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This paper presents data relating to occupant pre-evacuation times from a university and a hospital outpatient facility. Although the two structures are entirely different they do employ relatively similar procedures: members of staff sweeping areas of the structure to encourage individuals to evacuate. However, the manner in which the dependent population reacts to these procedures is quite different. In the hospital case the patients only evacuated once a member of the nursing staff had instructed them to do so while in the university evacuation the students were less dependent upon the actions of the staff with over 50% of them evacuating with no prior prompting. Although this data may be useful in a variety of areas, it was collected primarily for use within evacuation models.

The population pharmacokinetics of cyclosporine (CsA) in adult recipients of cardiac transplants were determined from sparse, retrospective drug monitoring data accumulated for at least 3 months after surgery. All were receiving oral CsA twice daily, and morning trough levels in whole-blood were measured by high-performance liquid chromatography. Additional data included height, weight, gender, age, ethnicity, hematocrit, total bilirubin, and concurrent drug use. Population modeling was performed using NONMEM on 36 randomly selected patients, assuming a one-compartment model with first-order absorption and elimination. Improved fits were obtained by incorporating the following expression in the model to adjust oral bioavailability as a function of postoperative day (POD): F = 0.2 + 10 x ABS (POD - 7)/([POD + 10] x 60). Interpatient variability (CV%) in clearance (CL) was 20.2%. There was a mean bias of 8.5% at the average CsA concentration of 250 ng/ml when the predictive performance was assessed statistically in a reserved subset of 33 patients who received cardiac transplants. For the entire population (n = 69 patients), the average CsA CL and terminal half-life (T1/2) were, respectively: CL (l/h) = 0.256 x weight (kg); T1/2 = 11.0 hours, or CL (l/h) = 0.184 x weight (kg); T1/2 = 14.7 hours, if there was concomitant diltiazem administration. These results compared favorably with those reported elsewhere for studies of postcardiac transplant kinetics using the traditional multiple blood sampling approach.

Using a validated population modelling approach, it was found that a number of factors influence the pharmacokinetics of CsA during the early postoperative period in cardiac transplant patients. These influences affecting oral bioavailability and clearance may need to be taken into account for maintaining appropriate concentrations of CsA in the bloodstream.

Aim: To investigate errors in prescribing, dispensing and administering medications, determine the origin of the error and analyse the risks according to established risk-rating matrices. Method: Errors detected by pharmacists were recorded and combined with errors recorded by nurses and doctors. Errors were classified by type of event, source of report and professional group responsible for the occurrence. Errors were evaluated against two risk-rating matrices developed by Queensland Health and Standards Australia. Results: Reported errors occurred at the rate of 1.8% of drugs prescribed over the period from admission to discharge. There were no dispensing errors reported during the study period. Nurses reported 150 incidents and pharmacists detected 275. In the majority of cases it was possible to identify the node in the medication-use process that was associated with the error (35% administering and 53% prescribing) but this was not possible in 12% of cases. The two largest categories of errors were incorrect dose prescribed (29%) and dose not recorded as given (28%). There was a marked difference in risk profile between the two risk-rating matrices. Conclusion: The majority of errors were due to performance lapses or lack of knowledge. The difference in risk profiles suggests that hospitals should adopt a uniform risk-rating matrix for benchmarking purposes. To avoid underestimates of hospital error rates, a reporting system that can interface with pharmacy information-management systems needs to be developed . INTRODUCTIONPharmacists have traditionally collected data on interventions made during clinical ward rounds or when dispensing prescriptions. This data collection is sporadic, or limited to occasions that seem particularly interesting or significant. The limited scope of collection is mainly due to workload issues or a perceived lack of opportunity to influence the behaviour of those who prescribe and administer drugs. It appears that many pharmacy departments do not report their intervention data to the hospital executive and therefore senior managers are not aware of the extent to which pharmacists reduce the risk of misadventure to patients.This study was conducted at Queen Elizabeth II Jubilee Hospital, Queensland-a 168-bed district hospital providing gynaecology, orthopaedic, urology, geriatric rehabilitation, general surgery, general medicine, intensive care, and accident and emergency services. The hospital has a high turnover of doctors, many of whom are overseas-trained. As a large proportion of these staff arrive outside of normal staff changeover times when there is no organised training and orientation, there is a great need for scrutiny of their prescribing practices.