The efficient management of pharmaceuticals is crucial for ensuring the availability of essential medicines when and where they are needed. However, errors in the pharmaceutical supply chain can have significant negative effects on the health of populations. Errors in the pharmaceutical supply chain can lead to a range of negative effects on the health of populations. One major negative effect is the risk of medication errors, which can occur at any stage of the supply chain, from manufacturing to dispensing. Medication errors can lead to adverse drug events, which can result in serious harm or even death. A study by (James, 2013) estimated that medication errors are responsible for 7000 people deaths in the United States per year. Similarly, a study by (Ayele and Tesfaye, 2021) found that medication errors were a significant problem in Ethiopia. The pooled prevalence of drug-related problems of patients who experienced at least one drug-related problem during their therapy was 69.4%. Furthermore, the overall level of patient safety culture including reporting of adverse events was very low (Kumbi et al., 2020).
Another negative effect of errors in the pharmaceutical supply chain is drug shortages. A study conducted by (Shukar et al., 2021) found that multifactorial issues including manufacturing problems, unavailability of raw materials, logistic and business problems, just-in-time inventory, higher demand for a product, unpredictable demand and lack of a unified definition of drug shortage were linked with causes of medicine shortage.
Drug shortages had a significant clinical and financial impact on patients (Atif et al., 2021) and can lead to delays in treatment, decreased quality of care, and the use of alternative medications with potentially harmful side effects. A study by (Fox et al., 2014) found that drug shortages in the United States were associated with increased mortality rates and higher healthcare costs. A study by (D et al., 2021) found that drug shortages were a common problem in Ethiopia, with up to 70.16% and 70.1% of public and private hospitals experiencing shortages of essential medications.
Substandard or counterfeit medications are another negative effect of errors in the pharmaceutical supply chain. Counterfeit medications can contain harmful ingredients or incorrect dosages, while substandard medications may not meet quality standards and may be ineffective in treating illnesses. A study by (Bate et al., 2008) estimated that up to 41% of antimalarial medications sold in sub-Saharan Africa were counterfeit or substandard. The use of these medications can lead to increased morbidity and mortality and can exacerbate the spread of infectious diseases.
In addition, errors in the pharmaceutical supply chain can lead to increased healthcare costs. When medications are not available or are not delivered in a timely manner, patients may require additional hospitalizations or treatments, leading to increased healthcare costs. A study by (Lee Ventola, 2011) found that medication errors and drug shortages in the United States were associated with increased healthcare costs. A study by (Mohammed et al., 2022) found that drug shortages in Ethiopia were associated with increased healthcare costs, with each day of drug shortage resulting 33.33% and 28.57% higher prices than international prices in private and public health facilities, respectively.
To mitigate these negative effects, healthcare organizations and supply chain management experts must implement effective strategies and best practices for pharmaceutical management. These strategies may include implementing inventory management techniques to ensure that medications are available when and where they are needed, using demand forecasting to anticipate future medication needs, and optimizing supply chains to reduce the risk of errors and delays.
2.1 Frameworks to Ensure Life-saving Medicines
Ensuring the development and availability of life-saving medicines is a crucial goal and critical global health priority for healthcare systems worldwide. Decision-making frameworks can play a critical role in this process by guiding the development, evaluation, and distribution of life-saving medicines. Various frameworks and initiatives, such as the WHO's Essential Medicines List, the Access to Medicine Index, and other global health initiatives, have been developed to address this challenge. These frameworks play a significant role in promoting transparency, accountability, and innovation in the pharmaceutical sector and have contributed to improving access to essential medicines worldwide. Ongoing research and collaboration among stakeholders are necessary to continue advancing this important goal.
The World Health Organization (WHO) Essential Medicines List (EML)
is a key initiative aimed at ensuring the availability of life-saving medicines for the global population. Established in 1977, the EML is a regularly updated list of medicines that are considered essential for addressing the priority health needs of populations (World Health Organization, 2019). The EML has been recognized as a critical tool for improving access to medicines, particularly in low- and middle-income countries (Persaud et al., 2019).
The EML classifies medicines into two main categories: core and complementary. Core medicines are those that are considered basic and indispensable for healthcare facilities, while complementary medicines may be necessary for certain conditions but are not always readily available due to higher costs or specialized needs (World Health Organization, 2019).
The Access to Medicine Index (ATMI)
is a biennial ranking of pharmaceutical companies based on their efforts to improve access to life-saving medicines, particularly in low- and middle-income countries. The index, which was first published in 2008, is developed by the Access to Medicine Foundation, a non-profit organization (Access to Medicine Foundation, 2021). The ATMI evaluates companies based on seven key areas, including research & development, pricing, and intellectual property management, with the aim of encouraging companies to prioritize access to essential medicines (Wirtz et al., 2017).
