Availability of antimalarial medicines and inventory management at the community level: a case study of Bugesera district in Rwanda.

BACKGROUND: Malaria is a public health hazard globally, with Sub-Saharan Africa accounting for more than 90% of malaria deaths, primarily affecting children under the age of five. In Rwanda, malaria interventions include the availability of antimalarial medications, notably Artemisinin-based combination treatments (ACTs) and quick diagnostic test kits (RDTs). However, the availability of antimalarial medicines and its related inventory management at community level in Rwanda has yet to be identified. METHODS: The study was conducted using a descriptive cross-sectional research design. The study involved the Community Health Workers (CHWs) in Bugesera District, working as a team of one male-female pair called Binômes. CHWs provide Integrated Community Case Management (iCCM) and treatment of Malaria in the villages. The sample size was 295 and respondents were selected using convenient random sampling from 15 sectors of Bugesera District, each cell being represented. A structured research questionnaire was used to collect data. The questionnaires were filled by CHWs who were available for this study at the time of data collection. Collected data were exported to SPSS version 26 for coding and analysis. RESULTS: The CHWs reported to be actively involved in managing the antimalarial medicines inventory. Overall, 64.1% of CHWs indicated that the population could easily obtain antimalarial medicines from community health workers and 31.2% attested that people could also obtain antimalarial medicines from the health centers. Majority of respondents 78% confirmed that the CHWs had the appropriate storage conditions for antimalarial medicines, while the overall stock out recorded was 3.20%. Furthermore, CHWs described some challenges, including but not limited to, lack of appropriate or dependable transportation and inappropriate medicines storage. Transportation was reported as a critical barrier for accessing antimalarial medicines. The majority, 70,85% travel on foot while 25.4% reported that CHWs walk for a distance between 1 and 2 h for resupply of antimalarial medicines. CONCLUSION: This study investigated the availability of antimalarial medicines and inventory management challenges at community level in Rwanda. Addressing these challenges will reduce the rate of stockout and increase the availability of antimalarial medicine at community level. Appropriate storage, and reduction of stock out rate, will serve to strengthen the current CHWs system, and provide critical guidance for the evolution of CHWs' systems in Rwanda.

Influence of inventory management practices on the availability of emergency obstetric drugs in Rwandan public hospitals: a case of Rwanda Southern Province.

BACKGROUND: Stock-outs of some life-saving drugs, such as emergency obstetric drugs, are evident in many health facilities and have been reported to be the leading cause of maternal mortality and morbidity for women from low and middle income countries (LMICs). For many cases, this situation is associated with poor inventory management practices. The aim of this study was to investigate the influence of inventory management practices on the availability of emergency obstetric drugs in Rwandan public hospitals: case of the Rwanda Southern Province. Moreover, to gain a better grasp of the problem and to suggest possible areas for improvement. METHODS: An institutional-based cross-sectional study was carried out in all ten district hospitals (DHs) providing maternal health care and dispensing emergency obstetric drugs namely; Kigeme DH, Munini DH, Kabutare DH, Kibilizi DH, Gakoma DH, Nyanza DH, Ruhango DH, Gitwe DH, Kabgayi DH and Remera Rukoma DH. Both quantitative and qualitative data were collected and analyzed. Oxytocin injection, Misoprostol tablet and Magnesium sulphate injection as recommended emergency obstetric drugs by WHO, UNFPA and Rwanda Essential Medicines list were included in the study. RESULTS: The study revealed that keeping logistics management tools up to date is the backbone of inventory management practices in the availability of medicines and medical supplies. The results showed that hospitals with up-to-date logistics tools for their pharmaceutical management were 33.25 times more likely to have their emergency obstetric drugs in stock at all times compared to those that do not regularly update their logistics tools. The proper use of bin cards and electronic software (e-LMIS) contributed greatly to reducing the stock-out rate of emergency obstetric drugs by 89.9% and reduction of unusable to usable stock ratio by appropriate use of simple techniques such as the Min-Max inventory control model by 79%. Over an 18-month period, misoprostol tablet had the highest average days (32) of stock-outs (5.9%), followed by magnesium sulphate injection with an average of 31 days (5.7%), and oxytocin injection with an average of 13 days (2.4%). CONCLUSION: Proper use of pharmaceutical management tools within hospitals premises positively influence the availability of life-saving drugs, such as emergency obstetric drugs. Adequate supply chain staffing in health facilities is the most important key to improving inventory management practices and medicine availability.

