Healthcare Supply Chain Research Articles

AI in Healthcare Supply Chain Management: Enhancing Efficiency and Reducing Costs with Predictive Analytics

This paper explores the transformative role of artificial intelligence (AI) and predictive analytics in enhancing operational efficiency within healthcare supply chains. By leveraging AI-driven business analytics, healthcare organizations can optimize inventory management, improve demand forecasting, and streamline supply chain processes. The study presents a comprehensive review of recent advancements, challenges, and opportunities in the integration of AI technologies, focusing on their application in various healthcare contexts. Through systematic analysis of existing literature, the findings emphasize the significance of adopting AI and predictive analytics for effective decision-making, cost reduction, and improved service delivery in healthcare. The research highlights the need for organizations to embrace digital transformation and foster a collaborative approach in the implementation of AI-driven solutions to enhance overall supply chain resilience.

Fermatean fuzzy distance and Sugeno–Weber operators-based SPC-MARCOS approach for sustainable supplier evaluation in the healthcare supply chain

The present work proposes a new decision support tool for assessing the sustainable suppliers in the healthcare supply chain. For this purpose, the classical Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) model is integrated with the Sugeno–Weber weighted averaging operators, modified symmetry point of criterion (SPC) model, rank sum (RS) tool and Fermatean fuzzy sets (FFSs), and named as the ‘FF-SPC-RS-MARCOS’ framework. The developed model firstly determines the decision experts’ weights through RS model. Second, novel Sugeno–Weber weighted operators are introduced to combine the experts’ opinions. Third, a unified weighting procedure is presented based on the combination of modified SPC approach for objective weight and RS method for subjective weight of attributes. To this aim, a novel distance measure is introduced for FFSs and further applied to compute the distance between aggregated Fermatean fuzzy numbers and symmetry point value of an attribute in the modified SPC approach. Further, a hybrid FF-SPC-RS-MARCOS approach is proposed to tackle the decision-making problems on FFSs setting. To elucidate the efficacy of the developed method, it is applied to a case study of sustainable supplier selection problem in the healthcare supply chain. The paper further conducts sensitivity investigation and comparison with existent approaches to test the stability and robustness of the ranking outcomes. This study shows how the proposed MARCOS method in combination with SPC and RS models can be used to prioritize the alternative suppliers in the healthcare supply chain. The introduced work provides a new methodology, which can help the practitioners and academics to evaluate suppliers with uncertain information and can also be employed to other areas facing similar types of decision-making problems.

Optimizing last-mile delivery of essential medicines in Nigeria: Insights from Niger State’s health-care supply chain

Last-mile delivery of health commodities is a critical component of efficient supply chains, and third-party logistics (3PL) providers are pivotal in ensuring cost-effective and reliable product distribution. This study explores the implementation of last-mile delivery outsourcing by government-operated warehouses and drug management agencies (DMAs). This research focuses on the relationship between 3PL utilization and key performance metrics, such as cost reduction, timely delivery, and end-user satisfaction. This study combines a literature review, surveys, and interviews conducted with employees of the DMAs in Minna, Niger State, to establish significant correlations. The findings show that using 3PLs significantly reduced operational costs, improved the frequency of timely deliveries, and enhanced end-user satisfaction. These findings underscore the need for continued engagement with 3PL providers to optimize supply chain performance and improve service delivery outcomes. Managers are recommended to maintain and expand such collaborations to sustain these benefits.

THE EFFECT OF AI-DRIVEN INVENTORY MANAGEMENT SYSTEMS ON HEALTHCARE OUTCOMES AND SUPPLY CHAIN PERFORMANCE: A DATA-DRIVEN ANALYSIS