The ATMI has been praised for its role in promoting transparency and accountability among pharmaceutical companies, as well as for encouraging the development of innovative access strategies (Leisinger et al., 2012).
Other Relevant Frameworks and Initiatives: Several other frameworks and initiatives have been proposed and implemented to ensure the availability and accessibility of life-saving medicines. Some of these include: The 2030 Agenda for Sustainable Development, which includes a specific target (3.8) related to achieving universal access to essential medicines and vaccines (United Nations, 2015).
The Medicines Transparency Alliance (MeTA), a multi-stakeholder initiative aimed at improving transparency and accountability in the pharmaceutical sector, particularly in low- and middle-income countries (MeTA, 2021).
The Global Fund to Fight AIDS, Tuberculosis, and Malaria, which supports programs to increase access to life-saving medicines for these diseases in the most affected countries (The Global Fund, 2021).
Theoretical framework of Demand Planning
Demand planning is a critical function in supply chain management that involves forecasting, estimating and managing customer demand for goods and services. It is crucial for organizations to have an effective demand planning process to ensure that they can meet customer demand while avoiding overstocking or stock outs. Theoretical frameworks can provide a useful basis for understanding the key concepts and variables that affect demand planning. This theoretical framework will focus on three key theories related to demand planning: the theory of demand forecasting, the theory of inventory management, and the theory of aggregate planning.
The theory of demand forecasting suggests that demand planning is based on the accurate estimation of future demand for goods and services. This theory emphasizes the importance of using historical data, market trends, and other relevant factors to forecast future demand accurately. Several forecasting methods have been developed to estimate future demand, including time-series forecasting, regression analysis, and judgmental forecasting (Armstrong, 2001; Makridakis S, Wheelwright SC, 1997). The theory of demand forecasting recommends using historical data, market trends, and other relevant factors to forecast future demand accurately. The goal is to identify patterns and trends in past demand that can be used to estimate future demand. This can be done using various forecasting methods, such as time-series forecasting, regression analysis, and judgmental forecasting.
The theory of inventory management emphasizes the importance of managing inventory levels to balance customer demand and supply. This theory recognizes that holding inventory incurs costs, such as storage and handling expenses, and can tie up capital. Therefore, it is essential to manage inventory levels effectively to meet customer demand while minimizing inventory holding costs. Inventory management techniques such as JIT and EOQ can help organizations optimize inventory levels. Several inventory management techniques have been developed to ensure that inventory levels are optimized, including just-in-time (JIT) inventory management and economic order quantity (EOQ) (Silver and Peterson Pyke, 1998).
The theory of aggregate planning focuses on the optimal allocation of resources to meet customer demand. This theory emphasizes the need to balance production capacity, inventory levels, and workforce levels to ensure that customer demand can be met while minimizing costs. Aggregate planning techniques such as level production planning, chase demand planning, and mixed planning can help organizations optimize their resource allocation (HEIZER and RENDER, 2017).
By integrating these theories, organizations can develop effective demand planning processes that balance customer demand and supply while minimizing costs. Accurate demand forecasting is essential for effective inventory management and aggregate planning. Effective inventory management, in turn, ensures that customer demand can be met while minimizing inventory holding costs. Finally, aggregate planning ensures that production capacity, inventory levels, and workforce levels are optimized to meet customer demand while minimizing costs.
Implementing aggregate planning can be challenging for organizations due to various factors such as forecasting accuracy, capacity constraints, and coordination across departments, seasonality, technology, cost estimation, and resistance to change. However, addressing these challenges can help organizations optimize their resources to meet customer demand while minimizing costs, leading to improved customer satisfaction and profitability. Improving forecasting accuracy, capacity management, effective coordination across departments, adopting flexible production processes, investing in new technologies, using advanced cost estimation techniques, and overcoming resistance to change are some of the best practices that organizations can adopt to overcome the challenges associated with implementing aggregate planning.
implementing aggregate planning and pooled demand management theories can be challenging for pharmaceutical firms due to various factors such as forecasting accuracy, capacity constraints, seasonality, customer heterogeneity, data sharing, and coordination. However, by adopting best practices such as improving forecasting accuracy, capacity management, customer segmentation, data sharing protocols, collaboration, and incentives, pharmaceutical firms can optimize their resources, meet customer demand, and improve overall supply chain performance.o
By following these best practices, organizations can optimize their resources, meet customer demand, and improve overall supply chain performance.
