TY - JOUR T1 - Routinely asking patients about income in primary care: a mixed-methods study JF - BJGP Open JO - BJGP Open DO - 10.3399/BJGPO.2021.0090 SP - BJGPO.2021.0090 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 Y1 - 2022/01/12 UR - http://bjgpopen.org/content/early/2022/01/10/BJGPO.2021.0090.abstract N2 - 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 & setting Mixed-methods study in a large, multi-site primary care organisation in Toronto, Canada, where patients are asked about income in a routinely administered sociodemographic survey.Method Data were examined 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). The study compared those who responded to the income question with non-responders. Structured interviews with 27 patients were also conducted.Results A total of 10 441 (73%) patients responded to both parts of the income question: ‘What was your total family income before taxes last year?’ and ‘How many people does your income support?’. Female patients, ethnic minorities, caregivers of young children, and older people 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.Conclusion 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 help target anti-poverty interventions. ER -