There has been much focus toward increasing integration of AI in healthcare generally, with a specific focus on inventory management systems in particular. As more hospitals in the United States public and private side face increasing costs and concerns over cost and length of operation all systems supporting inventory must be made most efficient and AI system offers the US hospitals the opportunity to maintain accurate inventory and hence improve the quality of patient care. But the literature review presents a small number of studies that focus on the effects of these systems as the means to improve healthcare results and organization. In this study, it is proposed that improving inventory management by actioning artificial intelligence in healthcare organizations will result in enhanced patient care and improved inventory accuracy, cost reduction and supply chain efficiency in the United States of America’s healthcare institutions. A cross-sectional, quantitative survey was administrated to 200 healthcare personnel and supply chain managers from different healthcare organizations based on hospitals, clinics and specialty medical centers of the USA. Sample design: Participants were purposefully chosen, who had prior exposure to the AI-induced systems or are aware about workflow of such systems. Respondents’ data was gathered via an online questionnaire and analyzed using SPSS: descriptive analysis, chi-square test, one-way ANOVA, correlation analysis, multiple regression analysis was used to establish the relationships of the study variables: AI systems, healthcare outcomes and supply chain performance. The results showed that the use of AI in inventory management systems enhances its accuracy in ordering order itself and overall patient care. Separate studies showed that where the management of a facility has deeper insight of the AI system then there will be more operations worked on to improve efficiency or cut costs. Adoption of these pathways among smaller providers including clinics and long-term care facilities was difficult, especially due to cost constraints. An analysis of the multiple regression equation showed that knowledge of AI improved the projection of potential healthcare outcome, creating greater worth and also increases the performance of supply chain. The outcomes of using AI based inventory management systems in the United States seem to have a lot of advantages that may help improve the efficacy of operations in the healthcare system. Issues such as funding and skills needed for implementation, especially in small healthcare organization, continue to slow the uptake of the technology. These existing problems may be solved if more focused investments in the development of comprehensive AI training or systematic solutions are given to enable the healthcare industry to reach the full potential of the application of artificial intelligence.

Assessing the Dynamic Capabilities and Sustainable Performance in Public Hospital Supply Chains Management

In the volatility, uncertainty, complexity, and ambiguity (VUCA) era, unexpected disasters are rising. The Coronavirus disease 2019 (COVID-19) pandemic severely disrupted healthcare supply chains, with resource shortages significantly impacting the sustainable provision of public healthcare services. This highlighted the importance of supply chain management for public healthcare sustainability operations. An online survey was conducted among 127 public hospital employees and managers, adopting the SEM-PLS method to identify critical dynamic capabilities of supply chain management capabilities and their effect on sustainable development. The results indicate that strategic formulation capabilities, leadership, and digital technology competence significantly enhance the sustainable performance of public hospitals. This finding enriches the literature on sustainable supply chain management in the healthcare sector and provides policymakers and healthcare administrators with decision-making support.

Blockchain in Healthcare: Overview of Applications, Challenges, and Future Directions

There are numerous healthcare issues which show the potential of blockchain technology such as transparency, interoperability and security of data. Through this study, it tries to offer a very deep explanation of where the Blockchain applications today stand for in the healthcare domain emphasising on possible benefits from the technology and some known challenges that are being faced while actuating those. We then use blockchain applications in the above-mentioned aspects to explain different aspects of use of Blockchain in healthcare like supply chain management, clinical trials, secure medical data exchange and patient empowerment. We also talk about Blockchain from implementation point of view – smart contracts, consensus methods and data privacy. In this publication, we determine whether deploying Blockchain in healthcare raises ethical and legal issues and how existing issues can be addressed. In conclusion, we describe future directions for research and opportunities to use Blockchain to improve healthcare delivery and outcomes.

Adapting Efficiency Analysis in Health Systems: A Scoping Review of Data Envelopment Analysis Applications During the COVID-19 Pandemic.