Components of effective decision-making framework in Demand planning
Decision-making frameworks can play a critical role in ensuring the efficiency and effectiveness of the pharmaceutical supply chain. Accurate, robust, and dynamic forecasting is essential for businesses and organizations in various industries. Forecasting can help organizations to make informed decisions, plan for the future, and respond to changing market conditions.
Supply chain visibility
is a fundamental component of decision-making frameworks for the pharmaceutical supply chain. Visibility refers to the ability to track and monitor products as they move through the supply chain, from raw materials to finished products. Supply chain visibility can help to identify and address supply chain disruptions, such as product shortages or delays, and ensure that products are delivered to patients in a timely and efficient manner (Papert et al., 2016).
Risk management
is another critical component of decision-making frameworks for the pharmaceutical supply chain. Risks can arise at every stage of the supply chain, from raw materials to manufacturing and distribution. Decision-making frameworks should include risk management strategies that identify and mitigate potential risks, such as quality control issues or supply chain disruptions (Thakur et al., 2020).
Supplier selection and management
are essential components of decision-making frameworks for the pharmaceutical supply chain. The selection of suppliers who meet quality standards and can provide reliable and consistent products is critical to the success of the supply chain. Decision-making frameworks should include supplier management strategies that ensure ongoing supplier compliance with quality standards and regulatory requirements, such as Good Manufacturing Practice (GMP) and Good Distribution Practice (GDP) (Saunders et al., 2012) (Kurtz et al., 2020).
Data analytics and automation
are emerging components of decision-making frameworks for the pharmaceutical supply chain. Data analytics can be used to identify trends and patterns in supply chain data, such as demand forecasting and inventory management. Automation can be used to streamline supply chain processes, such as order processing and shipment tracking, and reduce the risk of errors and delays (Melo et al., 2021). Accurate, robust and dynamic forecasting is a key element of this framework that can help drive policies and support evidence-based planning and decision making (Merkuryeva et al., 2019). Data analytics is a critical component of accurate, robust, and dynamic forecasting. Data analytics involves the use of statistical techniques and algorithms to analyze historical data and identify trends and patterns. Data analytics can help organizations to understand the factors that influence demand, identify potential risks and opportunities, and develop more accurate forecasts (Guo and Qin, 2017) (Berry & Linoff, 2018).
Regulatory compliance
is another crucial component of decision-making frameworks for the pharmaceutical supply chain. Regulatory authorities require that pharmaceutical products meet rigorous quality standards and are manufactured and distributed in compliance with GMP and GDP. Decision-making frameworks should include strategies for ensuring regulatory compliance, such as regular audits and inspections, and ongoing monitoring of quality standards (Prakash et al., 2021).
Collaboration and partnerships
are essential components of decision-making frameworks for the pharmaceutical supply chain. Collaboration can involve working with suppliers, logistics providers, and other stakeholders to share knowledge and resources, as well as to leverage expertise and technology to improve supply chain efficiency and effectiveness. Partnerships can also facilitate the distribution of pharmaceutical products to patients in need, particularly in low- and middle-income countries (Bhaskar et al., 2020).
Continuous evaluation and improvement
Finally, continuous evaluation and improvement are essential components of decision-making frameworks for the pharmaceutical supply chain. The supply chain is constantly evolving, and decision-making frameworks must be regularly evaluated and improved to ensure that they remain effective and responsive to the evolving needs of patients and healthcare systems. Ongoing monitoring and analysis of supply chain data, as well as the development of new technologies and approaches, can help to optimize the pharmaceutical supply chain (Kamal et al., 2020).
Forecasting models are another essential component of accurate, robust, and dynamic forecasting. Forecasting models use historical data to predict future outcomes and can help organizations to make informed decisions about resource allocation, inventory management, and production planning. Forecasting models can be based on statistical techniques, time-series analysis, or machine learning algorithms (Hyndman et al., 2021). Accurate, robust, and dynamic forecasting is essential for businesses and organizations in various industries. Data analytics, forecasting models, machine learning, ensemble forecasting, real-time forecasting, and uncertainty analysis are all critical components of accurate, robust, and dynamic forecasting. By incorporating these components into forecasting processes, organizations can make more informed decisions, better manage resources, and respond more effectively to changing market conditions. As technology and data analytics continue to evolve, accurate, robust, and dynamic forecasting will become even more critical for organizations to remain competitive and successful in their respective industries. The success of the supply chain relies on the accuracy of demand forecasting (Bousqaoui et al., 2017; Christopher, 2000; Subramanian, 2021).