Dynamic demand-centered process-oriented data model for inventory management of hemovigilance systems

Abstract

Objectives: This paper presents a reference data model for blood bank management to control blood inventories considering real-world uncertainties and constraints. It helps information systems identify blood product status for various critical deci-sions (such as replenishment, assignment, and issuing) instantly. Additionally, some significant optimization concepts of the inventory management literature for blood wastage and shortage reduction, such as clearance sale and substitution based on medical priorities, are applied in the model. Methods: The proposed model was constructed by object-oriented and ICAM (Integrated Computer Aided Manufacturing) definition ɸ (IDEF0) techniques for function modeling. Through semi-struc-tured questionnaires and interviews, the research team elicited and classified user requirements. Then, the demand-centered sub-processes and comprehensive functions were mapped to manage the process. Results: The model captures and integrates the top-level features of the inventory system entities. It also provides insights into a developed data dictionary to understand the system’s elements and attributes, where a data item fits in the structure, and what values it may contain. For designing the system’s process and following-up data, the main relevant inputs are considered. Conclusions: A flexible and applicable de-mand-centered framework for managing a typical blood bank’s inventory process was developed by focusing on user require-ments. The proposed model can be applied to design and monitor inventory information and decision-support systems. The model provides real-time iterative dynamic process insights. It can also provide the data needed for logistic planning systems and the design of blood operational infrastructure.