Objective: To synthesize the current evidence base concerning the application of Data Envelopment Analysis (DEA) in healthcare efficiency during the COVID-19 pandemic using a scoping review of 13 primary studies. Methods: We consulted databases including Web of Science (WoS) and Scopus, as well as manual search entries up to September 2022. Included studies were primary applications of DEA for assessing healthcare efficiency during the COVID-19 pandemic. Key findings derived from thematic analysis of repeating pattern observations were extracted and tabulated for further synthesis, taking into consideration the variations in DMU definitions, the inclusion of undesirable outputs, the influence of external factors, and the infusion of advanced technologies in DEA. Results: The review observed a diverse application of DMUs, ranging from healthcare supply chains to entire national health systems. There was an evident shift towards incorporating undesirable outputs, such as mortality rates, in the DEA models amidst the pandemic. The influence of external and non-discretionary factors became more pronounced in DEA applications, highlighting the interconnected nature of global health challenges. Notably, several studies integrated advanced computational methods, including machine learning, into traditional DEA, paving the way for enhanced analytical capabilities. Conclusions: DEA, as an efficiency analysis tool, has exhibited adaptability and evolution in its application in the context of the COVID-19 healthcare crisis. By recognizing the multifaceted challenges posed by the pandemic, DEA applications have grown more comprehensive, integrating broader societal and health outcomes. This review provides pivotal insights that can inform policy and healthcare strategies, underscoring the importance of dynamic and comprehensive efficiency analysis methodologies during global health emergencies.

Avoidance of Medicine Wastage in Private Clinics In Hong Kong: Practitioners’ Perspectives

Hong Kong with its well-established healthcare and medicine system and professional health services is one of the renowned healthiest places in the world. In fact, Hong Kong's healthcare system is running on a dual-track basis comprising public and private sectors. This study intends to explore medicine waste management and sustainability. First, we examine the existing phenomenon of Hong Kong medicine waste. Also, we discuss the causes of medical waste from a private clinic doctors' perspective. In addition, we identifies possible policies and recommendations to minimize the medicine wastage in private clinic in Hong Kong as well as improve the healthcare supply chain practices. Qualitative research with in-depth interviews of doctors and medical practitioners have been carried out to gather their views and opinion of medication wastage, including the current medicine waste situation and the means of handling the expired medicines. Also, the study analyzes the centralized procurement platform effectiveness and suggests some possible policies for government to adopt. Interviewees mentioned that medication waste has occurred over decades. Medicine wastages are not only financial burdens, but also social burdens. If the medication waste problem cannot be alleviated, it will affect the population health and environment in the long run. An all-rounded healthcare supply chain with efficient logistics operations would help the government to collect excess medicines from private clinics and redistribute to some NGOs. In fact, all parties including manufacturers, distributors, prescribers, and patients have the responsibilities to maintain and implement suitable policies to prevent bulk medicine waste. This research study provides the foundation of medicine wastage in private clinics in Hong Kong. Future research can investigate the medicine wastage in other aspects as well as consolidate the literatures in both industrial and public perspectives.

The Value of Applying Big Data Analytics in Health Supply Chain Management

The use of big data analytics (BDAs) allows for the collection, management, and analysis of large volumes of data, which helps in making real-time decisions. This study aims to assess how the application of BDA impacts the performance of healthcare supply chain management (HCSCMP). Through a systematic literature review, the research explores how BDA enhances efficiency within healthcare supply chains (HCSCs) and identifies the critical factors enabling successful BDA implementation. A comprehensive search strategy was employed to analyze 65 papers, resulting in the inclusion of 39 studies published between 2016 and 2023. The review revealed a preference for literature reviews and questionnaires as the primary research methods. The findings indicate that BDA significantly improves HCSCs' efficiency, particularly in real-time decision-making and operational management. However, successful BDA implementation depends on addressing critical enablers and overcoming associated challenges.

The effect of visibility on forecast and inventory management performance during the COVID-19 pandemic

During the COVID-19 pandemic, healthcare facilities faced significant shortages of critical supplies like personal protective equipment, with dire repercussions. This study evaluates the potential role of decreased data visibility on these shortages, analysing different forecasting methods integrated with a periodic review inventory system (i.e. a base stock policy) on semi-simulated data encompassing several visibility issues. The forecasting methods chosen pertain to different data types: Holt and naïve methods are used as demand-based predictors, while a modified epidemiological model utilises pandemic data for demand forecasting. We scrutinise three prevalent data visibility issues through specifically crafted scenarios examining the effects of delayed, temporally aggregated, and erroneous data on system performance. Generally, our research illustrates that data visibility issues have a detrimental impact on the healthcare supply chain's efficacy. Interestingly, the system performance sees an uptick when these issues spur significantly oversized over-forecasts, e.g. when employing an epidemiological compartmental model for predictions.