A Comparison of Inventory Management Models in Automated Dispensing Cabinets at a Large Academic Medical Center.

Purpose: To compare and evaluate 2 methods of inventory management in automated dispensing cabinets (ADCs). Methods: Ten profiled ADCs had 2 inventory management models implemented over 2 months. Implementation of the models on each ADC involved adjustment of par levels (desired accessible quantities of medication) and removal of medications not used in the past 90 days or more. The par levels of 5 ADCs were adjusted using a formula developed based on the economic order quantity model. The par levels of the other 5 ADCs were adjusted using a formula based on historical average daily usage. The study endpoints include stock out rate, vend:fill ratio, quantity of expired medications, and inventory carrying cost. Results: The total of number of medications stocked in the 10 ADCs was reduced from 3035 in a 2-month pre-implementation period to 2932 in a 2-month post-implementation period yielding a reduction of inventory carrying cost by $11 011. The mean stock out rate in both study groups increased and vend:fill ratio decreased after implementation. The quantity of expired medications increased in the modified economic order quantity formula inventory management model and decreased in the average daily usage inventory management model. Conclusion: The implementation of 2 inventory management models on ADCs had a negative impact on stock out rate and vend:fill ratio, a mixed impact on quantity of expired medications, and a positive impact on inventory carrying cost reduction.

Optimal policy of ordering blood units in the hospital according to compatibility and priority transfers between blood groups under uncertainty conditions: A case study.

In spite of significant advancements in medicine, there is still a shortage of human blood in the world. At present, there is no alternative chemical process or product that can produce blood, and only humans are capable of doing so. It is for this reason that blood is such an important component of our healthcare system. Due to the perishability of blood, managing blood inventories can be challenging. The challenge is to maintain a high level of supply while minimizing loss due to expiration. The purpose of this study is to present a mathematical model that reduces inventory costs, determines the optimal ordering policy in hospitals, and prevents the loss of blood units. To determine the optimal inventory level and order volume, a mixed integer programming model is presented in both deterministic and non-deterministic conditions. In order to address the uncertainty in the problem, a robust optimization approach is used. This model minimizes the transfer of blood groups and transmission between hospitals by considering compatibility and priority. A sensitivity analysis has also been conducted on the model. Based on a case study, it is demonstrated that the costs of buying, storing, ordering, and wasting two important RBCs and platelets can be reduced.

Inventory management practices: implications on the pharmaceuticals expenditure of rabies vaccine in public health facilities, Namibia.

BACKGROUND: To achieve well-regulated distribution, storage, and utilization of the rabies vaccine, health facilities should adhere to standard operating procedures. In Namibia, information on inventory management, utilization, monitoring, and reporting of rabies vaccine adherence to standard operating procedures in public healthcare facilities is insufficient. The aim of this study was to assess adherence to rabies vaccine standard operating procedures and inventory management and to compare rabies vaccine expenditure to the number of patients who received rabies vaccination at the Ministry of Health and Social Services' public healthcare facilities from 2018 to 2020. METHODS: A cross-sectional, web-based questionnaire consisting of closed-ended questions was sent to 147 pharmacy staff and warehouse managers working in the 14 regions of Namibia during the period of May 1, 2021, to June 2, 2021. The overall expenditure and the total number of patients vaccinated from 2018 to 2020 were obtained from national-level logistic and vaccination program coordinators. Data were coded and transcribed into Microsoft® Excel® 2013 and analyzed using SPSS® version 27. RESULTS: One hundred and thirty-three completed questionnaires were received from sixty-nine public health centers and hospitals. The group of respondents consisted of pharmacist assistants (50%), pharmacy technicians (12%), pharmacists (36.8%), senior pharmacists (0.8%), and chief pharmacists (1.5%). Overall, adherence to standard operating procedures was poor (27.1%). Rabies vaccine distributed to public health facilities from 2018 to 2020 was worth N$75,381,419.91 (~ US$4,074,671.46) and was expected to vaccinate 87,269 patients; however, only 95 cases of both rabies and rabid dog-bite patients were reported. The major inventory management challenges for public healthcare facilities include an inadequate number of pharmacy staff, poor adherence to standardized pharmaceutical warehousing, lack of regular supervision, and inadequate staff training. CONCLUSION: Inventory management practices in public healthcare facilities were not in compliance with standard operating procedures. There is a significant discrepancy between rabies vaccine expenditure and the number of patients that were vaccinated. Therefore, there is a need for adequate staff training on inventory management and regular facility supervision to enforce optimal rabies vaccine inventory management practices.

