To explore pregnant women's use, attitudes, knowledge and beliefs of complementary and alternative drugs (CADs) defined as products manufactured from herbs or with a natural origin. A preliminary survey was conducted among 172 pregnant women in their third trimester of pregnancy, consecutively recruited in two obstetrical settings; 15 women were randomly selected to compute a test-to-retest analysis. Response rate was 87.2%. Test-to-retest analysis showed a questionnaire's reproducibility exceeding a K-value of 0.7 for all items. Mean age was 32.4 ± 0.4 years; most women were nulliparae (62.7%). The majority of subjects (68%) declared to have used one or more CADs during their lifetime; 48% of pregnant women reported taking at least one CAD previously and during the current pregnancy. Women's habitual use of CADs meant they were at higher risk of taking CADs also during pregnancy (adjusted odds ratio = 10.8; 95% confidence interval: 4.7–25.0). Moreover, 59.1% of the subjects were unable to correctly identify the type of CADs they were using. The majority of women resorted to gynecologists as the primary information source for CADs during pregnancy, while they mainly referred to herbalists when not pregnant. Habitual use of CADs seems to be a strong predictor for their ingestion also during pregnancy; in addition most subjects were unable to correctly identify the products they were taking. In the light of the scanty data concerning the safety of CADs during pregnancy, these preliminary results confirm the need to investigate thoroughly the situation of pregnant women and CADs consumption.

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Background: In almost all healthcare systems, no-shows (scheduled appointments missed without any notice from patients) have a negative impact on waiting lists, costs and resource utilization, impairing the quality and quantity of cares that could be provided, as well as the revenues from the corresponding activity. Overbooking is a tool healthcare providers can resort to reduce the impact of no-shows. Methods: We develop an overbooking algorithm, and we assess its effectiveness using two methods: an analysis of the data coming from a practical implementation in an healthcare center; a simulation experiment to check the robustness and the potential of the strategy under different conditions. The data of the study, which includes personal and administrative information of patients, together with their scheduled and attended examinations, was taken from the electronic database of a big outpatient center. The attention was focused on the Magnetic Resonance (MR) ward because it uses expensive equipment, its services need long execution times, and the center has actually used it to implement an overbooking strategy aimed at reducing the impact of no-shows. We propose a statistical model for the patient's show/no-show behavior and we evaluate the ensuing overbooking procedure implemented in the MR ward. Finally, a simulation study investigates the effects of the overbooking strategy under different scenarios. Results: The first contribution is a list of variables to identify the factors performing the best to predict no-shows. We classified the variables in three groups: "Patient's intrinsic factors", "Exogenous factors" and "Factors associated with the examination". The second contribution is a predictive model of no-shows, which is estimated on context-specific data using the variables just discussed. Such a model represents a fundamental ingredient of the overbooking strategy we propose to reduce the negative effects of no-shows. The third contribution is the assessment of that strategy by means of a simulation study under different scenarios in terms of number of resources and no-show rates. The same overbooking strategy was also implemented in practice (giving the opportunity to consider it as a quasi-experiment) to reduce the negative impact caused by non attendance in the MR ward. Both the quasi-experiment and the simulation study demonstrated that the strategy improved the center's productivity and reduced idle time of resources, although it increased slightly the patient's waiting time and the staff's overtime. This represents an evidence that overbooking can be suitable to improve the management of healthcare centers without adversely affecting their costs and the quality of cares offered. Conclusions: We shown that a well designed overbooking procedure can improve the management of medical centers, in terms of a significant increase of revenue, while keeping patient's waiting time and overtime under control. This was demonstrated by the results of a quasi-experiment (practical implementation of the ...

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