Probabilistic mathematical modelling to predict the red cell phenotyped donor panel size.

In the last decade, Australia has experienced an overall decline in red cell demand, but there has been an increased need for phenotyped matched red cells. Lifeblood and mathematicians from Queensland universities have developed a probabilistic model to determine the percentage of the donor panel that would need extended antigen typing to meet this increasing demand, and an estimated timeline to achieve the optimum required phenotyped (genotyped) panel. Mathematical modelling, based on Multinomial distributions, was used to provide guidance on the percentage of typed donor panel needed, based on recent historical blood request data and the current donor panel size. Only antigen combinations determined to be uncommon, but not rare, were considered. Simulations were run to attain at least 95% success percentage. Modelling predicted a target of 38% of the donor panel, or 205,000 donors, would need to be genotyped to meet the current demand. If 5% of weekly returning donors were genotyped, this target would be reached within 12 years. For phenotyping, 35% or 188,000 donors would need to be phenotyped to meet Lifeblood's demand. With the current level of testing, this would take eight years but could be performed within three years if testing was increased to 9% of weekly returning donors. An additional 26,140 returning donors need to be phenotyped annually to maintain this panel. This mathematical model will inform business decisions and assist Lifeblood in determining the level of investment required to meet the desired timeline to achieve the optimum donor panel size.

Enhancing treatment participation in CAMHS among families of conduct problem children: effectiveness study of a clinician training programme.

BACKGROUND: The effectiveness of a training programme targeting structural and therapy process strategies to enhance treatment attendance among families of conduct problem children was evaluated across three community mental health clinics. METHOD: Utilising a staggered multiple-baseline design, referrals prior to clinician training were compared to posttraining referrals (N = 221). RESULTS: In comparison to service as usual, children and their families referred after the training initiative had significantly higher treatment attendance (66% vs. 83%) and 79% less likelihood of attrition, though findings were mixed for child's mental health. CONCLUSIONS: The findings provide initial support for the effectiveness of the clinician training programme in increasing treatment involvement.

Telemedicine for rural and remote child and youth mental health services.

The E-Child and Youth Mental Health Service was designed to provide children and adolescents in Queensland with access to specialist mental health consultations using telemedicine. A project officer provided a single point of contact for referral management and clinic coordination, thereby reducing barriers of access to the service. Over a six-month period from November 2004, 42 point-to-point videoconferences were conducted to nine sites in Queensland. Three multipoint conferences were also conducted. Eleven videoconferences (24%) were arranged for administrative purposes, and 34 (76%) were conducted for the delivery of clinical services (30 patients). The referral and consultation activity suggests an improvement in the capacity of rural and remote mental health service providers to deliver specialist services for children and adolescents.