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

BMC Medical Informatics and Decision Making

Research Article

Tyler Williamson¹  David Barber²  Rachael Morkem²  Ian Janssen³  Suzanne Biro⁴  Brian Mosley⁴  Kieran Moore⁵  Paul Belanger⁶  Jannet Ann Leggett⁷ 

[1] Department of Community Health Sciences, University of Calgary, Calgary, AB, Canada;Department of Family Medicine, Queen’s University, Kingston, ON, Canada;Department of Public Health Sciences, Queen’s University, Kingston, ON, Canada;School of Kinesiology and Health Studies, Queen’s University, Kingston, ON, Canada;Kingston, Frontenac, and Lennox & Addington Public Health, 221 Portsmouth Avenue, K7M 1V5, Kingston, ON, Canada;Kingston, Frontenac, and Lennox & Addington Public Health, 221 Portsmouth Avenue, K7M 1V5, Kingston, ON, Canada;Department of Family Medicine, Queen’s University, Kingston, ON, Canada;Kingston, Frontenac, and Lennox & Addington Public Health, 221 Portsmouth Avenue, K7M 1V5, Kingston, ON, Canada;Department of Public Health Sciences, Queen’s University, Kingston, ON, Canada;Department of Geography, Queen’s University, Kingston, ON, Canada;The College of Family Physicians of Canada, Mississauga, ON, Canada;

关键词: Socio-economic factors;    Population health;    BMI-Body Mass Index;    EMR-electronic medical record;    Obesity;    Public health;   

DOI  :  10.1186/s12911-016-0272-9

 received in 2015-12-01, accepted in 2016-03-04,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundElectronic 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.MethodsThe 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.ResultsThe 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.ConclusionsAn 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.

【 授权许可】

CC BY   
© Biro et al. 2016