Impact of organizational culture on healthcare supply chain resilience in Jordan: Moderating role of technology integration

This study aims to investigate the impact of organizational culture (i.e., rational, hierarchical, and group) on healthcare supply chain resilience (SCR) in Jordan. This paper further examines the moderating role of technology integration on the relationship between organizational culture and healthcare SCR. Cross-sectional research was conducted, and participants were recruited from different hospitals in Jordan. An electronic survey was employed to collect the responses from 304 participants, including senior professionals designated as doctors, nurses, ray technicians, physical therapists, procurement officers, pharmacists, and lab technicians with more than three years of work experience. There was no statistically significant influence of rational culture on healthcare SCR (p-value = 0.156) and an adverse impact of hierarchical culture on healthcare SCR (p-value = 0.030). Group culture had a statistically significant impact on healthcare SCR (p-value = 0.007). Technology integration had an influential moderating influence on the association between rational culture and healthcare SCR (p-value = 0.042) and the association between hierarchical culture and healthcare SCR (p-value = 0.0129). However, technology integration had no moderating influence on the association between group culture and healthcare SCR (p-value = 0.331). The analysis revealed that group culture has an influential impact on healthcare SCR, while hierarchical culture has a negative impact on healthcare SCR. Moreover, technological integration was observed to improve the beneficial influence of rational culture and the negative effects of hierarchical culture on healthcare SCR. However, the technology integration was not observed to moderate the relationship between group culture and healthcare SCR. Acknowledgment The author acknowledges all the associated personnel who, in any reference, contributed to the completion of this study.

Prioritizing Performance Indicators for the Circular Economy Transition in Healthcare Supply Chains

AbstractThe emergence of the circular economy (CE) paradigm is a key driver in steering industrial sectors towards sustainability. The formulation of a robust circularity strategy depends on a comprehensive assessment, which is closely related to the overarching goal of managing the transition to circularity. The initial phase of transition within the healthcare sector reinforces the need to seamlessly integrate CE principles. It is therefore imperative to define and carefully monitor indicators that will help assess and improve sustainability, operational efficiency, supply chain resilience and stakeholder satisfaction, including both consumers and patients. The primary objective of this research is to prioritize relevant performance indicators that will be critical in measuring the effectiveness of the transition to a circular economy within the healthcare supply chain. To achieve this objective, the study employs the Analytic Hierarchy Process (AHP), a well-established methodology known for its effectiveness in solving complex multi-criteria challenges. The AHP is used to prioritize performance indicators that facilitate the management of the circular economy transition in the healthcare supply chain. The focus is on improving the quality of care, optimizing delivery efficiency, and emphasizing environmental sustainability within the healthcare paradigm. The methodological framework includes the identification of key main criteria covering environmental, social, economic, and logistical dimensions. These criteria are further refined with the inclusion of 14 sub-criteria, resulting in a list of 16 key performance indicators (KPIs). Additionally, the study proposes an alternative business model advocating for the implementation of the Circular Supply Chain Operation Reference Model (circular SCOR). This model offers a perspective for rapid change in supply chain processes towards circular transition within the healthcare system. The final stage of the research involves verifying the results through sensitivity analysis and correlation mapping of the indicator results with the Circular SCOR model. This process helps organizations refine their performance measurement protocols, enhancing their capacity for effective evaluation and strategic decision-making within the circular economy framework. This comprehensive approach enables healthcare organizations to proactively contribute to a more sustainable and environmentally conscious future while maintaining a focus on quality care for patient well-being.