Predictors of medicine redistribution at public healthcare facilities in King Cetshwayo District, KwaZulu-Natal, South Africa.

BACKGROUND: Effective pharmaceutical inventory management is essential for optimizing healthcare outcomes and supply chain performance. However, challenges such as stockouts, overstocking, and wastage can hinder this process. This study examines the interrelationships between overstocking, stockouts, and wastage in eight healthcare facilities in Northern KwaZulu-Natal, South Africa. It also explores the extent of these challenges and investigates the use of medicine redistribution as a strategy to address inventory management issues. METHODS: A retrospective quantitative analysis was conducted using pharmacy inventory records from public healthcare facilities. Eight facilities, including hospitals and a community healthcare center in King Cetshwayo District, were purposively sampled. Linear regression analysis was used to examine the association between medicine redistribution as the outcome and the predictors - stockouts, overstocking, and wastage. Pearson's correlation was utilized to evaluate associations between the predictors. Descriptive statistics were employed to quantify the levels and extent of overstocking, stockouts, and wastage related to expiry. RESULTS: The study included eight healthcare facilities with pharmacy warehouses managed by pharmacists. A total of 392 medicines were analyzed (49 per facility). Stockouts affected 85.6% of medicines, while overstocking and expiry-related wastage impacted 50.6% and 15.2% of medicines, respectively. The most common stock-out medicines were salbutamol 200mcg inhalant (4.0%), paracetamol 500 mg tablets (3.5%), and azithromycin 500 mg tablets (3.3%). Overstocking, stock with short-dated expiry, and expired medicines explained 68% of redistribution transactions to other facilities (r² = 0.68). A moderate, statistically significant correlation was observed between overstocking and expiry-related wastage (r² = 0.47, p-value = 0.020). Stockouts had a weak correlation with redistribution, accounting for only 4.5% (p-value < 0.01). A weak correlation was found between stockouts and overstocking (r = 0.10), as well as between stockouts and expired medicines (r = -0.20). CONCLUSION: This study highlights significant challenges in inventory management, particularly regarding stockouts, overstocking, and expiry-related wastage in the evaluated healthcare facilities. Medicine redistribution emerged as a viable strategy to address these challenges. Improving inventory management practices and implementing targeted interventions are crucial for optimizing pharmaceutical supply chain performance and enhancing healthcare delivery outcomes in this setting.

The knock-on effects of COVID-19 pandemic on the supply and availability of generic medicines in Ethiopia: mixed methods study.

BACKGROUND: COVID-19 pandemic posed a major impact on the availability and affordability of essential medicines. This study aimed to assess the knock-on effects of the COVID-19 pandemic on the supply availability of non-communicable chronic disease (NCD) medicines and paracetamol products in Ethiopia. METHODS: A mixed methods study was conducted to assess the supply and availability of twenty-four NCD drugs and four paracetamol products listed on the national essential medicines list for hospitals. Data were collected from twenty-six hospitals located in seven zones of Oromia region in the southwestern part of Ethiopia. We extracted data on drug availability, cost and stock out for these drugs between May 2019 and December 2020. The quantitative data were entered into Microsoft Excel and exported to statistical package software for social science (SPSS) version 22 (IBM Corporation, Armonk, NY, USA) software for analysis. RESULTS: The overall mean availability of selected basket medicines was 63.4% (range 16.7% to 80.3%) during the pre-COVID-19 time. It was 46.3% (range 2.8% to 88.7) during the pandemic. There was a relative increase in the availability of two paracetamol products [paracetamol 500 mg tablet (67.5% versus 88.7%) and suppository (74.5% versus 88%)] during the pandemic. The average monthly orders fill rates for the selected products range from 43 to 85%. Pre-COVID-19, the average order fill rate was greater or equal to 70%. However, immediately after the COVID-19 case notification, the percentage of order(s) filled correctly in items and quantities began decreasing. Political instability, shortage of trained human resources, currency inflation, and limited drug financing were considered as the major challenges to medicine supply. CONCLUSION: The overall stock out situation in the study area has worsened during COVID-19 compared to pre-COVID-19 time. None of the surveyed chronic disease basket medicines met the ideal availability benchmark of 80% in health facilities. However, availability of paracetamol 500 mg tablet surprisingly improved during the pandemic. A range of policy frameworks and options targeting inevitable outbreaks should exist to enable governments to ensure that medicines for chronic diseases are consistently available and affordable.

