.5% to 63.6%), industrial accidents (59.3%; 95% CI 58.0% to 60.6%), and mass casualty incidents (50.6%; 95% CI 49.6% to 51.5%) were more likely to occur outside a patient’s residence zip code. Median network distance between home and incident zip centroid codes ranged from 8.6 to 23.5 miles. Conclusion In NEMSIS, there was geographic discordance between patient residence zip code and call location zip code in slightly more than one quarter of EMS responses records. The geographic discordance rates between residence and incident zip codes were associated with dispatch complaints and age. Although a patient’s residence might be a valid proxy for incident location for elderly patients, this relationship holds less true for other age groups and among different complaints. Our findings have important implications for EMS system planning, resource allocation, and injury surveillance.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>27497673</pmid><doi>10.1016/j.annemergmed.2016.05.025</doi></addata></record>
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subjects Accidents - statistics & numerical data
Adolescent
Adult
Age Factors
Aged
Aged, 80 and over
Child
Child, Preschool
Emergencies
Emergency
Emergency Medical Services - statistics & numerical data
Female
Geography
Humans
Infant
Infant, Newborn
Male
Mass Casualty Incidents - statistics & numerical data
Middle Aged
Residence Characteristics - statistics & numerical data
Sex Factors
United States
Young Adult
title Geographic Discordance Between Patient Residence and Incident Location in Emergency Medical Services Responses
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