A-205 Evaluating the Cost and Importance of Supply Chain Resilience in the Clinical Laboratory

Abstract Background Recent pandemics, epidemics and outbreaks continually underscore the critical importance of resilient supply chains in healthcare, particularly in clinical laboratories where timely access to supplies is essential for patient care. Supply chain disruptions, whether due to global crises or localized challenges, can significantly impact laboratory operations, leading to delayed diagnoses, compromised patient outcomes, and increased costs. It is estimated that 70%-80% of a patients’ EMR is clinical laboratory results. Despite this, supply chain resilience in clinical laboratories remains an under-addressed issue and remains a buzzword. Methods To evaluate the cost and importance of supply chain resilience in the clinical laboratory, we conducted a comprehensive review and interviews with 9 Healthcare Supply Chain experts analyzing the impact of supply chain disruptions on laboratory operations and patient care. Data was also collected from a diverse range of clinical laboratories, including hospitals, independent labs, and research institutions, spanning different geographic regions as well as a survey of 50 Laboratory experts with a 50% response rate. Key metrics assessed included: -Frequency and duration of supply chain disruptions. -Financial costs incurred due to disruptions, including expenses related to expedited shipping, alternative sourcing, and inventory management. -Impact on laboratory workflow, turnaround times, and patient care outcomes. -Strategies employed to mitigate supply chain risks and enhance resilience. Results Our review revealed findings regarding the cost and importance of supply chain resilience in the clinical laboratory: -Supply chain disruptions were frequent, with 85% of laboratories experiencing at least one significant disruption in the past year and 100% in experienced disruptions 2022. -The average duration of disruptions was 2-3 weeks, leading to substantial delays in test processing and patient care. -Financial costs associated with disruptions averaged $50,000 per laboratory per annum, including expenses for rush orders, and premium-priced alternatives. -Common strategies employed were increased inventory or safety stocks, multi-vendor sourcing, and supply chain mapping. Conclusions The findings of this study underscore the critical importance of supply chain resilience in the clinical laboratory. Supply chain disruptions are not just inconveniences; they pose significant risks to patient safety, operational efficiency, and financial sustainability. Investing in supply chain resilience is imperative for laboratories to fulfill their mission of delivering timely and accurate patient results. To continue to enhance supply chain resilience, laboratories must adopt a proactive approach, leveraging data-driven insights and collaborative partnerships. This includes diversifying supplier networks and fostering closer collaboration between laboratory and procurement teams.

Machine Learning for Optimizing Macro-ergonomics in Pharmaceutical Supply Chain

This study endeavors to enhance the macro-ergonomics of pharmaceutical supply chains by introducing an innovative hybrid AI methodology, incorporating fuzzy data envelopment analysis (FDEA). A comprehensive case study is conducted to evaluate the efficiency of the pharmaceutical supply chain, focusing on macro-ergonomic work system assessment. This evaluation aims to identify design flaws contributing to communication delays between physicians and patients. The proposed integrated approach utilizes a hybrid AI framework, specifically FDEA, to accurately measure macro-ergonomic influences on the healthcare supply chain under uncertain conditions. The case study involves a prominent urban outpatient medical facility with 20 clinics, selecting 20 Decision-Making Units for a holistic perspective. Results uncover factors causing delays, emphasizing weak or absent feedback structures as critical elements affecting the healthcare supply chain’s effectiveness. In conclusion, the study recommends modifications to optimize the pharmaceutical supply chain, enhancing overall healthcare efficiency. The findings provide valuable insights for healthcare management, underscoring the crucial role of advanced AI methodologies in addressing complex challenges within healthcare supply chains.

Integrating risk management in implementing circular economy principles in the healthcare sector: a case study from Indonesia

