Exploring trade-offs between staffing levels and turnaround time in a pathology laboratory using discrete event simulation.

Many health delivery services have required performance targets. Typically, these targets are presented as percentiles of patients to be seen within specified timeframes. These targets present hospital administrators with a resourcing problem complicated by conflicting objectives: How to minimize costs while maximizing throughput to achieve the performance targets? In this paper, we describe the use of a simulation model to evaluate the effect of changes to staff levels in a cytology department, investigating the trade-off between staff levels and turnaround times in light of performance targets specified by government. Standard practice for determining staffing levels in a cytology department uses average workload estimates and does not take into account target performance measures, task variability, and the interruptive nature of the workload of pathologists. We develop a simulation model for pathologist workload within a cytology department in New Zealand. We describe the model construction process that follows the hierarchical control conceptual modeling (HCCM) framework. We use the resulting simulation model to examine the trade-offs between staffing levels (and associated rosters) and task turnaround time. The results indicate that consideration of variation in task arrivals is important when considering the effect of staffing levels on turnaround time. Furthermore, as the cytology department is required to meet performance targets that involve maximum service times for a percentile of patients, such an approach is necessary in order to estimate the performance level of a staffing roster.

Distribution of HPV genotypes in women with cervical cancer in Auckland, New Zealand; a review of 50 specimens between 2000-2006.

BACKGROUND: In New Zealand, around two hundred women are diagnosed with cervical cancer annually, with approximately seventy deaths from cervical cancer per year. AIM: Our aim was to determine the distribution of oncogenic HPV genotypes in biopsy specimens from women with diagnosed cervical cancers in the Auckland region of New Zealand between 2000-2006. MATERIALS AND METHODS: Confirmed cases of cervical carcinoma were identified from the local pathology register, and representative tissue samples were taken from these blocks. Sections were deparaffinised, and DNA was extracted according to standard protocols. Samples were subject to PCR amplification using L1 consensus primer sets MY09/11 and GP5/6. Further type-specific amplification was performed on positive samples, using an in-house primer sequence based on target sequences within the E6 gene. Remaining samples were typed by a Linear Array Assay, or by DNA sequencing. RESULTS: HPV DNA was detected in 100% of cases. In 49/50 samples, the HPV genotype was identified, with a total of 14 different HPV genotypes detectable. Together HPV-16 and 18 were found in 41/49 cases (83.6%) either singly or in combination. DISCUSSION: Our findings suggest that the distribution of HPV genotypes in New Zealand is similar to that of other geographic areas. CONCLUSION: Ongoing surveillance is warranted to ensure appropriate genotype selection for prophylactic HPV vaccinations.