Geospatial Monitoring of Body Mass Index: Use of Electronic Health Record Data Across Health Care Systems
Objectives: The Colorado BMI Monitoring System was developed to assess geographic (ie, census tract) patterns of obesity prevalence rates among children and adults in the Denver-metropolitan region. This project also sought to assess the feasibility of a surveillance system that integrates data acro...
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Veröffentlicht in: | Public health reports (1974) 2020-03, Vol.135 (2), p.211-219 |
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container_title | Public health reports (1974) |
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creator | Anthamatten, Peter Thomas, Deborah S.K. Williford, Devon Barrow, Jennifer C. Bol, Kirk A. Davidson, Arthur J. Davies, Sara J. Deakyne Kraus, Emily McCormick Tabano, David C. Daley, Matthew F. |
description | Objectives:
The Colorado BMI Monitoring System was developed to assess geographic (ie, census tract) patterns of obesity prevalence rates among children and adults in the Denver-metropolitan region. This project also sought to assess the feasibility of a surveillance system that integrates data across multiple health care and governmental organizations.
Materials and Methods:
We extracted data on height and weight measures, obtained through routine clinical care, from electronic health records (EHRs) at multiple health care sites. We selected sites from 5 Denver health care systems and collected data from visits that occurred between January 1, 2013, and December 31, 2015. We produced shaded maps showing observed obesity prevalence rates by census tract for various geographic regions across the Denver-metropolitan region.
Results:
We identified clearly distinguishable areas by higher rates of obesity among children than among adults, with several pockets of lower body mass index. Patterns for adults were similar to patterns for children: the highest obesity prevalence rates were concentrated around the central part of the metropolitan region. Obesity prevalence rates were moderately higher along the western and northern areas than in other parts of the study region.
Practice Implications:
The Colorado BMI Monitoring System demonstrates the feasibility of combining EHRs across multiple systems for public health and research. Challenges include ensuring de-duplication across organizations and ensuring that geocoding is performed in a consistent way that does not pose a risk for patient privacy. |
doi_str_mv | 10.1177/0033354920904078 |
format | Article |
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The Colorado BMI Monitoring System was developed to assess geographic (ie, census tract) patterns of obesity prevalence rates among children and adults in the Denver-metropolitan region. This project also sought to assess the feasibility of a surveillance system that integrates data across multiple health care and governmental organizations.
Materials and Methods:
We extracted data on height and weight measures, obtained through routine clinical care, from electronic health records (EHRs) at multiple health care sites. We selected sites from 5 Denver health care systems and collected data from visits that occurred between January 1, 2013, and December 31, 2015. We produced shaded maps showing observed obesity prevalence rates by census tract for various geographic regions across the Denver-metropolitan region.
Results:
We identified clearly distinguishable areas by higher rates of obesity among children than among adults, with several pockets of lower body mass index. Patterns for adults were similar to patterns for children: the highest obesity prevalence rates were concentrated around the central part of the metropolitan region. Obesity prevalence rates were moderately higher along the western and northern areas than in other parts of the study region.
Practice Implications:
The Colorado BMI Monitoring System demonstrates the feasibility of combining EHRs across multiple systems for public health and research. Challenges include ensuring de-duplication across organizations and ensuring that geocoding is performed in a consistent way that does not pose a risk for patient privacy.</description><identifier>ISSN: 0033-3549</identifier><identifier>EISSN: 1468-2877</identifier><identifier>DOI: 10.1177/0033354920904078</identifier><identifier>PMID: 32053469</identifier><language>eng</language><publisher>Los Angeles, CA: Sage Publications, Inc</publisher><subject>Adolescent ; Adult ; Adults ; Body Mass Index ; Body size ; Census ; Censuses ; Child ; Child, Preschool ; Children ; Colorado - epidemiology ; Data ; Data collection ; Electronic Health Records ; Electronic medical records ; Feasibility studies ; Female ; Geographic Information Systems ; Health care ; Health services ; Humans ; Indexes ; Male ; Medical records ; Metropolitan areas ; Monitoring systems ; Obesity ; Obesity - epidemiology ; Organizations ; Population Surveillance - methods ; Privacy ; Public health ; Public Health Methodology ; Regions ; Surveillance ; Urban Population - statistics & numerical data</subject><ispartof>Public health reports (1974), 2020-03, Vol.135 (2), p.211-219</ispartof><rights>2020, Association of Schools and Programs of Public Health</rights><rights>2020, Association of Schools and Programs of Public Health 2020 US Surgeon General’s Office</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c484t-602c097dc988d7941e4e853b6b4ff9b1850cbd0ccedef49cd8876c5bc7e07d913</citedby><cites>FETCH-LOGICAL-c484t-602c097dc988d7941e4e853b6b4ff9b1850cbd0ccedef49cd8876c5bc7e07d913</cites><orcidid>0000-0003-4413-9381</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/26990687$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/26990687$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,723,776,780,799,881,21798,27843,27901,27902,43597,43598,53766,53768,57992,58225</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32053469$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Anthamatten, Peter</creatorcontrib><creatorcontrib>Thomas, Deborah S.K.</creatorcontrib><creatorcontrib>Williford, Devon</creatorcontrib><creatorcontrib>Barrow, Jennifer C.</creatorcontrib><creatorcontrib>Bol, Kirk A.</creatorcontrib><creatorcontrib>Davidson, Arthur J.</creatorcontrib><creatorcontrib>Davies, Sara J. Deakyne</creatorcontrib><creatorcontrib>Kraus, Emily McCormick</creatorcontrib><creatorcontrib>Tabano, David C.</creatorcontrib><creatorcontrib>Daley, Matthew F.</creatorcontrib><title>Geospatial Monitoring of Body Mass Index: Use of Electronic Health Record Data Across Health Care Systems</title><title>Public health reports (1974)</title><addtitle>Public Health Rep</addtitle><description>Objectives:
The Colorado BMI Monitoring System was developed to assess geographic (ie, census tract) patterns of obesity prevalence rates among children and adults in the Denver-metropolitan region. This project also sought to assess the feasibility of a surveillance system that integrates data across multiple health care and governmental organizations.