Purpose The purpose of this study is to explore the integration of risk management and circular economy (CE) principles within the healthcare sector to promote sustainability and resilience. Specifically, the study aims to demonstrate how risk management can support the transition to a circular economy in healthcare supply chains. By integrating risk management practices with CE principles, healthcare organizations can identify potential risks and opportunities associated with circular initiatives. Design/methodology/approach This study adopts a qualitative research approach, using a case study methodology with semi-structured interviews conducted at primary care facilities to understand the application of CE principles in practice. The study uses fuzzy logic methods to assess and mitigate risks associated with strategies promoting CE principles. Additionally, key performance indicators are identified to evaluate the effectiveness and enhance the resilience of these strategies within healthcare supply chains. Findings The study highlights the critical role of robust risk management strategies in facilitating the transition to a circular economy within healthcare organizations. Primary care facilities, which are critical to frontline healthcare delivery, are particularly vulnerable to product shortages due to supply risks. This study focuses on critical protective equipment, specifically latex gloves and assesses operational risks, including supply, demand and environmental risks, using a fuzzy logic-based model. Import delays were found to be a moderate risk, typically occurring once a year. The research highlights critical KPIs for a successful CE transition within healthcare supply chains, such as on-time delivery and service quality, which are directly related to the risk of supply chain disruption. In addition, the study highlights the significant impact of other CE strategies on healthcare supply chains, including localized production and manufacturing, innovation in product development, reverse logistics, closed-loop supply chains and the adoption of lean principles. Practical implications This study provides valuable insights for healthcare organizations to optimize resource efficiency, reduce waste and promote circularity in their operations. By implementing the proposed solutions and focusing on the identified KPIs, organizations can develop strategies to achieve sustainability goals and enhance resilience in healthcare supply chains. Originality/value This study contributes to the literature by demonstrating the application of risk management in facilitating the transition to a circular economy in the healthcare sector. The use of fuzzy logic methodology offers a novel approach to assessing and mitigating risks associated with critical product failures in supply chain activities. The study’s findings provide practical guidance for healthcare organizations seeking to integrate circular economy principles and improve sustainability performance.

헬스케어 공급망 리스크 주요 이슈 분석: 뉴스기사를 중심으로

This study investigates the major risk issues and their causes in healthcare supply chains, using network analysis and qualitative analysis of news media publications, and then proposes response and operational strategies for managing healthcare supply chain risks. We divided our study into two time periods for a comparative analysis of key risk issues in different degrees of environmental uncertainty. The year 2020 marked the emergence of the COVID-19 pandemic. The first period of our analysis is four years covering 2016-2019, prior to COVID-19 disruptions. The second period is also four years during 2020-2023 when the full force of COVID-19 disruptions affected healthcare supply chains. The keywords used to collect news media publications were “healthcare,” “healthcare industry,” “healthcare services,” “hospital,” “health center,” and “medicine.” The results of the study indicated that the major risks experienced in healthcare supply chains were due to the following factors: the type of patients who needed healthcare services, care services provided (lab tests, treatment, prescriptions, etc.), care service methods used (surgery, utilization of medical devices), and examination and diagnostics (clinical kits, etc.). While these factors were identified as possible causes of risk in the healthcare supply chains involving procurement of supplies and raw materials, these risks tend to intensify in the increased disruption period (year 2020-2023). Managing these risk issues in the disruptive periods contributes significantly not only to the performance of healthcare organizations but also to the well-being of the society at large. This study offers theoretical implications in that it analyzes the causes of risks in the healthcare supply chains and provides a basis for a comparative analysis of the relationships of risk factors in healthcare supply chains during a normal environment and a very disruptive environment. From a practical perspective, this study suggests effective countermeasures for managing healthcare supply chain risks with examples that can be used as a guideline by healthcare executives, managers, and policy-makers of healthcare services.

The Optimization of the Pay-per-use Model for the Healthcare Supply Chain

The Optimization of the Pay-per-use Model for the Healthcare Supply Chain

Reimagining healthcare supply chains: a systematic review on digital transformation with specific focus on efficiency, transparency and responsiveness

