Identifying older inpatients at high risk of unintentional medication discrepancies: a classification tree analysis

This study aimed to identify the clinical profiles of geriatric inpatients with unintentional medication discrepancies at hospital admission. A classification tree Chi-square Automatic Interaction Detector (CHAID) analysis was conducted to assess those patients' profiles and characteristics that were associated with a higher risk of unintentional medication discrepancies. One-hundred and thirty consecutive older patients admitted to acute care (87 ± 5 years old; 61.8% women) were assessed. The CHAID analysis retrieved 5 clinical profiles of older inpatients with a risk of up to 94.4% for unintentional medication discrepancies. These profiles were determined based on combinations of three characteristics: use of eye drops, frequent falls (≥ 1/year), and admission due to urgent hospitalization. These easily measurable clinical characteristics may be helpful as a supportive measure to improve pharmacological care.PMID:37943406 | DOI:10.1007/s40520-023-02598-2

Source: Aging Clinical and Experimental Research - November 9, 2023 Category: Geriatrics Authors: Mathieu Corvaisier Dolores Sanchez-Rodriguez Kevin Sautret J érémie Riou Laurence Spiesser-Robelet C édric Annweiler Source Type: research