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Stephen Dean

Publications and source records attributed to Stephen Dean.

12 recordsLinked to original sources
PubMed2004

The origins of system status management.

A review of the scientific, administrative and popular literature on system status management and vehicle location reveals the following: 1. Historical demand patterns can be used to predict future patterns. 2. If the number of calls exceeds the number of ambulances available, calls must wait for an available ambulance, and this increases response time averages. Response times can be reduced by matching the number of ambulances with the number of calls received (matching supply with demand). 3. Response times can be reduced by dispersing ambulances in a service area and also by placing ambulances near the locations of expected clusters of calls. 4. Ambulance demand patterns fluctuate by hour of day and by day of week. 5. All ambulance services have some sort of procedures and policies for preparing for the next response (system status management). Some use algorithms and step-by-step procedures to prepare for the next call; others rely upon dispatchers to invent them on the spot. 6. Ambulance response times can be improved using dynamic deployment and peak-load staffing, but it is also possible to reduce quality with these techniques. Results are influenced by system design, competence of the managers and commitment of the workforce.

Emergency Medical Services↗
PubMed2003

In vivo transgenic mutation assays.

Transgenic rodent gene-mutation models provide relatively quick and statistically reliable assays for gene mutations in the DNA from any tissue. This report summarizes those issues that have been agreed upon at a previous IWGT meeting [Environ. Mol. Mutagen. 35 (2000) 253], and discusses in depth those issues for which no consensus was reached before. It was previously agreed that for regulatory applications, assays should be based upon neutral genes, be generally available in several laboratories, and be readily transferable. For phage-based assays, five to ten animals per group should be analyzed, assuming a spontaneous mutant frequency (MF) of approximately 3x10(-5) mutants/locus and 125,000-300,000 plaque or colony forming units (pfu or cfu) per tissue per animal. A full set of data should be generated for a vehicle control and two dose groups. Concurrent positive control animals are only necessary during validation, but positive control DNA must be included in each plating. Tissues should be processed and analyzed in a blocked design, where samples from negative control, positive control and each treatment group are processed together. The total number of pfus or cfus and the MF for each tissue and animal are reported. Statistical tests should consider the animal as the experimental unit. Nonparametric statistical tests are recommended. A positive result is a statistically significant dose-response and/or statistically significant increase in any dose group compared to concurrent negative controls using an appropriate statistical model. A negative result is a statistically non-significant change, with all mean MFs within two standard deviations of the control. During the current workshop, a general protocol was agreed in which animals are treated daily for 28 consecutive days and tissues sampled 3 days after the final treatment. This recommendation could be modified by reducing or increasing the number of treatments or the length of the treatment period, when scientifically justified. Normally male animals alone are sufficient and normally at least one rapidly proliferating and one slowly proliferating tissue should be sampled. Although, as agreed previously, sequencing data are not normally required, they might provide useful additional information in specific circumstances, mainly to identify and correct for clonal expansion and in some cases to determine a mechanism associated with a positive response.

Animals↗