Non-response Bias in Social Risk Factor Screening Among Adult Emergency Department Patients

• Published in: Journal of medical systems Vol. 47; no. 1; p. 78
• Main Authors: Vest, Joshua R, Mazurenko, Olena
• Format: Journal Article
• Language: English
• Published: New York Springer US 22.07.2023; Springer Nature B.V
• Subjects: Adolescent; Adult; Documentation; Emergency medical care; Emergency medical services; Emergency response; Emergency Service, Hospital; Health Informatics; Health Sciences; Humans; Language; Logistic Models; Medicine; Medicine & Public Health; Natural Language Processing; Original Paper; Patients; Questionnaires; Regression analysis; Regression models; Response bias; Risk factors; Social factors; Statistical analysis; Statistics for Life Sciences; Surveys; Social determinants of health; Emergency department; Bias
• ISSN: 1573-689X; 0148-5598; 1573-689X
• DOI: 10.1007/s10916-023-01975-8

Healthcare organizations increasingly use screening questionnaires to assess patients’ social factors, but non-response may contribute to selection bias. This study assessed differences between respondents and those refusing participation in a social factor screening. We used a cross-sectional approach with logistic regression models to measure the association between subject characteristics and social factor screening questionnaire participation. The study subjects were patients from a mid-western state safety-net hospital’s emergency department. Subjects’ inclusion criteria were: (1) ≥ 18 years old, (2) spoke English or Spanish, and (3) able to complete a self-administered questionnaire. We classified subjects that consented and answered the screening questionnaire in full as respondents. All others were non-respondents. Using natural language processing, we linked all subjects’ participation status to demographic characteristics, clinical data, an area-level deprivation measure, and social risk factors extracted from clinical notes. We found that nearly 6 out of every 10 subjects approached (59.9%), consented, and completed the questionnaire. Subjects with prior documentation of financial insecurity were 22% less likely to respond to the screening questionnaire (marginal effect = -22.40; 95% confidence interval (CI) = -41.16, -3.63; p = 0.019). No other factors were significantly associated with response. This study uniquely contributes to the growing social determinants of health literature by confirming that selection bias may exist within social factor screening practices and research studies.