ABSTRACT
OBJECTIVE: Because both clerks and medical faculty quality management workers expressed the need for it, we aimed to develop a compact, valid and uniform instrument to assess the quality of Dutch clinical clerkships across all medical faculties in the Netherlands. METHOD: We divided all 249 items from existing published and unpublished clerkship quality instruments into the three essential learning environment domains: content, atmosphere and organisation. In a 3-stage Delphi procedure, the 45 most relevant items from this list were selected that comprehensively covered the three domains. All clinical clerks in the country's northeastern educational region were invited to evaluate their last clerkship using this draft instrument. We used half of these data for item reduction and the other half to validate the final instrument, the QUality Instrument for ClerKships (QUICK). RESULTS: After the Delphi procedure and further item reduction, the QUICK comprises 15 items, 5 in each domain. The internal consistency of the QUICK and each of the three domains was satisfactory (Cronbach's α 0.88, 0.73, 0.84 and 0.67, respectively). The variance of the draft instrument domain scores were explained for >80% by item variance of the final QUICK. A panel of educational experts and medical faculty quality management workers evaluated QUICK's face validity as good. CONCLUSION: The QUICK is a concise and valid instrument to assess the quality of Dutch clinical clerkships. Its repeated use in a quality cycle can contribute to monitoring and ongoing development of the quality of this key phase in the medical education curriculum.
Subject(s)
Clinical Clerkship , Faculty, Medical , Humans , Learning , Reproducibility of Results , Surveys and QuestionnairesABSTRACT
BackgroundLittle is known on amplitude-integrated electroencephalography (aEEG) during the first few days after birth in neonates with congenital heart disease (CHD). Our aim was, therefore, to assess electrocortical activity using aEEG within the first 72 h after birth in neonates diagnosed prenatally with CHD, and to define independent prenatal and postnatal predictors for abnormal aEEG.MethodsNeonates with CHD who were admitted to the neonatal intensive care unit between 2010 and 2017 were retrospectively included. We assessed aEEG background patterns, sleep-wake cycling, and epileptic activity during the first 72 h after birth and defined prenatal and postnatal clinical parameters associated with aEEG patterns.ResultsSeventy-two neonates were included. Twenty-six (36%) had mildly abnormal and six (8%) had severely abnormal aEEG background patterns at some point during the study period. Sleep-wake cycling was present in 97% of the neonates. Subclinical seizures were common (15%), whereas none of the neonates had clinical seizures. Only treatment with sedatives was a significant predictor for abnormal aEEG background patterns, explaining 56% of the variance.ConclusionAbnormal aEEG background patterns are common and are strongly associated with treatment with sedatives in neonates with prenatally diagnosed CHD. Future studies should assess the association between early postnatal aEEG abnormalities and neurodevelopmental outcome.
