• Kyle G Steiger, Kasey R Boehmer, Molly C Klanderman, Aamena Mookadam, Sethu Sandeep Koneru, Victor M Montori, and Martina Mookadam.
• From the Mayo Clinic Alix School of Medicine, Mayo Clinic College of Medicine and Science, Scottsdale (KGS); Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota (KRB, VMM); Division of Health Care Delivery Research, Mayo Clinic, Rochester, Minnesota (KRB); Department of Quantitative Health Sciences, Mayo Clinic, Scottsdale, Arizona (MCK); Mayo Clinic, Scottsdale, Arizona (AM, SSK); Department of Family Medicine, Mayo Clinic, Scottsdale, Arizona (MM); Arizona State University, Tempe (AM).
• J Am Board Fam Med. 2023 Apr 3; 36 (2): 277288277-288.

ObjectiveTo create a model based on patients' characteristics that can predict the number of burdens reported using the ICAN Discussion Aid, to target use of this tool to patients likeliest to benefit.Patients And MethodsSix hundred thirty-five patients (aged ≥18 years) completed the ICAN Discussion Aid at a Scottsdale, Arizona, family medicine clinic. Patient characteristics were gathered from their health records. Regression trees with Poisson splitting criteria were used to model the data.ResultsOur model suggests the patients with the most burdens had major depressive disorder, with twice as many overall burdens (personal plus health care burdens) than patients without depression. Patients with depression who were younger than 38 years had the highest number of personal burdens. A body mass index (BMI) of 26 or greater was associated with increased health care burden versus a BMI below 26.ConclusionThe number of burdens a patient will report on the ICAN Discussion Aid can be approximated based on certain patient characteristics. Adults with major depression, a BMI of 26 or greater, and younger age may have greater reported burdens on ICAN, but this finding needs to be validated in independent samples.© Copyright by the American Board of Family Medicine.

21 keywords...

hide…