"Doctor, would it surprise you if there were prescribing errors in this patient's medication?" Identifying eligible patients for in-hospital pharmacotherapeutic stewardship: A matched case-control study.
Rashudy F Mahomedradja, Birgit I Lissenberg-Witte, Kim C E Sigaloff, Jelle Tichelaar, Michiel A van Agtmael
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引用次数: 0
Abstract
Background: Evaluating a patient's medication list is critical to reduce prescribing errors (PEs), but is a labour- and time-intensive process. Identification of patients at risk of PEs could improve the allocation of scarce time and resources, but currently available prediction tools are not effective.
Objective: To investigate whether ward doctors can identify patients at risk of PEs.
Methods: This prospective matched case-control study was conducted on three clinical wards in an academic hospital. Otolaryngology and oncology ward doctors used clinical intuition to select patients requiring a clinical medication review (CMR) (cases). These patients were then matched 1:1 on age (±10 years) and number (±1) of prescriptions with patients not selected for CMRs on the internal medicine and upper gastrointestinal surgery ward (controls). A multidisciplinary in-hospital pharmacotherapeutic stewardship team assessed the prevalence of PEs.
Results: A total of 387 patients with 5191 prescriptions were included. Overall, 799 PEs affecting 279 patients (72.1%) were identified. Most PEs (58.8%) occurred during hospitalization. There were no significant differences in age, number of prescriptions, sex, renal function or documented allergies or intolerances between the cases and controls or between controls and other patients who did not receive a CMR. The incidence of PEs was higher in cases than in controls (97.5% vs 72.5%, odds ratio = 14.8, 95% confidence interval [CI] 1.8-121.1, P = .002)). The rate of PEs was three times higher in cases than in controls (incidence rate ratio = 3.0, 95% CI 2.3-4.0, P < .001).
Conclusions: Ward doctors can effectively identify patients with PEs, and thus at risk of medication-related harm, using clinical intuition.