Completeness and accuracy of anthropometric measurements in electronic medical records for children attending primary care

Sarah Carsley, Catherine Sari Birken, Patricia Parkin, Eleanor Pullenayegum, Karen Tu

Abstract


Background: Electronic medical records (EMRs) from primary care may be a feasible source of height and weight data. However the use of EMRs in research has been impeded by lack of standardization of EMRs systems, data access and concerns about the quality of the data.

Objectives: The study objectives were to determine the data completeness and accuracy of child heights and weights collected in primary care EMRs, and to identify factors associated with these data quality attributes.

Methods: A cross-sectional study examining height and weight data for children <19 years from EMRs through the Electronic Medical Records Administrative data Linked Database (EMRALD), a network of family practices across the province of Ontario. Body mass index z-scores were calculated using the WHO Growth Standards and Reference.

Results: A total of 54,964 children were identified from EMRALD. Overall, 93% had at least 1 complete set of growth measurements to calculate a BMI z-score. 66.2% of all primary care visits had complete BMI z-score data. After stratifying by visit type 89.9% of well-child visits and 33.9% of sick visits had complete BMI z-score data; incomplete BMI z-score was mainly due to missing height measurements. Only 2.7% of BMI z-score data were excluded due to implausible values.

Conclusions: Data completeness at well-child visits and overall data accuracy were greater than 90%. EMRs may be a valid source of data to provide estimates of obesity in children who attend primary care.

Keywords


Electronic Health Records; Child; Body Mass Index; Data Accuracy; Obesity

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References


Collier R. National physician survey: EMR use at 75%. Canadian Medical Association Journal de l’Association Medicale Canadienne 2015;187(1):E17–18.

Terry AL, Stewart M, Fortin M, Wong ST, Kennedy M, Burge F, et al. How does Canada stack up? A bibliometric analysis of the primary healthcare electronic medical record literature. Informatics in Primary Care 2012;20(4):233–40. Available from: https://doi.org/10.14236/jhi.v20i4.2. PMid:23890334.

Guttman A, Schultz SE and Jaakkimainen L. Primary Care for Children. Toronto, ON: Institute for Clinical Evaluative Sciences, 2006.

Woo Baidal JA, Locks LM, Cheng ER, Blake-Lamb TL, Perkins ME and Taveras EM. Risk factors for childhood obesity in the first 1,000 days: a systematic review. American Journal of Preventive Medicine 2016;50(6):761–79. doi: 710.1016/j.amepre.2015.1011.1012. Epub 2016 Feb 1022.

Greig A, Constantin E, Carsley S and Cummings C. Preventive health care visits for children and adolescents aged six to 17 years: The Greig Health Record – Executive Summary. Paediatrics & Child Health 2010;15(3):157–62. Available from: https://doi.org/10.1093/pch/15.3.157. PMid:21358896; PMCid:PMC2865953.

Rourke L, Leduc D, Constantin E, Carsley S and Rourke J. Update on well-baby and well-child care from 0 to 5 years: What’s new in the Rourke Baby Record? Canadian Family Physician 2010;56(12):1285–90. PMid:21156890; PMCid:PMC3001919.

Wood GC, Chu X, Manney C, Strodel W, Petrick A, Gabrielsen J, et al. An electronic health record-enabled obesity database. BMC Medical Informatics and Decision Making 2012;12:45. Available from: https://doi.org/10.1186/1472-6947-12-45. PMid:22640398; PMCid:PMC3508953.

Healthy Kids Panel. No Time to Wait: The Healthy Kids Strategy. Toronto, ON: Ministry of Health and Long-Term Care, 2013.

Greenhalgh T, Potts HW, Wong G, Bark P and Swinglehurst D. Tensions and paradoxes in electronic patient record research: a systematic literature review using the meta-narrative method. Milbank Quarterly 2009;87(4):729–88. Available from: https://doi.org/10.1111/j.1468-0009.2009.00578.x. PMid:20021585; PMCid:PMC2888022.

Jensen RE, Chan KS, Weiner JP, Fowles JB and Neale SM. Implementing electronic health record-based quality measures for developmental screening. Pediatrics 2009;124(4):e648–54. Available from: https://doi.org/10.1542/peds.2008-3091. PMid:19786425.

Keshavjee K, Williamson T, Martin K, Truant R, Aliarzadeh B, Ghany A, et al. Getting to usable EMR data. Canadian Family Physician 2014;60(4):392. PMid:24733333; PMCid:PMC4046531.

Tu K, Widdifield J, Young J, Oud W, Ivers NM, Butt DA, et al. Are family physicians comprehensively using electronic medical records such that the data can be used for secondary purposes? A Canadian perspective. BMC Medical Informatics and Decision Making 2015;15:67. Available from: https://doi.org/10.1186/s12911-015-0195-x. PMid:26268511; PMCid:PMC4535372.

Biro S, Williamson T, Leggett JA, Barber D, Morkem R, Moore K, et al. 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 2016;16:32. doi: 10.1186/s12911-12016-10272-12919.