Conductive Polymer-Based Interactive Shelving System for Real-Time Inventory Management.

Stockouts constitute a major challenge in the retail industry. Stockouts are caused by errors related to manual stockkeeping and by the misplacement of items on shelves. Such errors account for up to 4% of lost sales. Real-time inventory management systems for misplaced items or missing stock detection in retail stores are limited. Accordingly, a conductive polymer-based interactive shelving system for real-time inventory management is developed. The system comprises an 80 × 48 sensor array fabricated by screen-printing a piezoresistive carbon-based conductive polymer layer onto gold interdigitated electrodes deposited on a flexible substrate. Each sensing pixel has dimensions of 5 mm × 5 mm and a sensing area of 4 mm × 4 mm. The sensor mat can detect the shape and weight features of stockkeeping units (SKUs), which can then be analyzed by a TensorFlow model for SKU identification. The developed system is characterized for functional resistance range, uniformity, repeatability, and durability. The accuracy of SKU identification achieved using shape features only and the accuracy of SKU identification achieved using both shape and weight features is 95% and 99.2%, respectively. The key novelty of the work is the development of a deep learning-embedded interactive smart shelving system for retail inventory management by using the shape and weight features of SKU. Also, the developed system helps to detect the SKU if they are stacked one over the other. Furthermore, multiple sensor mats implemented on various shelves in a retail store can be modularized and integrated for monitoring under the control of a single PC. Accordingly, the proposed retail inventory tracking system can facilitate the development of automated "humanless" shops.

Dual sourcing inventory management with nonconsecutive lead times from a supply chain perspective: a numerical study.

We study a stochastic multi-period two-echelon dual sourcing inventory system where the buyer can source a product from two different suppliers: a regular and an expedited supplier. The regular supplier is a low-cost offshore supplier, whereas the expedited supplier is a responsive nearshore supplier. Such dual sourcing inventory systems have been well studied in the literature, mostly being solely evaluated from the buyer's perspective. Since the buyer's decisions have an impact on the supply chain profit, we adopt the perspective of the entire supply chain, i.e., by taking the suppliers explicitly into consideration. In addition, we study this system for general (nonconsecutive) lead times for which the optimal policy is unknown or very complex. We numerically compare the performance of two different policies in a two-echelon setting: the Dual-Index Policy (DIP) and the Tailored Base-Surge Policy (TBS). From earlier studies we know that when the lead time difference is one period, DIP is optimal from the buyer's perspective, but not necessarily from the supply chain perspective. On the other hand, when the lead time difference grows to infinity, TBS becomes optimal for the buyer. In this paper, we evaluate the policies numerically (under various conditions) and we show that from a supply chain perspective, TBS typically outperforms DIP at a limited lead time difference of a few time periods. Based on data collected from 51 manufacturing firms, the results of our paper imply for many supply chains with a dual sourcing setting that TBS quickly becomes a beneficial policy alternative, especially given its simple and appealing structure.

An optimization framework for COVID-19 vaccine allocation and inventory management: A case study.

As the novel coronavirus pandemic wreaked havoc globally, governments have implemented massive vaccination programs to tackle it. However, since the pandemic's emergence moves beyond the second year, some issues have stymied vaccination programs, including vaccine hesitancy, vaccine distribution inequality, new strains of the virus, and a possibility that the virus enters a stage of a requirement for cyclical vaccination. These challenges highlight the need for an appropriate mass COVID-19 vaccination program. Therefore, we attempt to address this problem by developing a bi-objective integrated vaccine allocation and inventory management framework. The goal is to minimize the system costs while maximizing the vaccination service level. Several important factors, such as multiple types of vaccines, the vaccines' perishability concept, demand uncertainty, and motivational strategy, have been addressed using dynamic planning. Besides that, the model development mechanism is carried out to be compatible and applicable to the current general vaccination program policies, forcing few strategic changes. Then, a case study concerning the vaccination program of the city of Mashhad in Iran is applied to the model. The results demonstrated significant advantages in total cost, vaccine shortage, and wastage compared to the current policy. Finally, the Lagrangian relaxation method is implemented on the model to strengthen further its capacity to handle larger-scale problems.

