Management of patients with major haemorrhage is extremely challenging due to its often unpredictable occurrence, requirement for multiple tasks to be completed simultaneously by a multidisciplinary team at a moment’s notice and an increasing risk of patient morbidity and mortality. Providing blood products to institutions across Australia to support the management of haemorrhage wherever and whenever it occurs also represents a significant financial cost to the community, but hospital costs of managing a massive transfusion (MT) are essentially unknown.
MT requires a time-critical coordinated effort between front-line clinicians (anaesthetists, emergency physicians, and nursing staff), haematologists, and hospital blood bank staff, working in separate physical environments to expedite complex transfusion support requirements. Most hospitals organise this process through a locally adapted MT Protocol (MTP) that directs staff roles and activities, specifies the type and quantity of blood products, and provides guidance for ongoing laboratory investigation, markers for success of resuscitation and continuing management specific to the cause of bleeding.
To improve patient care in complex settings, clinical decision support systems (CDSS) have been developed that involve computerised application of evidence-based rules or algorithms to patient-specific information. These systems have been shown in non-critical transfusion settings to reduce both the amount of blood transfused and patient complications. To-date however, no such studies have been conducted to evaluate their efficacy in critical bleeding requiring MT. Therefore, it is imperative that additional approaches be investigated to address these problems and improve the efficacy and efficiency of this process and therefore improve patient outcomes.
The aim of this study, which is part of Dr Sanderson’s PhD, is to enhance decision-making processes during MT to improve efficiency and outcomes through the development of a CDSS for MT. Specifically, this research project will identify quality indicators and processes that represent optimised decision-making in MT and describe the barriers and risks of clinical decision-making processes in MT. To address these barriers and risks, the investigators will develop and evaluate a computerised CDSS to optimise clinical decision-making processes.
This project will support rational use of blood products during MT, help conserve this precious resource by establishing evidence-based quality indicators, and support institutions around the world to improve their own MTP quality processes. It will also describe anaesthetists’ experiences in managing MT to ensure that proposed improvements to the process address the perceived barriers of its most common users. Finally, this project will establish the role of a CDSS for surgical MT and recommend whether such systems should be considered in clinical practice. Additionally, this project has the potential to help support clinicians in other life-threatening clinical contexts to provide evidence-based care via CDSS, improve outcomes, and reduce the cost of caring for vulnerable patient populations. Therefore a reduction in transfusion requirements should improve patient outcomes and reduce costs of healthcare.
Dr Brenton Sanderson, Westmead Hospital and Macquarie University, NSW; Professor Enrico Coiera, Macquarie University, NSW; Professor Erica Wood, Monash Univeristy, Melbourne; Dr Lise Estcourt, John Radcliffe Hospital, Oxford UK; Dr Jeremy Field, Westmead Hospital, NSW.
The project was awarded $A130,244 including scholarship through the ANZCA research grants program in 2020.
Major bleeding can occur in surgical, trauma, obstetric, or critically ill patients, but remains difficult to manage, requiring significant hospital resources often urgently and unexpectedly.
Patients may require massive blood transfusion (MT), and recent studies show 30-day mortality at over 20%, related to blood loss, underlying causes, or complications. Studies show that MT requires a time-critical, coordinated effort between front-line clinicians, haematologists, and hospital blood bank staff, working in separate environments to expedite complex transfusion support.
Most hospitals use a locally-adapted MT Protocol (MTP) to determine roles, activities, blood products, quantities, laboratory investigation guidance, success markers for resuscitation, and continuing management specific to cause of bleeding. High quality process completion is associated with better patient outcomes, and reduced blood resource requirements and overall cost.
MT requires critical decisions on timing and blood product selection, often by staff resuscitating the patient, involving significant stress. Clinical decision support systems (CDS) developed to improve complex care, involving computerised evidence-based rules, algorithms and patient information, are shown to reduce blood transfused and complications in non-critical settings. However, before this research no studies had evaluated their efficacy in critical bleeding requiring MT.
This project aimed to enhance MT decision-making by developing and evaluating a CDS; identify quality indicators and processes for optimised MT decision-making; and to describe barriers and risks in these processes.
The team’s systemic literature review of current MT measures research identified a lack of international consensus on optimal quality care measures. Significant variation in the quality indicators reported limited potential to guide future decision making. Pragmatic indicators that may represent high quality care were also identified for future investigation.
In a binational MT survey, anaesthetists reported that multiple simultaneous tasks and lack of equipment to measure patient’s blood clotting potential limited their subjective performance the most. A majority supported future use of a CDS for MT.
A prototype MT CDS was then developed using best-practice evidence-based software development, involving clinical staff, and several opportunities were identified to improve MT efficiency and efficacy. The prototype, ‘MTP Assistant’, was evaluated in a randomised simulation trial using a simulated bleeding patient compared to current best practice. MTP Assistant improved decision efficiency, with similar efficacy, while reducing clinical team cognitive load.
These outcomes also support the potential to use a decision support approach in other emergency scenarios associated with high cognitive load.
Sanderson, B., Coiera, E., Asrianti, L., Field, J., Estcourt, L. J., & Wood, E. M. How well does your massive transfusion protocol perform? A scoping review of quality indicators. Blood Transfusion 2020;18(6), 423. Doi: 10.2450/2020.0082-20
Sanderson, B. J., Field, J. D., Estcourt, L. J., Wood, E. M., & Coiera, E. W. Massive transfusion experience, current practice and decision support: A survey of Australian and New Zealand anaesthetists. Anaesthesia and Intensive Care 2021. Doi: 0310057X20974035.
Sanderson B, Field JD, Kocaballi AB, et al. Multicenter, multidisciplinary user-centered design of a clinical decision-support and simulation system for massive transfusion. Transfusion. 2023;63(5):993-1004. Doi: 10.1111/trf.17315