Optimal Blood Safety

Blood products are very safe but as these are obtained from donors that are exposed to an external environment, such risks (e.g. risks from transmissible infections) remain difficult to control. Exposure to emerging infectious diseases may require changes to existing, or implementation of new safety interventions. Also, newly identified non-infectious risks for recipients (like for example the shelf life of blood products) may require adaptation of current practice. Risks of negative health outcomes for recipients of blood products therefore need (re)assessment on a regular basis. Dutch government policy aims at ‘optimal blood safety’. The concept of optimal blood safety has become increasingly acknowledged worldwide, although not (yet) well defined. Within a context of high costs for infection prevention, cost-utility analyses provide tools to support rational decision making for both new and existing safety interventions.

Optimal Blood Use

Modelling recipient outcomes requires national data on clinical blood use and blood recipient profiles, including recipient gender, age, underlying disease and survival after transfusion. In collaboration with hospitals data are collected and maintained on the use of blood products for different categories of recipients and on recipient morbidity and mortality. In addition, the characteristics of local blood use can be used for benchmarking and hypothesis generation for potential risk factors. European data collection and analysis for the Council of Europe by TTA provides additional comparisons and insight in trends in blood use at a European level.

Optimal Blood Supply

Aging of donors may diminish the provision of the blood supply and conversely aging of recipients may increase the demand. Donor population and collection characteristics may be modelled using various available datasets. Blood use may be analysed from hospital datasets in order to signal trends in blood use for various patient groups. Ongoing monitoring and statistical modelling of changes herein allows Sanquin’s blood supply management to be timely informed on trends in supply of and demand for blood.

In addition to predicting future supply in order to ensure meeting blood supply requirements in a quantitative sense, supply itself can be improved by optimizing internal logistics and production processes, which is currently also one of the focal points for research within the BloodMatch project.

Optimal Methodology

Studies performed over the years have revealed that in some cases existing methods or models require adaptation or that these can be improved or extended. Hence, methodological developments have been primarily initiated for problem solving within the TTA objectives, and when appropriate, submitted for publication. Development of new methodological approaches is essential to remain on the forefront of transfusion technology assessment research.

Tools

A number of tools have been developed by the TTA group (either alone or in collaboration with others) that are publicly available:

• The European Up Front Risk Assessment Tool (EUFRAT) 

• The ISBT Cost Utility tool for blood screening tests

• The European Travelling donors’ risk assessment tool (EBA)

• The WHO Risk-Based Decision-Support Tool for Blood Safety (no weblink available yet)

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Key publications
 

• Langi Sasongko P, Rolink M, van den Hurk K, van Kraaij M, Janssen M. Past, present, and future: a qualitative and literature study identifying historical trends, drivers, and transformational factors for the future demand of blood supply in the Netherlands. Transfusion 2019; 59: 3413-23.
• van Sambeeck JHJ, de Wit PD, Luken J, Veldhuisen B, van den Hurk K, van Dongen A, Koopman MMW, van Kraaij MGJ, van der Schoot CE, Schonewille H, de Kort W, Janssen MP. A Conceptual Framework for Optimizing Blood Matching Strategies: Balancing Patient Complications Against Total Costs Incurred. Front Med (Lausanne) 2018;5: 199.
• de Vos AS, van der Schoot CE, Rizopoulos D, Janssen MP. Predicting anti-RhD titers in donors: Boostering response and decline rates are personal. PLoS ONE 13(4): e0196382, 2018.
• Koffijberg H, Knies S, Janssen MP. The Impact of Decision Makers’ Constraints on the Outcome of Value of Information Analysis. Value Health 2018;21: 203-9.
• Janssen MP, van Hulst M, Custer B, ABO RBDM Health Economics Outcomes Working Group Collaborators. An assessment of differences in costs and health benefits of serology and NAT screening of donations for blood transfusion in different Western countries. Vox Sang 2017;112: 518-25.
• de Vos AS, Janssen MP, Zaaijer HL, Hogema BM. Cost-effectiveness of the screening of blood donations for hepatitis E virus in the Netherlands. Transfusion 2017;57: 258-66.
• Janssen MP. What does your data tell you? How transfusion chain data can support managerial decision‐making. ISBT Science Series 2017;12: 38-45.
• Neslo REJ, Oei W, Janssen MP. Insight into “Calculated Risk”: An Application to the Prioritization of Emerging Infectious Diseases for Blood Transfusion Safety. Risk Anal 2017;37: 1783-95.
• Fischer K, Lewandowski D, Janssen MP. Modelling lifelong effects of different prophylactic treatment strategies for severe haemophilia A. Haemophilia 2016;22: e375-82.
• Mapako T, Oei W, van Hulst M, Kretzschmar ME, Janssen MP. Modelling the risk of transfusion transmission from travelling donors. BMC Infect Dis 2016;16: 143.
• Custer B, Janssen MP, Alliance of Blood Operators Risk-Based Decision-Making I. Health economics and outcomes methods in risk-based decision-making for blood safety. Transfusion 2015;55: 2039-47.
• Borkent-Raven BA, Janssen MP, van der Poel CL, Schaasberg WP, Bonsel GJ, van Hout BA. The PROTON study: profiles of blood product transfusion recipients in the Netherlands. Vox Sang 2010;99: 54-64.