[Research on Emergency Material Inventory Management Mode Based on AHP-ABC Classification].

OBJECTIVE: To establish an emergency material inventory management system for hospitals. METHODS: The evaluation index weight of emergency supplies is calculated by analytic hierarchy process, and the emergency supplies are divided into three categories by ABC classification method. The data of emergency supplies inventory before and after the establishment of classification management are analyzed. RESULTS: 15 kinds of common emergency supplies are determined, and the evaluation system composed of 5 first-class indexes. The evaluation weights pass the consistency test and meet the requirements of analytic hierarchy process. 15 kinds of emergency materials are divided into three categories: A, B and C, and inventory management is further optimized to improve the turnover rate of emergency supplies and reduce capital occupation. CONCLUSIONS: The classified management system of emergency materials constructed by analytic hierarchy process is scientific and reasonable, which provides a reference and new idea for the classified management of emergency materials inventory under public health emergencies.

Implementation of a dual platelet inventory in a tertiary hospital during the COVID-19 pandemic enabling cold-stored apheresis platelets for treatment of actively bleeding patients.

BACKGROUND: To increase preparedness and mitigate the risk of platelet shortage without increasing the number of collections, we introduced a dual platelet inventory with cold-stored platelets (CSP) with 14-days shelf life for actively bleeding patients during the COVID-19 pandemic. STUDY DESIGN AND METHODS: We collected apheresis platelet concentrates with blood type O or A. All patients receiving CSP units were included in a quality registry. Efficacy was evaluated by total blood usage and laboratory analysis of platelet count, hemoglobin, and TEG 6s global hemostasis assay. Feasibility was evaluated by monitoring inventory and a survey among laboratory staff. RESULTS: From 17 March, 2020, to 31 December, 2021, we produced 276 CSP units and transfused 186 units to 92 patients. Main indication for transfusion was surgical bleeding (88%). No transfusion reactions were reported. 24-h post-transfusion patient survival was 96%. Total outdate in the study period was 33%. The majority (75%) of survey respondents answered that they had received sufficient information and training before CSP was implemented. Lack of information about bleeding status while issuing platelets, high workload, and separate storage location was described as main reasons for outdates. DISCUSSION: CSP with 14-days shelf life is a feasible alternative for the treatment of patients with bleeding. Implementation of a dual platelet inventory requires thorough planning, including information and training of clinical and laboratory staff, continuous follow-up of practice and patients, and an easy-to-follow algorithm for use of CSP units. A dual platelet inventory may mitigate the risk of platelet shortage during a pandemic situation.

Use of O RhD-negative red blood cells: A nationwide, prospective audit.

BACKGROUND AND OBJECTIVES: Despite declining transfusion rates, overuse of O RhD-negative red blood cells (RBCs) risks the secure supply of this limited resource. A nationwide prospective audit was performed in Finland to understand the clinical use and inventory management of O RhD-negative units. Our aim was to identify areas where policy changes could help alleviate the shortage of O RhD-negative RBCs. MATERIALS AND METHODS: The use of every O RhD-negative unit in Finland during a period of 1 month was reviewed. For each issued unit (n = 1105), unit age, urgency of transfusion, hospital and patient demographics, and specific reasons for issuing O RhD-negative units were recorded. RESULTS: Almost half of the O RhD-negative units (n = 529, 47.9%) were issued to non-O RhD-negative patients. Only 22.3% (n = 118) were issued for females under the age of 50. Of the units for ABO-nonidentical transfusion, one-third (32.5%, n = 172) were issued for emergency transfusion, two-thirds (67.5%, n = 357) for non-urgent transfusions. The most common reason for issuing an O RhD-negative unit was inventory management (n = 172, 48.2% of units issued for non-urgent transfusion). Most of these units were issued close to the unit expiry date. CONCLUSION: This nationwide audit revealed that a significant proportion of O RhD-negative RBCs are used inappropriately. Clinicians should be educated on the appropriate use of O RhD-negative RBCs, and blood banks should develop strategies for inventory management to avoid issuing O RhD-negative units purely to prevent outdating.

