Kevin A Hallgren1,2, Theresa E Matson3,4, Malia Oliver4, Katie Witkiewitz5, Jennifer F Bobb4, Amy K Lee4, Ryan M Caldeiro4, Daniel Kivlahan6, Katharine A Bradley3,4,6,7. 1. Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA. khallgre@uw.edu. 2. Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA. khallgre@uw.edu. 3. Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA. 4. Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA. 5. Department of Psychology and Center on Alcohol, Substance Use, and Addictions, University of New Mexico, Albuquerque, NM, USA. 6. Center of Innovation for Veteran-Centered and Value-Driven Care, Health Services Research and Development, Veteran Affairs Puget Sound Health Care System, Seattle, WA, USA. 7. Department of Medicine, University of Washington, Seattle, WA, USA.
Abstract
BACKGROUND: Alcohol use disorder (AUD) is highly prevalent but underrecognized and undertreated in primary care settings. Alcohol Symptom Checklists can engage patients and providers in discussions of AUD-related care. However, the performance of Alcohol Symptom Checklists when they are used in routine care and documented in electronic health records (EHRs) remains unevaluated. OBJECTIVE: To evaluate the psychometric performance of an Alcohol Symptom Checklist in routine primary care. DESIGN: Cross-sectional study using item response theory (IRT) and differential item functioning analyses of measurement consistency across age, sex, race, and ethnicity. PATIENTS: Patients seen in primary care in the Kaiser Permanente Washington Healthcare System who reported high-risk drinking on the Alcohol Use Disorder Identification Test Consumption screening measure (AUDIT-C ≥ 7) and subsequently completed an Alcohol Symptom Checklist between October 2015 and February 2020. MAIN MEASURE: Alcohol Symptom Checklists with 11 items assessing AUD criteria defined in the Diagnostic and Statistical Manual for Mental Disorders, 5th edition (DSM-5), completed by patients during routine medical care and documented in EHRs. KEY RESULTS: Among 11,464 patients who screened positive for high-risk drinking and completed an Alcohol Symptom Checklist (mean age 43.6 years, 30.5% female), 54.1% reported ≥ 2 DSM-5 AUD criteria (threshold for AUD diagnosis). IRT analyses demonstrated that checklist items measured a unidimensional continuum of AUD severity. Differential item functioning was observed for some demographic subgroups but had minimal impact on accurate measurement of AUD severity, with differences between demographic subgroups attributable to differential item functioning never exceeding 0.42 points of the total symptom count (of a possible range of 0-11). CONCLUSIONS: Alcohol Symptom Checklists used in routine care discriminated AUD severity consistently with current definitions of AUD and performed equitably across age, sex, race, and ethnicity. Integrating symptom checklists into routine care may help inform clinical decision-making around diagnosing and managing AUD.
BACKGROUND: Alcohol use disorder (AUD) is highly prevalent but underrecognized and undertreated in primary care settings. Alcohol Symptom Checklists can engage patients and providers in discussions of AUD-related care. However, the performance of Alcohol Symptom Checklists when they are used in routine care and documented in electronic health records (EHRs) remains unevaluated. OBJECTIVE: To evaluate the psychometric performance of an Alcohol Symptom Checklist in routine primary care. DESIGN: Cross-sectional study using item response theory (IRT) and differential item functioning analyses of measurement consistency across age, sex, race, and ethnicity. PATIENTS: Patients seen in primary care in the Kaiser Permanente Washington Healthcare System who reported high-risk drinking on the Alcohol Use Disorder Identification Test Consumption screening measure (AUDIT-C ≥ 7) and subsequently completed an Alcohol Symptom Checklist between October 2015 and February 2020. MAIN MEASURE: Alcohol Symptom Checklists with 11 items assessing AUD criteria defined in the Diagnostic and Statistical Manual for Mental Disorders, 5th edition (DSM-5), completed by patients during routine medical care and documented in EHRs. KEY RESULTS: Among 11,464 patients who screened positive for high-risk drinking and completed an Alcohol Symptom Checklist (mean age 43.6 years, 30.5% female), 54.1% reported ≥ 2 DSM-5 AUD criteria (threshold for AUD diagnosis). IRT analyses demonstrated that checklist items measured a unidimensional continuum of AUD severity. Differential item functioning was observed for some demographic subgroups but had minimal impact on accurate measurement of AUD severity, with differences between demographic subgroups attributable to differential item functioning never exceeding 0.42 points of the total symptom count (of a possible range of 0-11). CONCLUSIONS: Alcohol Symptom Checklists used in routine care discriminated AUD severity consistently with current definitions of AUD and performed equitably across age, sex, race, and ethnicity. Integrating symptom checklists into routine care may help inform clinical decision-making around diagnosing and managing AUD.
Authors: Katharine A Bradley; Anna F DeBenedetti; Robert J Volk; Emily C Williams; Danielle Frank; Daniel R Kivlahan Journal: Alcohol Clin Exp Res Date: 2007-04-19 Impact factor: 3.455
Authors: Katharine A Bradley; Kristen R Bush; Amee J Epler; Dorcas J Dobie; Tania M Davis; Jennifer L Sporleder; Charles Maynard; Marcia L Burman; Daniel R Kivlahan Journal: Arch Intern Med Date: 2003-04-14
Authors: Mikko Sayre; Gwen T Lapham; Amy K Lee; Malia Oliver; Jennifer F Bobb; Ryan M Caldeiro; Katharine A Bradley Journal: J Gen Intern Med Date: 2020-01-23 Impact factor: 5.128
Authors: Joseph E Glass; Jennifer F Bobb; Amy K Lee; Julie E Richards; Gwen T Lapham; Evette Ludman; Carol Achtmeyer; Ryan M Caldeiro; Rebecca Parrish; Emily C Williams; Paula Lozano; Katharine A Bradley Journal: Implement Sci Date: 2018-08-06 Impact factor: 7.327
Authors: Kevin A Hallgren; Theresa E Matson; Malia Oliver; Ryan M Caldeiro; Daniel R Kivlahan; Katharine A Bradley Journal: Alcohol Clin Exp Res Date: 2022-03 Impact factor: 3.455
Authors: Emma D Ryan; Yanni M Chang; Malia Oliver; Katharine A Bradley; Kevin A Hallgren Journal: BMC Health Serv Res Date: 2022-09-05 Impact factor: 2.908