Risk factors associated with unintentional medication discrepancies at admission in an internal medicine department

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

Unintentional medication discrepancies at admission are differences between the best possible medication history and the prescribed treatment at admission, and are associated with adverse outcomes, particularly in older people. 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.

[Medication reconciliation: Interests and limits]

Admission to hospital is a critical transition point for the continuity of care in medication management. Medication reconciliation can identify and resolve errors due to inaccurate medication histories. The practice of medication reconciliation is securing for the patient because of the medication errors detected with significant clinical impact. Its implementation must comply with the recommendations of the French National Authority for Health (HAS) and its deployment is now integrated into the contract for improving the quality and efficiency of care (CAQES). However, although it allows to intercept medication errors, its impact on the length of hospitalization, the rate of readmission and/or death following discharge seems limited. Given the limited human resources to carry out this time-consuming activity, patient prioritization should be considered. Studies on the fate of patients and on the medico-economic issues are also necessary in order to make this activity sustainable.

Risk factors for clinically relevant deviations in patients' medication lists reported by patients in personal health records: a prospective cohort study in a hospital setting

Background Personal health records have the potential to identify medication discrepancies. Although they facilitate patient empowerment and broad implementation of medication reconciliation, more medication discrepancies are identified through medication reconciliation performed by healthcare professionals. Aim We aimed to identify the factors associated with the occurrence of a clinically relevant deviation in a patient’s medication list based on a personal health record (used by patients) compared to medication reconciliation performed by a healthcare professional. Method Three- to 14 days prior to a planned admission to the Cardiology-, Internal Medicine- or Neurology Departments, at Amphia Hospital, Breda, the Netherlands, patients were invited to update their medication file in their personal health records. At admission, medication reconciliation was performed by a pharmacy technician. Deviations were determined as differences between these medication lists. Associations between patient-, setting-, and medication-related factors, and the occurrence of a clinically relevant deviation (National Coordinating Council for Medication Error Reporting and Prevention class \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\ge$$\end{document}≥ E) were analysed. Results Of the 488 patients approached, 155 patients were included. Twenty-four clinically relevant deviations were observed. Younger patients (adjusted odds ratio (aOR) 0.94; 95%CI:0.91–0.98), patients who used individual multi-dose packaging (aOR 14.87; 95%CI:2.02–110), and patients who used \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\ge$$\end{document}≥ 8 different medications, were at highest risk for the occurrence of a clinically relevant deviation (sensitivity 0.71; specificity 0.62; area under the curve 0.64 95%CI:0.52–0.76). Conclusion Medication reconciliation is the preferred method to identify medication discrepancies for patients with individual multi-dose packaging, and patients who used eight or more different medications.