Point-of-use hospital inventory management with inaccurate usage capture.

Many hospital supply chains in the US follow a "stockless" structure, often implemented with the acquisition of new systems promising improved efficiencies and responsiveness. Despite vendor promises, supply chain gains from new technology are often unfulfilled or result in a reduction of performance. A critical component of achieving promised gains is the hospital's ability to accurately and consistently capture hospital inventory use. In practice, recording demand with perfect, 100% accuracy is infeasible, so our models condition on the level of accuracy in a particular hospital department, or point-of-use (POU) inventory location. Similar to previous literature, we consider actual net inventory and recorded net inventory in developing the system performance measures. We develop two models, optimizing either cost or service level, and we assume a periodic-review, base-stock (or par-level) inventory policy with full backordering. In addition to choosing the optimal order-up-to level, we seek the optimal frequency of inventory counts to reconcile inaccurate records. Results from both models provide insights for supply chain managers in the hospital setting, as well as hospital administrators considering the adoption of similar technologies or systems.

Classification of medicines and materials in hospital inventory management: a multi-criteria analysis.

BACKGROUND: In the hospital environment, to achieve an optimum level of operations and service, it is necessary to develop adequate inventory management system. Stocks can be managed, amongst other ways, through inputs classification, which is generally carried out based on a single criterion, such as monetary value, demand or criticality, which does not fully address the complexity of a hospital's inventory management system. Thus, the present study proposes a multi-criteria decision support model to help classify the stock of medicines and materials, enabling a more effective inventory management system for hospitals. METHODS: Methodologically, the study followed 3 stages: (1) preliminary phase; (2) modelling and choice phase; and (3) finalization phase. Each stage had a set of specific steps that were followed. The first stage identified the actors of the process, objectives, criteria and alternatives, establishing 5 criteria and 48 alternatives; the second stage was the choice and execution of the multi-criteria decision method to solve the problem. It was decided to use the Flexible and Interactive Tradeoff method for the sorting problematic. Finally, in the third stage, the sensitivity analysis for the developed model and the validation of the results with decision makers were carried out. In the study, 48 medicines and materials were included to validate the proposed model; however, the model could be used for more items. RESULTS: From the total of 48 medicines and hospital medical materials selected for the study, the classification of 34 of these alternatives to a single class was obtained through modelling and the other 14 alternatives were destined to two possible classes; moreover, the sensitivity analysis performed showed robust results. The items classified in class W should receive special attention by the stock manager; therefore, they should be monitored weekly. Items classified in class B should be monitored biweekly and finally, items classified in class M, should be monitored monthly. CONCLUSIONS: The classification of medicines and materials developed according to the inventory demands allowed more efficient purchasing decisions, optimizing the stock of materials and medicines at the hospital while optimizing the inventory manager's activities, saving time. Consequently, the proposed model can support the development of other multicriteria models in different hospital scenarios.

Implementing a material planning and control method for special nutrition in a Brazilian public hospital.

This study aims to (i) propose a demand forecast model for special nutrition materials in the context of health services, and (ii) comparatively evaluate three inventory management and control systems (periodic review, continuous review and mixed) for special nutrition materials. For that, we carried out a case study in a Brazilian public teaching hospital where data and information collection were conducted over a span of 22 months (from January 2018 and were consolidated until October 2019). A six-step approach was followed to propose the demand forecasting models and, later, evaluate the inventory control systems for special nutrition materials. Results indicate that if the organization implements the proposed inventory management method, there could be savings of up to 33% in the stock values managed by the healthcare organization. This research shows the planning and control of special nutrition materials in an integrated manner. Demand forecasting methods have been combined with inventory management to promote systemic improvements to healthcare organization.

A Real-Time Cup-Detection Method Based on YOLOv3 for Inventory Management.

