Development and validation of a risk prediction model for medication administration errors among neonates in the neonatal intensive care unit: a study protocol.
Josephine Henry BasilChandini Menon PremakumarAdliah Mhd AliNurul-Ain Mohd-TahirZamtira SemanNoraida Mohamed ShahPublished in: BMJ paediatrics open (2023)
This 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.
Keyphrases
- adverse drug
- electronic health record
- intensive care unit
- study protocol
- healthcare
- big data
- randomized controlled trial
- case report
- clinical trial
- public health
- emergency department
- preterm infants
- primary care
- palliative care
- open label
- machine learning
- drug induced
- mass spectrometry
- liquid chromatography
- deep learning
- patient safety
- general practice
- solid phase extraction
- clinical evaluation