Utility of linking primary care electronic medical records with Canadian census data to study the determinants of chronic disease: an example based on socioeconomic status and obesity.
Background: Electronic medical records (EMRs) used in primary care contain a breadth of data that can be used in public health research. Patient data from EMRs could be linked with other data sources, such as a postal code linkage with Census data, to obtain additional information on environmental d...
| Published in: | BMC Medical Informatics & Decision Making Vol. 16; pp. 1 - 9 |
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| Main Authors: | , , , , , , , , |
| Format: | pictorial research tables/charts Journal Article |
| Published: |
BioMed Central
3/11/2016
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=113741632&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 113741632 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14726947 1CI0 jtl: BMC Medical Informatics & Decision Making issn: 14726947 maglogo: N pubinfo: dt: 3/11/2016 vid: 16 pid: 24147 pub: BioMed Central artinfo: ui: 113741632 113741632 NLM26969124 113741632 10.1186/s12911-016-0272-9 NLM26969124 PMC4788841 113741632 ppf: 1 ppct: 8 formats: tig: atl: Utility of linking primary care electronic medical records with Canadian census data to study the determinants of chronic disease: an example based on socioeconomic status and obesity. aug: au: Biro, Suzanne Williamson, Tyler Leggett, Jannet Ann Barber, David Morkem, Rachael Moore, Kieran Belanger, Paul Mosley, Brian Janssen, Ian affil: Kingston, Frontenac, and Lennox & Addington Public Health, 221 Portsmouth Avenue, Kingston, ON K7M 1V5, Canada sug: subj: Social Class Primary Health Care Statistics and Numerical Data Obesity Epidemiology Census Chronic Disease Epidemiology Medical Record Linkage Methods Pilot Studies Aged Male Middle Age Young Adult Canada Female Adult Human Aged: 65+ years Middle Aged: 45-64 years Adult: 19-44 years Male Female ab: Background: Electronic medical records (EMRs) used in primary care contain a breadth of data that can be used in public health research. Patient data from EMRs could be linked with other data sources, such as a postal code linkage with Census data, to obtain additional information on environmental determinants of health. While promising, successful linkages between primary care EMRs with geographic measures is limited due to ethics review board concerns. This study tested the feasibility of extracting full postal code from primary care EMRs and linking this with area-level measures of the environment to demonstrate how such a linkage could be used to examine the determinants of disease. The association between obesity and area-level deprivation was used as an example to illustrate inequalities of obesity in adults.Methods: The analysis included EMRs of 7153 patients aged 20 years and older who visited a single, primary care site in 2011. Extracted patient information included demographics (date of birth, sex, postal code) and weight status (height, weight). Information extraction and management procedures were designed to mitigate the risk of individual re-identification when extracting full postal code from source EMRs. Based on patients' postal codes, area-based deprivation indexes were created using the smallest area unit used in Canadian censuses. Descriptive statistics and socioeconomic disparity summary measures of linked census and adult patients were calculated.Results: The data extraction of full postal code met technological requirements for rendering health information extracted from local EMRs into anonymized data. The prevalence of obesity was 31.6 %. There was variation of obesity between deprivation quintiles; adults in the most deprived areas were 35 % more likely to be obese compared with adults in the least deprived areas (Chi-Square = 20.24(1), p < 0.0001). Maps depicting spatial representation of regional deprivation and obesity were created to highlight high risk areas.Conclusions: An area based socio-economic measure was linked with EMR-derived objective measures of height and weight to show a positive association between area-level deprivation and obesity. The linked dataset demonstrates a promising model for assessing health disparities and ecological factors associated with the development of chronic diseases with far reaching implications for informing public health and primary health care interventions and services. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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