Using self-reported data on the social determinants of health in primary care to identify cancer screening disparities: opportunities and challenges

Abstract

BackgroundData on the social determinants of health can help primary care practices target improvement efforts, yet relevant data are rarely available. Our family practice located in Toronto, Ontario routinely collects patient-level sociodemographic data via a pilot-tested survey developed by a multi-organizational steering committee. We sought to use these data to assess the relationship between the social determinants and colorectal, cervical and breast cancer screening, and to describe the opportunities and challenges of using data on social determinants from a self-administered patient survey.MethodsPatients of the family practice eligible for at least one of the three cancer screening types, based on age and screening guidelines as of June 30, 2015 and who had answered at least one question on a socio-demographic survey were included in the study. We linked self-reported data from the sociodemographic survey conducted in the waiting room with patients’ electronic medical record data and cancer screening records. We created an individual-level income variable (low-income cut-off) that defined a poverty threshold and took household size into account. The sociodemographic characteristics of patients who were overdue for screening were compared to those who were up-to-date for screening for each cancer type using chi-squared tests.ResultsWe analysed data for 5766 patients for whom we had survey data. Survey participants had significantly higher screening rates (72.9, 78.7, 74.4% for colorectal, cervical and breast cancer screening respectively) than the 13, 036 patients for whom we did not have survey data (59.2, 65.3, 58.9% respectively). Foreign-born patients were significantly more likely to be up-to-date on colorectal screening than their Canadian-born peers but showed no significant differences in breast or cervical cancer screening. We found a significant association between the low-income cut-off variable and cancer screening; neighbourhood income quintile was not significantly associated with cancer screening. Housing status was also significantly associated with colorectal, cervical and breast cancer screening. There was a large amount of missing data for the low-income cut-off variable, approximately 25% across the three cohorts.ConclusionWhile we were able to show that neighbourhood income might under-estimate income-related disparities in screening, individual-level income was also the most challenging variable to collect. Future work in this area should target the income disparity in cancer screening and simultaneously explore how best to collect measures of poverty.Electronic supplementary materialThe online version of this article (doi:10.1186/s12875-017-0599-z) contains supplementary material, which is available to authorized users.

Mailed Letter Versus Phone Call to Increase Uptake of Cancer Screening: A Pragmatic, Randomized Trial

“…We identified potentially eligible patients as of March 31, 2015 using data from a provincial registry and our practice EMR as described previously. 12,15 Eligibility determination was consistent with provincial guidelines. 16 Women aged 21 to 69 years and 50 to 74 years were eligible for cervical and breast cancer screening, respectively.…”

Toward Understanding the Value of Missing Social Determinants of Health Data in Care Transition Planning

“…6 Even with self-reported data, up to 25% of some SDH variables can be missing for some cohorts. 20 Widespread missing data may artificially create more variation in the revisit estimates. 21 To alleviate this problem during statistical analysis, many researchers exclude SDH variables with high levels of missingness, 6,20,21 use multiple imputation mechanisms, 8,22 or use other weighting procedures.…”

“…20 Widespread missing data may artificially create more variation in the revisit estimates. 21 To alleviate this problem during statistical analysis, many researchers exclude SDH variables with high levels of missingness, 6,20,21 use multiple imputation mechanisms, 8,22 or use other weighting procedures. 23 While these methods are sound, there is a need to gather a more relevant SDH history on patients to understand the significance of SDH across the care continuum, including transitioning to care at home.…”

Meaningful Information in the Age of Big Data: A Scoping Review on Social Determinants of Health Data Collection for Electronic Health Records

“…Decisions around which data to collect are determined by the priorities, and subsequent informational needs, of the health system in question. For example, considerable research is devoted to which data are necessary to improve care continuity and chance of recovery(24), reduce rate of readmission(32), or improve population rates of participation preventative practices(6). The landscape of SDOH metrics and valid associations therefore changes across environments based on situated needs.…”

“…One of the two articles from Canadian study sites provides an example of how regional information management contexts influence SDOH screening. The authors stated that their survey design did not initially follow the principles of Ownership, Control, Access, and Possession (OCAP®), which governs research concerning Canada's Indigenous populations(38), and thus influenced how the authors reported study findings(6). This observation points to the need for additional research on contextually driven data collection methods, as well as further investigation into how recommendations from leading health organizations (e.g.…”