The use of historical platelet counts from blood donors to program apheresis platelet donation: An Australian perspective.

BACKGROUND: For Australian apheresis platelet donations, in-centre haematology analysers provided the platelet count used to program the platelet collection machines. When the haematology analysers were not functional, historical platelet counts from previous donations were used. This study aimed to confirm that the routine use of historical platelet counts for programming apheresis collection machines would maintain platelet yields within the donated units and that haematology analysers could be removed. STUDY DESIGN: A staggered implementation for the routine use of mean historical platelet counts to program apheresis platelet collection machines was conducted. The donors' full blood counts following donation were tested centrally for comparison to the historical mean. The component yields when using on-the-day platelet counts to program platelet collection were compared with those collected using historical platelet counts. For historical platelet counts to be deemed successful, the target was for 90% of the mean historical donor platelet counts to have less than 20% variance from the on-the-day platelet count. RESULTS: Over 96% of the mean historical platelet counts were within 20% variance of the platelet count on the day of donation. The component yield (platelet count x109 cell/unit) before analyser removal was 273.3 ±â€¯32.0 (n = 2639) and post-removal was 282.8 ±â€¯38.8 (n = 2689). CONCLUSION: The removal of haematology analysers from donor centres and replacement with mean historical platelet counts was successful in maintaining platelet yields. Replacement of the haematology analysers with historical platelet counts simplified regulatory compliance, reduced staff workload and costs associated with analyser registration.

Methodological Guidelines for Reducing the Complexity of Data Warehouse Development for Transactional Blood Bank Systems.

Over time, data warehouse (DW) systems have become more difficult to develop because of the growing heterogeneity of data sources. Despite advances in research and technology, DW projects are still too slow for pragmatic results to be generated. Here, we address the following question: how can the complexity of DW development for integration of heterogeneous transactional information systems be reduced? To answer this, we proposed methodological guidelines based on cycles of conceptual modeling and data analysis, to drive construction of a modular DW system. These guidelines were applied to the blood donation domain, successfully reducing the complexity of DW development.