PT - JOURNAL ARTICLE AU - Andrew David Pinto AU - Erica Shenfeld AU - Tatiana Aratangy AU - Ri Wang AU - Rosane Nisenbaum AU - Aisha Lofters AU - Gary Bloch AU - Tara Kiran TI - Routinely asking patients about income in primary care: a mixed-methods study AID - 10.3399/BJGPO.2021.0090 DP - 2021 Oct 19 TA - BJGP Open PG - BJGPO.2021.0090 4099 - http://bjgpopen.org/content/early/2021/10/19/BJGPO.2021.0090.short 4100 - http://bjgpopen.org/content/early/2021/10/19/BJGPO.2021.0090.full AB - Background Income is a key social determinant of health yet it is rare for data on income to be routinely collected and integrated with electronic health records.Aim To examine response bias and evaluate patient perspectives of being asked about income in primary care.Design and setting Mixed-methods study in a large, multi-site primary care organization in Toronto, Canada where patients are asked about income in a routinely administered sociodemographic survey.Methods We examined data from the electronic health records of patients who answered at least one question on the survey between December 2013 and March 2016 (n=14,247). We compared those who responded to the income question to non-responders. We also conducted structured interviews with 27 patients.Results 10,441 (73%) patients responded to both parts of the income question. Female patients, minorities, caregivers of young children and seniors were less likely to respond. From interviews, many patients were comfortable answering the income question, particularly if they understood the connection between income and health, and believed the data would be used to improve care. Several patients found it difficult to estimate their income or felt the options did not reflect fluctuating financial circumstances.Conclusions Many patients will provide data on income in the context of a survey in primary care, but accurately estimating income can be challenging. Future research should compare self-reported income to perceived financial strain. Data on income linked to health records can help identify health inequities and can help target anti-poverty interventions.