Development and validation of a score to assess risk of medication errors detected during medication reconciliation process at admission in internal medicine unit: SCOREM study

[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.

Development of a decision tree for the pharmacy-led consultation of elderly patients with haematological malignancies

INTRODUCTION

Elderly patients with haematological malignancies are a population at risk of iatrogenic for whom these activities could optimize therapeutic management. However, the limitation of human resources requires optimization of the process in order to improve the efficiency of pharmaceutical activities. The objective was to build a decision tree to optimize the pharmaceutical consultation in these population within a multidisciplinary team in haematology.

METHOD

Pharmaceutical consultations were proposed to elderly subjects with haematological malignancies followed up in a haematology day hospitalization at the University Hospital of Limoges. Risk factors for prescribing risky drugs in this population were determined by logistic regression models. A decision tree was constructed based on these results and by agreement between pharmacist, geriatrician and hematologist.

RESULTS

Female gender (aOR[CI95%] = 1.71 [1.14-2.57]), polypharmacy (aOR[CI95%] = 1.89 [1.14-3.13]), hyper-polypharmacy (aOR[CI95%] = 5.73 [3.03-10.84]) and moderate cholinergic load (aOR[CI95%] = 2.15 [1.04-4.45]) were risk factors for the prescription of inappropriate medicine. Female gender (aOR[CI95%] = 1.55 [1.02-2.35]) and hyper-polypharmacy (aOR[CI95%] = 6.19 [1-1.28]) were risk factors for prescribing anticholinergic drugs or anticoagulants; in contrast, frailty status was a protective factor for prescribing anticholinergics (aOR[CI95%] = 0.51 [0.33-0.81]). Prioritization of pharmaceutical consultations is based on frailty status, prescription of a target drug and polypharmacy.

DISCUSSION

Pharmaceutical consultations during the day hospitalization of elderly subjects with hematological diseases allow to propose therapeutic optimizations. The prioritization proposed in our study would increase the efficiency of pharmaceutical activities in order to improve quality and safety throughout the care pathway of these patients.

Clinical usefulness of prediction tools to identify adult hospitalized patients at risk of drug-related problems: A systematic review of clinical prediction models and risk assessment tools

AIMS

This study aimed to review systematically all available prediction tools identifying adult hospitalized patients at risk of drug-related problems, and to synthesize the evidence on performance and clinical usefulness.

METHODS

PubMed, Scopus, Web of Science, Embase, and CINAHL databases were searched for relevant studies. Titles, abstracts and full-text studies were sequentially screened for inclusion by two independent reviewers. The Prediction Model Risk of Bias Assessment Tool (PROBAST) and the Revised Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) checklists were used to assess risk of bias and applicability of prediction tools. A narrative synthesis was performed.

RESULTS

A total of 21 studies were included, 14 of which described the development of new prediction tools (four risk assessment tools and ten clinical prediction models) and six studies were validation based and one an impact study. There were variations in tool development processes, outcome measures and included predictors. Overall, tool performance had limitations in reporting and consistency, with the discriminatory ability based on area under the curve receiver operating characteristics (AUROC) ranging from poor to good (0.62-0.81), sensitivity and specificity ranging from 57.0% to 89.9% and 30.2% to 88.0%, respectively. The Medicines Optimisation Assessment tool and Assessment of Risk tool were prediction tools with the lowest risk of bias and low concern for applicability. Studies reporting external validation and impact on patient outcomes were scarce.

CONCLUSION

Most prediction tools have limitations in development and validation processes, as well as scarce evidence of clinical usefulness. Future studies should attempt to either refine currently available tools or apply a rigorous process capturing evidence of acceptance, usefulness, performance and outcomes.