Rigobon AV, Birtwhistle R, Khan S, Barber D, Biro S, Morkem R, et al. Adult obesity prevalence in primary care users: an exploration using Canadian Primary Care Sentinel Surveillance Network (CPCSSN) data. Canadian Journal of Public Health 2015;106(5):e283–89. doi: 210.17269/cjph.17106.14508.

Birken CS, Tu K, Oud W, Carsley S, Hanna M, Lebovic G, et al. Determining rates of overweight and obese status in children using electronic medical records: cross-sectional study. Canadian Family Physician 2017;63(2):e114–22. PMid:28209703; PMCid:PMC5395409.

Lawman HG, Ogden CL, Hassink S, Mallya G, Vander Veur S and Foster GD. Comparing methods for identifying biologically implausible values in height, weight, and body mass index among youth. American Journal of Epidemiology 2015;182(4):359–65. Available from: https://doi.org/10.1093/aje/kwv057. PMid:26182944; PMCid:PMC4528955.

Tu K, Mitiku TF, Ivers NM, Guo H, Lu H, Jaakkimainen L, et al. Evaluation of Electronic Medical Record Administrative data Linked Database (EMRALD). The American Journal of Managed Care 2014;20(1):e15–21. PMid:24669409.

OntarioMD. Core EMR specifications, 2015. Available from: https://www.ontariomd.ca/portal/server.pt/community/ontario_emr_specifications/current_emr_specifications/. Accessed 31 January 2017.

Smith N, Coleman KJ, Lawrence JM, Quinn VP, Getahun D, Reynolds K, et al. Body weight and height data in electronic medical records of children. International Journal of Pediatric Obesity: An Official Journal of the International Association for the Study of Obesity 2010;5(3):237–42.

Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organization Technical Teport Series 1995;854:1–452. PMid:8594834.

WHO. AnthroPlus for Personal Computers Manual: Software for Assessing Growth of the World’s Children and Adolescents. Geneva, Switzerland: WHO, 2009. Available from: http://www.who.int/growthref/tools/readme_sas.pdf?ua=1. Accessed 31 March 2016.

Lo JC, Maring B, Chandra M, Daniels SR, Sinaiko A and Daley MF. Prevalence of obesity and extreme obesity in children aged 3–5 years. Pediatric Obesity 2014;9(3):167–75. Available from: https://doi.org/10.1111/j.2047-6310.2013.00154.x. PMid:23677690; PMCid:PMC3830709.

Guttmann A, Manuel D, Dick PT, To T, Lam K and Stukel TA. Volume matters: physician practice characteristics and immunization coverage among young children insured through a universal health plan. Pediatrics 2006;117(3):595–602. Available from: https://doi.org/10.1542/peds.2004-2784. PMid:16510636.

Snijders TA and Bosker RJ. Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling, 2nd edition. Los Angeles, CA: Sage, 2012.

Estabrooks PA and Shetterly S. The prevalence and health care use of overweight children in an integrated health care system. Archives of Pediatrics & Adolescent Medicine 2007;161(3):222–7. Available from: https://doi.org/10.1001/archpedi.161.3.222. PMid:17339502.

Wood AJ, Raynes-Greenow CH, Carberry AE and Jeffery HE. Neonatal length inaccuracies in clinical practice and related percentile discrepancies detected by a simple length-board. Journal of Paediatrics and Child Health 2013;49(3):199–203. Available from: https://doi.org/10.1111/jpc.12119. PMid:23432733.

Canadian Task Force on Preventive Health Care. Recommendations for growth monitoring, and prevention and management of overweight and obesity in children and youth in primary care. Canadian Medical Association Journal 2015;187(6):411–21.

Nader PR, O’Brien M, Houts R, Bradley R, Belsky J, Crosnoe R, et al. Identifying risk for obesity in early childhood. Pediatrics 2006;118(3):e594–601. Available from: https://doi.org/10.1542/peds.2005-2801. PMid:16950951.

Ratcliff MB, Jenkins TM, Reiter-Purtill J, Noll JG and Zeller MH. Risk-taking behaviors of adolescents with extreme obesity: normative or not? Pediatrics 2011;127(5):827–34. Available from: https://doi.org/10.1542/peds.2010-2742.

Freedman DS, Lawman HG, Pan L, Skinner AC, Allison D, McGuire LC, et al. The prevalence and validity of high, biologically implausible values of weight, height, and BMI among 8.8 million children. Obesity 2016;24(5):1132–9. Available from: https://doi.org/10.1002/oby.21446. PMid:26991694; PMCid:PMC4846478.

CDC. A SAS Program for the 2000 CDC Growth Charts (ages 0 to <20 years). Available from: https://www.cdc.gov/nccdphp/dnpao/growthcharts/resources/sas.htm. Accessed 31 January 2017.

Zemel BS. A commentary on the construction of weight velocity charts. Nutrition in Clinical Practice: Official Publication of the American Society for Parenteral and Enteral Nutrition 2009;24(5):651–53.




DOI: http://dx.doi.org/10.14236/jhi.v25i1.963

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