Inventory is the basis of business activities; inventory management helps industries keep their inventories stocked with reasonable quantities, which ensures consumers demand while minimizing storage costs. The traditional manual inventory management has low efficiency and a high labor cost. In this paper, we used improved YOLOv3 to detect the cups stored on the warehouse shelves and counted their numbers to realize automated inventory management. The warehouse images are collected by the camera and transmitted to the industrial computer, which runs the YOLOv3 network. There are three feature maps in YOLOv3, the two smaller feature maps and the structure behind them are removed, and the k-means algorithm is used to optimize the default anchor size. Moreover, the detection range is limited to a specified area. Experiments show that, by eliminating those two feature maps, the network parameter is reduced from 235 MB to 212 MB, and detection FPS is improved from 48.15 to 54.88 while mAP is improved from 95.65% to 96.65% on our test dataset. The new anchors obtained by the k-means algorithm further improve the mAP to 96.82%. With those improvements, the average error rate of detection is reduced to 1.61%. Restricted detection areas eliminate irrelevant items to ensure the high accuracy of the detection result. The accurately counted number of cups and its change provide significant data for inventory management.

Modelling retail inventory pricing policies under service level and promotional efforts during COVID-19.

Most supply chain and production systems faced multiple manufacturing and delivery challenges during COVID-19 and transformed their supply chain for improved customer service. These challenges are mostly related to stocking and managing the inventory flow throughout the supply chain (from manufacturer to end consumer). Due to the COVID-19 travel and movement restrictions, inventory reorganisation is necessary for fulfilling consumer demand with adequate service facilities. The safety and serviceability of inventory consumption is the primary concern of many retail grocery stores and consumers. Maintaining the supply of groceries items during and post COVID-19 time without disruption is a real operational and policy challenge. Therefore, this research tries to solve an inventory pricing mechanism and retailer's profit under the optimal service level and retailers' promotional efforts. The proposed optimisation model is validated in the grocery retail sector. The grocery retail market situation is modelled when the demand for the grocery product (which may be essential items) and selling price depending on the investment in item promotional effort and consumer serviceability. The retail grocery store's investment in the product promotional efforts, such as awareness of the item availability and no-contact delivery which, may attract consumers. Therefore, the proposed inventory consumption is modelled with an optimisation problem to maximise the store profit with the optimal investment in promotional activities and service facilities to the consumers and maintain an optimal replenishment cycle. The optimisation model is tested with three different cases (no investment in promotional efforts, no investment in service facility, and investment in both) of investment to maximise the retailer's profit and stock availability. The optimality results depicted that investment in promotional efforts and service facility givens higher profit to the retailer. The proposed optimisation model's policy implications would help grocery retail store managers to develop operational strategies for maximising profit with the optimal service level and promotional efforts.

Just-in-time approach in healthcare inventory management: Does it really work?

Healthcare organizations need to efficiently use their available resources, improve their productivity, reduce operating costs, and provide high-quality services. Just in time (JIT) is an approach that has benefited the healthcare industry in these regards, improving patient outcomes by reducing waste and non-value-adding activities. As such, our main purpose in this study was to discuss the use of JIT systems in healthcare inventory management and highlight their importance, as well as explore the advantages and limitations of JIT systems in healthcare management systems. We also explored supply chain issues in healthcare during the COVID-19 pandemic and provide strategies and recommendations for improvement.

Application of unsupervised machine learning to identify areas of blood product wastage in transfusion medicine.

BACKGROUND: Wastage of blood products can be a significant cost to blood banks. However, the cause of wastage is often complex and makes it difficult to determine wastage-associated factors. Machine learning techniques may be useful tools to investigate these complex associations. We investigated whether unsupervised machine learning can identify patterns associated with wastage in our blood bank. MATERIALS AND METHODS: Data on red blood cells, platelets and frozen products were obtained from the laboratory information system of the Central Zone Blood Transfusion Services at Nova Scotia Health Authority. A total of 879 532 transactions were analysed by association rule mining, a type of machine learning algorithm. Associations with lift scores greater than 25 and with clinical relevance were flagged for further examination. RESULTS: Association rule mining returned a total of 3355 associations related to wastage. Several notable associations were identified. For example, certain wards were associated with wastage due to thawing unused frozen products. Other examples included association between smaller blood banks and evening work shifts with product wastage due to excess time outside the laboratory or returning products with high temperatures. CONCLUSION: This paper demonstrates the effective use of unsupervised machine learning for the purpose of investigating wastage in a large blood bank. The use of association rule mining was able to identify wastage factors, which can help guide quality improvement initiatives. This technique can be automated to provide rapid analysis of complex associations contributing to wastage and could be utilized in modern blood banks.