Francis Lau PhD, FCAHS, Professor
School of Health Information Science, University of Victoria
fylau@uvic.ca @francislau1 #HealthTerminologyStandards #CCHIMCTSS #HINF
The impact of social determinants of health (SDH) on the health of Canadians is well documented [1,2], yet few health organizations routinely collect SDH and related interventions in electronic health records (EHRs) [3]. Even for those wanting to collect such data, there is no common SDH terminology or implementation guidance in place to ensure the data are encoded consistently with the same meaning across systems [4]. Different SDH factors and related interventions have been reported in the Canadian literature, such as the use of PROGRESS as an equity lens from the University of Ottawa [5] and the stratifiers for measuring health inequity from the Canadian Institute for Health Information [6]. These variations are largely driven by local contexts, priorities, and available resources to address SDH-related needs.
In the United States, the PRAPARE (Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences) initiative is a national effort to assist health organizations with collecting the data needed to better understand and act on patients’ SDH [7]. The initiative has created a suite of resources that includes a set of core and optional SDH measures, an action toolkit, training materials, studies underway, and lessons learned. For SDH terminology, Arons has examined coding schemes for 20 SDH domains in six published assessment tools and found 1,095 existing screening, assessment/diagnosis, and treatment/intervention codes that can be used to document SDH-related activities [8,9]. In Canada, a similar initiative led by Dr. Andrew Pinto et al. is underway to reduce inequities through the routine collection of SDH in primary care with promising results [10]. Outstanding work ahead includes reaching consensus on the SDH measures, terminology and coding schemes for the EHRs, how the SDH-related information is used, and the extent to which patients’ voices are represented. Having standardized SDH terminology will enable the collection, use, and exchange of SDH information across EHRs and organizations. Canada needs to increase the capacity of HIM professionals knowledgeable in health terminology standards.
References
[1] Public Health Agency of Canada. Key Health Inequalities in Canada– A National Portrait. 2018.
[2] Toronto Public Health, St. Michael’s, CAMH and Mount Sinai Hospital. We ask because we care: The Tri-Hospital + TPH Health Equity Data Collection Research Project Report, 2013. Available from http://www.stmichaelshospital.com/quality/equity-data-collection-report.pdf
[3] Venzon A, Le TB & Kim K. Capturing social health data in electronic systems –a systematic review. CIN: Computers, Informatics, Nursing 2019;37(2):90-8.
[4] Freij M, Dullabh P, Lewis S, Smith S, Hovey L & Dhopeshwarkar R. Incorporating social determinants of health in electronic health records: qualitative study of current practices among top vendors. JMIR Medical Informatics 2019;7(2):e13849.
[5] O’Neill J, Tabish H, Welch V, Petticrew M, Pottie K, Clarke M, et al. Applying an equity lens to interventions: using PROGRESS ensures consideration of socially stratifying factors to illuminate inequities in health. Journal of Clinical Epidemiology 2014; 67:56-64.
[6] Canadian Institute for Health Information. In Pursuit of Health Equity: Defining Stratifiers for Measuring Health Inequity. April 2018.
[7] National Association of Community Health Centers. PRAPARE – Protocol for Responding to and Assessing Patients’ Asses, Risks and Experiences. [Internet]. Bethesda (MD): NACHC; c 2018 [cited 2018 Feb 5]. Available from: http://www.nachc.org/research-and-data/prapare/
[8] Arons A, DeSilvey S, Fichtenberg C & Gottlieb L. Documenting social determinants of health-related clinical activities using standardized medical vocabularies. JAMIA 2019; 2(1):81-8.
[9] Arons A, DeSilvey S, Fichtenberg C & Gottlieb L. Compendium of Medical Terminology Codes for Social Risk Factors [Internet], 2018. Available from https://sirenetwork.ucsf.edu/tools-resources/mmi/compendium-medical-terminology-codes-social-risk-factors
[10] Pinto AD, Glattstein-YG, Mohamed A, Bloch G, Leung FH & Glazier RH. Building a foundation to reduce health inequities: routine collection of sociodemographic data in primary care. Journal of American Board of Family Medicine 2016; 29(3):348-55.