Modelling and simulation of blood collection systems: improvement of human resources allocation for better cost-effectiveness and reduction of candidate donor abandonment

Designing an optimal model of blood logistics management with the possibility of return in the three-level blood transfusion network

BACKGROUND

Inventory managers in the blood supply chain always endeavor to provide their clients with prompt and appropriate responses. On the other hand, timely and regular blood deliveries to consumers are essential since ineffective delivery and transportation practices promote shortages, returns, blood loss. The paper attempted to develop an extensive and integrated optimal model of blood transfusion network logistics management by blood type to reduce the cost of losses, returns, and blood shortages given the relevance of this for the blood transfusion network.

METHODS

The regional blood transfusion network in Khorasan Razavi, which contains one main base, six central bases, and 54 hospitals, should be constructed using the optimal model for blood inventory management and distribution. A reusable simulation process was used to identify the optimal behavior for the inventory of all participants in the region (central bases as suppliers and hospitals as consumers), and the demand of hospitals as consumers has been calculated using artificial neural networks. This will lead to a significant reduction of returned blood units by consumers, optimal management of suppliers' and consumers' inventory to prevent waste and shortages. The routing method was used to proceed with the designed model and look into the optimal strategy to distribute blood requested by the consumers. with the aim of reducing the cost and increasing the speed of transportation.

RESULTS

The model's solution allowed for the estimation of the amount of consumers' demand, the optimal amount of target stock, the central bases and hospitals' reorder points, as well as the method of distributing blood from the supplier to its consumers. Implementing the model leads to outcomes such as reducing the time of blood transfer from the central bases to their consumers, increasing the speed of blood delivery to the consumers, increasing the average stock of blood in the central bases, reducing the accumulation of distribution machines at the location of the central bases, the amount of stock, the method for requesting, consuming, and storing blood, and the performance of the central bases' consumers all affect how much control they have over them.

A systematic literature review of simulation models for non-technical skill training in healthcare logistics

Background

Resource allocation in patient care relies heavily on individual judgements of healthcare professionals. Such professionals perform coordinating functions by managing the timing and execution of a multitude of care processes for multiple patients. Based on advances in simulation, new technologies that could be used for establishing realistic representations have been developed. These simulations can be used to facilitate understanding of various situations, coordination training and education in logistics, decision-making processes, and design aspects of the healthcare system. However, no study in the literature has synthesized the types of simulations models available for non-technical skills training and coordination of care.

Methods

A systematic literature review, following the PRISMA guidelines, was performed to identify simulation models that could be used for training individuals in operative logistical coordination that occurs on a daily basis. This article reviewed papers of simulation in healthcare logistics presented in the Web of Science Core Collections, ACM digital library, and JSTOR databases. We conducted a screening process to gather relevant papers as the knowledge foundation of our literature study. The screening process involved a query-based identification of papers and an assessment of relevance and quality.

Results

Two hundred ninety-four papers met the inclusion criteria. The review showed that different types of simulation models can be used for constructing scenarios for addressing different types of problems, primarily for training and education sessions. The papers identified were classified according to their utilized paradigm and focus areas. (1) Discrete-event simulation in single-category and single-unit scenarios formed the most dominant approach to developing healthcare simulations and dominated all other categories by a large margin. (2) As we approached a systems perspective (cross-departmental and cross-institutional), discrete-event simulation became less popular and is complemented by system dynamics or hybrid modeling. (3) Agent-based simulations and participatory simulations have increased in absolute terms, but the share of these modeling techniques among all simulations in this field remains low.

Conclusions

An extensive study analyzing the literature on simulation in healthcare logistics indicates a growth in the number of examples demonstrating how simulation can be used in healthcare settings. Results show that the majority of studies create situations in which non-technical skills of managers, coordinators, and decision makers can be trained. However, more system-level and complex system-based approaches are limited and use methods other than discrete-event simulation.

Simulation-optimization model for production planning in the blood supply chain

Production planning in the blood supply chain is a challenging task. Many complex factors such as uncertain supply and demand, blood group proportions, shelf life constraints and different collection and production methods have to be taken into account, and thus advanced methodologies are required for decision making. This paper presents an integrated simulation-optimization model to support both strategic and operational decisions in production planning. Discrete-event simulation is used to represent the flows through the supply chain, incorporating collection, production, storing and distribution. On the other hand, an integer linear optimization model running over a rolling planning horizon is used to support daily decisions, such as the required number of donors, collection methods and production planning. This approach is evaluated using real data from a blood center in Colombia. The results show that, using the proposed model, key indicators such as shortages, outdated units, donors required and cost are improved.

Discrete Event Simulation-Based Resource Modelling in Health Technology Assessment

OBJECTIVE

The objective of this article was to conduct a systematic review of published research on the use of discrete event simulation (DES) for resource modelling (RM) in health technology assessment (HTA). RM is broadly defined as incorporating and measuring effects of constraints on physical resources (e.g. beds, doctors, nurses) in HTA models.

METHODS

Systematic literature searches were conducted in academic databases (JSTOR, SAGE, SPRINGER, SCOPUS, IEEE, Science Direct, PubMed, EMBASE) and grey literature (Google Scholar, NHS journal library), enhanced by manual searchers (i.e. reference list checking, citation searching and hand-searching techniques).

RESULTS

The search strategy yielded 4117 potentially relevant citations. Following the screening and manual searches, ten articles were included. Reviewing these articles provided insights into the applications of RM: firstly, different types of economic analyses, model settings, RM and cost-effectiveness analysis (CEA) outcomes were identified. Secondly, variation in the characteristics of the constraints such as types and nature of constraints and sources of data for the constraints were identified. Thirdly, it was found that including the effects of constraints caused the CEA results to change in these articles.

CONCLUSION

The review found that DES proved to be an effective technique for RM but there were only a small number of studies applied in HTA. However, these studies showed the important consequences of modelling physical constraints and point to the need for a framework to be developed to guide future applications of this approach.