Optimisation of medication reconciliation using queueing theory: a computer experiment.

BACKGROUND: Medication reconciliation (MedRec) in hospitals is an important tool to enhance the continuity of care, but completing MedRec is challenging. AIM: The aim of this study was to investigate whether queueing theory could be used to compare various interventions to optimise the MedRec process to ultimately reduce the number of patients discharged prior to MedRec being completed. Queueing theory, the mathematical study of waiting lines or queues, has not been previously applied in hospital pharmacies but enables comparisons without interfering with the baseline workflow. METHOD: Possible interventions to enhance the MedRec process (replacing in-person conversations with telephone conversations, reallocating pharmacy technicians (PTs) or adjusting their working schedule) were compared in a computer experiment. The primary outcome was the percentage of patients with an incomplete discharge MedRec. Due to the COVID-19 pandemic, it was possible to add a real-life post hoc intervention (PTs starting their shift later) to the theoretical interventions. Descriptive analysis was performed. RESULTS: The queueing model showed that the number of patients with an incomplete discharge MedRec decreased from 37.2% in the original scenario to approximately 16% when the PTs started their shift 2 h earlier and 1 PT was reassigned to prepare the discharge MedRec. The number increased with the real-life post hoc intervention (PTs starting later), which matches a decrease in the computer experiment when started earlier. CONCLUSION: Using queueing theory in a computer experiment could identify the most promising theoretical intervention to decrease the percentage of patients discharged prior to MedRec being completed.

Effect of medication reconciliation on patient reported potential adverse events after hospital discharge.

BACKGROUND: Although medication reconciliation (MedRec) is effective in decreasing medication discrepancies, the effectiveness on Adverse Events (AEs) is very scarce. The objective of this study was to assess the effect of MedRec by a pharmacy team on patient-reported, potential AEs post-discharge. METHODS: This was a multicenter prospective intervention study with before-after design at two Dutch hospitals. Participants were patients aged ≥18 years admitted for more than 48 h using three or more prescription medications upon discharge. Patients in the control group received usual care. In the intervention period, a trained team of pharmacy staff executed medication reconciliation consisting of patient education upon admission and discharge, review of prescribed medication to identify errors, and information transfer to primary care. To address the primary outcome, the difference in proportion of patients with one or more potential AEs was measured by a structured telephone interview, two weeks after discharge between usual care and intervention group. To address the second outcome, the difference in median number of potential AEs per patient was calculated. Other outcomes assessed included the association between the intervention and patient characteristics. RESULTS: In total, 221 (138 usual care and 83 intervention) patients were included. The proportion of control and intervention patients with AEs was 88.4% and 86.7% respectively (p > 0.05). The median number of potential AEs per patient was lower in the intervention group compared with usual care (1.1 vs. 2.1, p < 0.0001). Being in the intervention arm was associated with less potential AEs (RR 0.5, 95% CI [0.4-0.6]), whereas being previously admitted was associated with a higher number of potential AEs (RR 1.3, 95% CI [1.1-1.5]). The effect of the intervention on the number of potential AE was stronger among women compared with men (p = 0.04). CONCLUSION: Although the intervention did not decrease the proportion of patients with AEs, a significant reduction in the median number of potential AEs after hospital discharge between the intervention and usual care group was observed.

Correction to: Towards a patient journey perspective on causes of unplanned readmissions using a classification framework: results of a systematic review with narrative synthesis.

Due to an error introduced during copyediting of this article [1], following corrections need to be made.

Towards a patient journey perspective on causes of unplanned readmissions using a classification framework: results of a systematic review with narrative synthesis.

BACKGROUND: Several literature reviews have been published focusing on the prevalence and/or preventability of hospital readmissions. To our knowledge, none focused on the different causes which have been used to evaluate the preventability of readmissions. Insight into the range of causes is crucial to understand the complex nature of readmissions. We conducted a systematic review to: (1) evaluate the range of causes of unplanned readmissions in a patient journey, and (2) present a cause classification framework that can support future readmission studies. METHODS: A literature search was conducted in PUBMED and EMBASE using "readmission" and "avoidability" or "preventability" as key terms. Studies that specified causes of unplanned readmissions were included. The causes were classified into eight preliminary root causes: Technical, Organization (integrated care), Organization (hospital department level), Human (care provider), Human (informal caregiver), Patient (self-management), Patient (disease), and Other. The root causes were based on expert opinions and the root cause analysis tool of PRISMA (Prevention and Recovery Information System for Monitoring and Analysis). The range of different causes were analyzed using Microsoft Excel. RESULTS: Forty-five studies that reported 381 causes of readmissions were included. All studies reported causes related to organization of care at the hospital department level. These causes were often reported as preventable. Twenty-two studies included causes related to patient's self-management and 19 studies reported causes related to patient's disease. Studies differed in which causes were seen as preventable or unpreventable. None reported causes related to technical failures and causes due to integrated care issues were reported in 18 studies. CONCLUSIONS: This review showed that causes for readmissions were mainly evaluated from a hospital perspective. However, causes beyond the scope of the hospital can also play a major role in unplanned readmissions. Opinions regarding preventability seem to depend on contextual factors of the readmission. This study presents a cause classification framework that could help future readmission studies to gain insight into a broad range of causes for readmissions in a patient journey.

Possible drug-drug interaction between high-dose esomeprazole and phenprocoumon.

PURPOSE: It is established that omeprazole increases (R)+ warfarin levels with around 10 %. Whether (es)omeprazole also increase the plasma levels of acenocoumarol or phenprocoumon is still uncertain. We analyzed whether addition of (es)omeprazole to acenocoumarol or phenprocoumon increases the international normalized ratio (INR) levels and the risk of overanticoagulation. METHODS: We analyzed all hospital admissions in four teaching hospitals. Patients who used coumarins and pantoprazole or (es)omeprazole simultaneously for at least four consecutive days were included in the study. We analyzed the highest INR level and whether patients had an INR level above six. We compared patients using omeprazole or esomeprazole with patients using pantoprazole, because for pantoprazole, no interaction has been reported. RESULTS: We analyzed 5747 admissions with 4540 patients using one of the drug combinations. For acenocoumarol (4578 admissions), no significant differences were found between users of esomeprazole, omeprazole, and pantoprazole. For phenprocoumon (1169 admissions), the highest INR measured was significantly higher in users of esomeprazole than in users of pantoprazole (4.7 versus 4.3; p = 0.035). No significant difference was found with omeprazole versus pantoprazole (4.3 versus 4.3; p = 0.66). A non-significant association was found between the esomeprazole dose and the highest INR level (p = 0.055). The risk of an INR above six did not differ significantly between esomeprazole and pantoprazole (27.7 % versus 22.9 %; p = 0.34). CONCLUSIONS: The use of esomeprazole simultaneously with phenprocoumon during hospital admissions might increase the anticoagulant effect. The clinical relevance seems to be limited, because no statistically significant increased risk of overanticoagulation was found.