Mary M Orr, Adolfo L Molina, Cassandra N Smola, Samantha L Hanna, Ariel E Carpenter, Chang L Wu
{"title":"Disparities and Biases in Food Insecurity Screening Among Admitted Children.","authors":"Mary M Orr, Adolfo L Molina, Cassandra N Smola, Samantha L Hanna, Ariel E Carpenter, Chang L Wu","doi":"10.1542/hpeds.2023-007602","DOIUrl":null,"url":null,"abstract":"<p><strong>Background and objectives: </strong>Food insecurity (FI) has increasingly become a focus for hospitalized patients. The best methods for screening practices, particularly in hospitalized children, are unknown. The purpose of the study was to evaluate results of an electronic medical record (EMR) embedded, brief screening tool for FI among inpatients.</p><p><strong>Methods: </strong>This was a cross-sectional study from August 2020 to September 2022 for all children admitted to a quaternary children's hospital. Primary outcomes were proportion of those screened for FI and those identified to have a positive screen. FI was evaluated by The Hunger Vital Sign, a validated 2-question screen verbally obtained in the nursing intake form in the EMR. Covariates include demographic variables of age, sex, race, ethnicity, primary language, and insurance. Statistical analyses including all univariate outcome and bivariate comparisons were performed with SAS 9.4.</p><p><strong>Results: </strong>There were 31 553 patient encounters with 81.7% screened for FI. Patients had a median age of 6.3 years, were mostly male (54.2%), White (60.6%), non-Hispanic (92.7%), English-speaking (94.3%), and had government insurance (79.8%). Younger (0-2 years), non-White, and noninsured patients were all screened significantly less often for FI (all P < .001). A total of 3.4% were identified as having FI. Patients who were older, non-White, Hispanic, non-English speaking, and had nonprivate insurance had higher FI (all P < .001).</p><p><strong>Conclusions: </strong>Despite the use of an EMR screening tool intended to be universal, we found variation in how we screen for FI. At times, we missed those who would benefit the most from intervention, and thus it may be subject to implementation bias.</p>","PeriodicalId":38180,"journal":{"name":"Hospital pediatrics","volume":" ","pages":"e304-e307"},"PeriodicalIF":0.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hospital pediatrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1542/hpeds.2023-007602","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Nursing","Score":null,"Total":0}
引用次数: 0
Abstract
Background and objectives: Food insecurity (FI) has increasingly become a focus for hospitalized patients. The best methods for screening practices, particularly in hospitalized children, are unknown. The purpose of the study was to evaluate results of an electronic medical record (EMR) embedded, brief screening tool for FI among inpatients.
Methods: This was a cross-sectional study from August 2020 to September 2022 for all children admitted to a quaternary children's hospital. Primary outcomes were proportion of those screened for FI and those identified to have a positive screen. FI was evaluated by The Hunger Vital Sign, a validated 2-question screen verbally obtained in the nursing intake form in the EMR. Covariates include demographic variables of age, sex, race, ethnicity, primary language, and insurance. Statistical analyses including all univariate outcome and bivariate comparisons were performed with SAS 9.4.
Results: There were 31 553 patient encounters with 81.7% screened for FI. Patients had a median age of 6.3 years, were mostly male (54.2%), White (60.6%), non-Hispanic (92.7%), English-speaking (94.3%), and had government insurance (79.8%). Younger (0-2 years), non-White, and noninsured patients were all screened significantly less often for FI (all P < .001). A total of 3.4% were identified as having FI. Patients who were older, non-White, Hispanic, non-English speaking, and had nonprivate insurance had higher FI (all P < .001).
Conclusions: Despite the use of an EMR screening tool intended to be universal, we found variation in how we screen for FI. At times, we missed those who would benefit the most from intervention, and thus it may be subject to implementation bias.