IntroductionMedication administration errors (MAEs) are the most common type of medication error. Furthermore, they are more common among neonates as compared with adults. MAEs can result in severe patient harm, subsequently causing a significant economic burden to the healthcare system. Targeting and prioritising neonates at high risk of MAEs is crucial in reducing MAEs. To the best of our knowledge, there is no predictive risk score available for the identification of neonates at risk of MAEs. Therefore, this study aims to develop and validate a risk prediction model to identify neonates at risk of MAEs.Methods and analysisThis is a prospective direct observational study that will be conducted in five neonatal intensive care units. A minimum sample size of 820 drug preparations and administrations will be observed. Data including patient characteristics, drug preparation-related and administration-related information and other procedures will be recorded. After each round of observation, the observers will compare his/her observations with the prescriber’s medication order, hospital policies and manufacturer’s recommendations to determine whether MAE has occurred. To ensure reliability, the error identification will be independently performed by two clinical pharmacists after the completion of data collection for all study sites. Any disagreements will be discussed with the research team for consensus. To reduce overfitting and improve the quality of risk predictions, we have prespecified a priori the analytical plan, that is, prespecifying the candidate predictor variables, handling missing data and validation of the developed model. The model’s performance will also be assessed. Finally, various modes of presentation formats such as a simplified scoring tool or web-based electronic risk calculators will be considered.
Pharmacy value-added services (PVAS) include any innovative pharmacy activities to facilitate and aid the refilling of medications. In Malaysia, the government has invested in infrastructure development, promotional activities, and manpower to enhance PVAS utilization. In this study, PVAS data for the years 2019 and 2020 that were obtained from all public health facilities in the state of Selangor, Malaysia, were analyzed to identify the pattern of PVAS utilization. A reduction in the total number of new and refill prescriptions was observed in 2020. The number of patients enrolled in a PVAS program increased by 44.5% in 2020. Overall, totals of 222,358 and 416,635 prescriptions were supplied through the PVAS programs in 2019 and 2020, respectively. The most common PVAS that was newly offered in 2020 was the medicines by post (locally known as Ubat Melalui Pos) service. The service was also the most utilized PVAS by patients in 2020. The average waiting time per prescription for patients receiving their medications from the outpatient pharmacies at the hospitals increased slightly in 2020 but was reduced at the health clinics. Activities such as campaigns to promote PVAS can be undertaken to further enhance the utilization of the services at public health facilities.
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