Materials and Methods:
We extracted data on height and weight measures, obtained through routine clinical care, from electronic health records (EHRs) at multiple health care sites. We selected sites from 5 Denver health care systems and collected data from visits that occurred between January 1, 2013, and December 31, 2015. We produced shaded maps showing observed obesity prevalence rates by census tract for various geographic regions across the Denver-metropolitan region.
Results:
We identified clearly distinguishable areas by higher rates of obesity among children than among adults, with several pockets of lower body mass index. Patterns for adults were similar to patterns for children: the highest obesity prevalence rates were concentrated around the central part of the metropolitan region. Obesity prevalence rates were moderately higher along the western and northern areas than in other parts of the study region.
Practice Implications:
The Colorado BMI Monitoring System demonstrates the feasibility of combining EHRs across multiple systems for public health and research. Challenges include ensuring de-duplication across organizations and ensuring that geocoding is performed in a consistent way that does not pose a risk for patient privacy.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Adults</subject><subject>Body Mass Index</subject><subject>Body size</subject><subject>Census</subject><subject>Censuses</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Children</subject><subject>Colorado - epidemiology</subject><subject>Data</subject><subject>Data collection</subject><subject>Electronic Health Records</subject><subject>Electronic medical records</subject><subject>Feasibility studies</subject><subject>Female</subject><subject>Geographic Information Systems</subject><subject>Health care</subject><subject>Health services</subject><subject>Humans</subject><subject>Indexes</subject><subject>Male</subject><subject>Medical records</subject><subject>Metropolitan areas</subject><subject>Monitoring systems</subject><subject>Obesity</subject><subject>Obesity - epidemiology</subject><subject>Organizations</subject><subject>Population Surveillance - methods</subject><subject>Privacy</subject><subject>Public health</subject><subject>Public Health Methodology</subject><subject>Regions</subject><subject>Surveillance</subject><subject>Urban Population - statistics & numerical data</subject><issn>0033-3549</issn><issn>1468-2877</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>7TQ</sourceid><recordid>eNp9kL1PwzAQxS0EoqWws4AisbAEzrHjjwUJKiiVWrHAbDm2U1K1cYlTRP97XLWUj4Fbbnjv3t39EDrFcIUx59cAhJCcygwkUOBiD3UxZSLNBOf7qLuW07XeQUchTCFWhskh6pAMckKZ7KLLgfNhodtKz5Kxr6vWN1U9SXyZ3Hm7SsY6hGRYW_dxjA5KPQvuZNt76OXh_rn_mI6eBsP-7Sg1VNA2ZZAZkNwaKYTlkmJHnchJwQpalrLAIgdTWDDGWVdSaawQnJm8MNwBtxKTHrrZ5C6WxdxZ4-q20TO1aKq5blbK60r9VurqVU38u-JAGItv9dDFNqDxb0sXWjX1y6aON6uMsIiA5YJEF2xcpvEhNK7cbcCg1mzVX7Zx5PznZbuBL5jRkG4MQU_c99Z_As82_mmI2Hd5GZMSmODkE-pYifs</recordid><startdate>20200301</startdate><enddate>20200301</enddate><creator>Anthamatten, Peter</creator><creator>Thomas, Deborah S.K.</creator><creator>Williford, Devon</creator><creator>Barrow, Jennifer C.</creator><creator>Bol, Kirk A.</creator><creator>Davidson, Arthur J.</creator><creator>Davies, Sara J. Deakyne</creator><creator>Kraus, Emily McCormick</creator><creator>Tabano, David C.</creator><creator>Daley, Matthew F.</creator><general>Sage Publications, Inc</general><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TQ</scope><scope>ASE</scope><scope>DHY</scope><scope>DON</scope><scope>FPQ</scope><scope>K6X</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-4413-9381</orcidid></search><sort><creationdate>20200301</creationdate><title>Geospatial Monitoring of Body Mass Index</title><author>Anthamatten, Peter ; Thomas, Deborah S.K. ; Williford, Devon ; Barrow, Jennifer C. ; Bol, Kirk A. ; Davidson, Arthur J. ; Davies, Sara J. Deakyne ; Kraus, Emily McCormick ; Tabano, David C. ; Daley, Matthew F.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c484t-602c097dc988d7941e4e853b6b4ff9b1850cbd0ccedef49cd8876c5bc7e07d913</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Adults</topic><topic>Body Mass Index</topic><topic>Body size</topic><topic>Census</topic><topic>Censuses</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>Children</topic><topic>Colorado - epidemiology</topic><topic>Data</topic><topic>Data collection</topic><topic>Electronic Health Records</topic><topic>Electronic medical records</topic><topic>Feasibility studies</topic><topic>Female</topic><topic>Geographic Information Systems</topic><topic>Health care</topic><topic>Health services</topic><topic>Humans</topic><topic>Indexes</topic><topic>Male</topic><topic>Medical records</topic><topic>Metropolitan areas</topic><topic>Monitoring systems</topic><topic>Obesity</topic><topic>Obesity - epidemiology</topic><topic>Organizations</topic><topic>Population Surveillance - methods</topic><topic>Privacy</topic><topic>Public health</topic><topic>Public Health Methodology</topic><topic>Regions</topic><topic>Surveillance</topic><topic>Urban Population - statistics & numerical data</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Anthamatten, Peter</creatorcontrib><creatorcontrib>Thomas, Deborah S.K.