Adverse events and medication-related errors are common with anticoagulants. Heparin infusions are frequently associated with administration errors or challenges potentially leading to undesired events. Solving these challenges is multi-faceted given related complexities associated with the process, numerous variabilities related to heparin itself, heparin resistance, factors impacting assays to measure the intensity of anticoagulation, ineffective education processes, and limited data even on describing optimal target ranges to hard outcomes of thrombosis and bleeding. To overcome this, health care professionals have looked to technology as a potential solution. Some components of technology, such as smart pumps, and timing lab slips for ordering assays at a selected time to avoid incorrect information, have been means of improving management; however, gaps are still recognized. One component of treatment post a venous thromboembolism is achieving target goals within 24 hours. However, incorrect timing of assay draws related to the bolus and the related changes in order of elimination can work against achieving it unless the situation is understood and adapted during management. Machine learning is being explored to do this; however, it is not yet ready for prime time. Moving forward, clinicians need to stay engaged and be aware of the variables present. This includes an understanding of all assumptions, limitations and verification of what is intended does occur. The process should include validation of hard outcomes with the management approach.
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