ORAHS 2015

HEC Montréal, July 19 - 24, 2015



HEC Montréal, 19 July — 31 August 2015

Schedule Authors My Schedule

MB3 Modeling Blood Services 1

Jul 20, 2015 01:30 PM – 03:00 PM

Location: Banque Scotia

Chaired by Christos Vasilakis

3 Presentations

  • 01:30 PM - 02:00 PM

    A Generic Simulation Framework for Modelling Blood Inventory: Background, Development, Uses, and Lessons Learned

    • John Blake, presenter, Dalhousie University

    Since 2010 we have created simulation models to analyze logistics and inventory questions for Canadian Blood Services and Héma-Québec, Canada’s two blood agencies. The original genesis of the framework was a model to evaluate the impact of a shorter shelf-life for red blood cells in Québec. A set of similar models was then developed for each of the distribution regions serviced by Canadian Blood Services (CBS). The size of the task led to the adoption of a generic modelling framework that could be easily ported from location to location. While designed to evaluate the amount and distribution of inventory at the different regions in the CBS network, the generic framework and its use has evolved over time – sometimes in unexpected ways. The models have been used to draw general conclusions about shorter shelf life for red blood cells, to evaluate site-to-site inventory transfers between production centres, and even as a basic framework for short term decision making around platelet production ahead of statutory holidays.

    While generic or reusable models are often considered the “holy grail” of modelling efforts, examples of their application in health care are rare. In this presentation we discuss a generic approach to modelling a set of similar problems in the blood supply chain. We discuss the good and the bad of a generic approach. Our experience suggests that the issues that influence the usability of “one-off” models – data availability, ownership and on-going maintenance, and linkage with decision makers – also influences the usefulness of generic models. However, the effort to make a generic model portable serendipitously provides an inherit extensibility to respond to new and unforeseen questions and can thus provide unexpected benefits.

  • 02:00 PM - 02:30 PM

    A Simulation-Optimization Model for Production Planning in the Blood Supply Chain

    • Andres Osorio, University of Southampton
    • Sally Brailsford, presenter, University of Southampton
    • Honora Smith, University of Southampton

    Production planning in the blood supply chain is a complex task. Multiple aspects such as proportionalities of blood groups, shelf life constraints, multiple collection and fractionation alternatives and capacity constraints must be considered. This complexity requires advanced decision-making methodologies. This article presents an integrated simulation-optimisation model to support decisions in production planning. The simulation model is used to represent the flows throughout the supply chain considering collection, production, storing and distribution. On the other hand, an integer linear optimization model running over a rolling horizon planning scheme is proposed to support daily decisions about number of donors required, including blood groups, collection and fractionation methods. The integration of simulation and optimization methodologies enhance the decisions making processes in the studied system. The proposed methodology is evaluated using real information from a blood centre in Colombia. Results show that applying the developed rolling horizon optimization model, a reduction of 16%, 40% and 100% is obtained in the stockout rate for red blood cells, platelets and plasma and cryoprecipitate respectively. In addition, the expired number of units is also reduced by 93% for red blood cells and 45% in the case of platelets. Finally, the number of donors required and the production cost are reduced by about 1.3% using the optimization model proposed.

  • 02:30 PM - 03:00 PM

    Development and Validation of a Discrete Event Simulation Model for Planning Hospital Based Provision of Blood for Mass Casualty Events

    • Simon Glasgow, Centre for Trauma Sciences, Blizard Institute, Queen Mary University of London, UK
    • Christos Vasilakis, presenter, Centre for Healthcare Innovation & Improvement (CHI2), University of Bath School of Management, UK
    • Zane Perkins, Centre for Trauma Sciences, Blizard Institute, Queen Mary University of London, UK
    • Nigel Tai, Trauma Clinical and Academic Unit, The Royal London Hospital, Barts Health NHS Trust, London, UK; Academic Department of Military Surgery and Trauma, Royal Centre for Defence Medicine, Birmingham, UK
    • Karim Brohi, Centre for Trauma Sciences, Blizard Institute, Queen Mary University of London, UK; Trauma Clinical and Academic Unit, The Royal London Hospital, Barts Health NHS Trust, London, UK

    Mass casualty events (MCEs) create a surge in severely injured casualties amongst which haemorrhage is a leading cause of preventable mortality. Minimising in-hospital mortality therefore demands adequate blood provision. MCE planning through live or tabletop excercies is disruptive, costly and limited in terms of experimentation. A simulation model offers potential as a practical planning tool for understanding and improving outcomes from these events.
    For this study we developed a discrete event simulation model of casualty blood provision at a UK major trauma centre following a generic MCE. The model incorporated the delivery of emergency red cells to different cohorts of casualties of varied priority and blood demands. Both treatment and laboratory-based blood group processing systems were modelled. The model was validated using real-life data from the experience at the main responding major trauma centre during the London bombings of 2005.
    Nearly half of all the transfused casualties on the day of the bombings received their transfusion requirement within one hour. Similarly, our simulation experiments incorporated this same amount within the interquartile range (IQR) of results across all 100 replications performed. Furthermore, there was no significant difference identified between the real world values and the model output for all individual red cell treatment times on paired t-test analysis (p value = 0.35). The other principal output of interest was individual red cell group stock levels and their rate of consumption following an event, especially in terms of emergency universal donor group O red cells. All post event real world red cell stock levels were found to fall within the IQR produced by the simulation model for each corresponding group.
    In conclusion, we have designed a simulation model to aid in understanding the transfusion system levers, which potentially have the greatest impact on improving bleeding casualty outcomes following these challenging events.