</creatorcontrib><creatorcontrib>Williford, Devon</creatorcontrib><creatorcontrib>Barrow, Jennifer C.</creatorcontrib><creatorcontrib>Bol, Kirk A.</creatorcontrib><creatorcontrib>Davidson, Arthur J.</creatorcontrib><creatorcontrib>Davies, Sara J. Deakyne</creatorcontrib><creatorcontrib>Kraus, Emily McCormick</creatorcontrib><creatorcontrib>Tabano, David C.</creatorcontrib><creatorcontrib>Daley, Matthew F.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>PAIS Index</collection><collection>British Nursing Index</collection><collection>PAIS International</collection><collection>PAIS International (Ovid)</collection><collection>British Nursing Index (BNI) (1985 to Present)</collection><collection>British Nursing Index</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Public health reports (1974)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Anthamatten, Peter</au><au>Thomas, Deborah S.K.</au><au>Williford, Devon</au><au>Barrow, Jennifer C.</au><au>Bol, Kirk A.</au><au>Davidson, Arthur J.</au><au>Davies, Sara J. Deakyne</au><au>Kraus, Emily McCormick</au><au>Tabano, David C.</au><au>Daley, Matthew F.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Geospatial Monitoring of Body Mass Index: Use of Electronic Health Record Data Across Health Care Systems</atitle><jtitle>Public health reports (1974)</jtitle><addtitle>Public Health Rep</addtitle><date>2020-03-01</date><risdate>2020</risdate><volume>135</volume><issue>2</issue><spage>211</spage><epage>219</epage><pages>211-219</pages><issn>0033-3549</issn><eissn>1468-2877</eissn><abstract>Objectives:
The Colorado BMI Monitoring System was developed to assess geographic (ie, census tract) patterns of obesity prevalence rates among children and adults in the Denver-metropolitan region. This project also sought to assess the feasibility of a surveillance system that integrates data across multiple health care and governmental organizations.
Materials and Methods:
We extracted data on height and weight measures, obtained through routine clinical care, from electronic health records (EHRs) at multiple health care sites. We selected sites from 5 Denver health care systems and collected data from visits that occurred between January 1, 2013, and December 31, 2015. We produced shaded maps showing observed obesity prevalence rates by census tract for various geographic regions across the Denver-metropolitan region.
Results:
We identified clearly distinguishable areas by higher rates of obesity among children than among adults, with several pockets of lower body mass index. Patterns for adults were similar to patterns for children: the highest obesity prevalence rates were concentrated around the central part of the metropolitan region. Obesity prevalence rates were moderately higher along the western and northern areas than in other parts of the study region.
Practice Implications:
The Colorado BMI Monitoring System demonstrates the feasibility of combining EHRs across multiple systems for public health and research. Challenges include ensuring de-duplication across organizations and ensuring that geocoding is performed in a consistent way that does not pose a risk for patient privacy.</abstract><cop>Los Angeles, CA</cop><pub>Sage Publications, Inc</pub><pmid>32053469</pmid><doi>10.1177/0033354920904078</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0003-4413-9381</orcidid><oa>free_for_read</oa></addata></record> |
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source | SAGE Complete A-Z List; Jstor Complete Legacy; MEDLINE; PAIS Index; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Alma/SFX Local Collection |
subjects | Adolescent Adult Adults Body Mass Index Body size Census Censuses Child Child, Preschool Children Colorado - epidemiology Data Data collection Electronic Health Records Electronic medical records Feasibility studies Female Geographic Information Systems Health care Health services Humans Indexes Male Medical records Metropolitan areas Monitoring systems Obesity Obesity - epidemiology Organizations Population Surveillance - methods Privacy Public health Public Health Methodology Regions Surveillance Urban Population - statistics & numerical data |
title | Geospatial Monitoring of Body Mass Index: Use of Electronic Health Record Data Across Health Care Systems |
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