PurposeThe purpose of this study is to comprehensively explore the impact of digitalization on healthcare supply chains (HcSCs). It seeks to understand how digital technologies enhance efficiency, transparency and responsiveness within these complex logistical systems. The study aims to provide a holistic view of the transformative potential of digitalization in the healthcare sector, with a particular focus on improving patient care and streamlining operational processes.Design/methodology/approachThis research employs a systematic review methodology, carefully curating a selection of 45 relevant articles from 66 articles rigorously screened using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to provide a holistic view. It follows established systematic review protocols, incorporating a meticulous search strategy and precise keyword selection. The chosen research design enables a comprehensive examination of the existing body of knowledge concerning digital platforms, real-time tracking technologies, transparency and responsiveness in the context of HcSCs.FindingsThe findings of this study emphasize the pivotal role of digital technologies in reshaping HcSCs. Digital platforms, real-time tracking systems and technological integrations substantially enhance efficiency, transparency and responsiveness. Data-driven decision-making, improved communication and agile responses to dynamic demands are key aspects. These findings underscore the transformative impact of digitalization on healthcare logistics, emphasizing the potential for streamlined operations, enhanced patient care and more efficient resource allocation.Research limitations/implicationsDespite the systematic methodology, this study is subject to certain limitations. It relies on existing literature, which may not cover the most recent developments in the rapidly evolving field of digital HcSCs. Furthermore, the study may be influenced by publication bias. The implications suggest the need for continued research to explore emerging digital technologies and their effects on healthcare logistics, ensuring that supply chains remain agile and responsive.Practical implicationsThe practical implications of this research are significant for HcSC managers with insights into digital technologies to enhance transparency and collaboration and improve resource visibility. The integration of data analytics can lead to more effective inventory management and demand forecasting. Blockchain (BC) technology can ensure transparent and secure transactions, fostering trust among stakeholders. For practitioners, this research offers actionable guidance for navigating the digital age, promoting operational efficiency and ensuring a consistent supply of essential medical products. Researchers can use these insights as a foundation for further exploration into the potential of digitalization in HcSCs.Social implicationsThe social implications of digitalization in HcSCs are far-reaching. They encompass improved patient care, as digital technologies enhance the efficiency, transparency and responsiveness of supply chains. This translates to better access to critical medical supplies, potentially reducing healthcare disparities and benefiting underserved populations. Enhanced patient safety is a significant social outcome, as transparent and secure transactions enabled by technologies like BC mitigate the risks associated with counterfeit medications. Furthermore, digitalization builds trust among stakeholders, promotes accountability and fosters resilient healthcare systems, which are capable of responding effectively to crises. It also has the potential to make healthcare more affordable, contributing to increased healthcare access and transparency in decision-making.Originality/valueThe originality and value of this study lie in its comprehensive synthesis of diverse findings related to digitalization in HcSCs. While prior studies have examined isolated facets of digital technology adoption, this research provides a comprehensive overview. It contributes to a deeper understanding of the transformative potential of digitalization within the healthcare sector, offering practical approaches to enhance patient care and streamline operations.

Drug Tracing System Using Blockchain Technology

Healthcare supply chains are complicated networks that span various departmental and geographical limits and provide the foundation for many benefits that are necessary for everyday life .The difficulties of this systems can result in contaminations such as erroneous data and lack of clarity and poor data origin. one issue of present supply chain restrictions is the production of counterfeit drugs, which not only has negative impact on people health but also has negative impact on financial status of pharmaceutical business. A recent research emphasised the importance of a well founded end-to-end track and trace system for health care supply chains .The smart contract ensures data provenance and gives all participants access to a secure unalterable transaction history .Moreover, it eliminates the need for intermediaries we give a high-level overview of thesystem architecture and algorithms that form the basis of the key elements of our proposed solution. we test and analyse the system to find how effectively it can enhance traceabilityinside health care supply chains before providing a cost and security analysis Keywords— Drug Counterfeiting , Supply Chain, Blockchain, Traceability, Healthcare, Trust, Securit

Impact pathways: putting workers front and center in addressing workforce shortages in intellectual disability care

PurposeAddressing workforce shortages in operations and supply chain management (OSCM) necessitates adaptive measures by both individuals and organizations, with a pivotal role played by Human Resources (HR). This impact pathway delves into how healthcare organizations can effectively manage workforce shortages, informed by HR practices. Through an in-depth understanding of healthcare organizations, the authors pinpoint challenges and concerns linked to workforce shortages. Pathways are proposed to stimulate future OSCM research and collaboration, leveraging innovative and creative methods from the HR field.Design/methodology/approachData was collected from various representatives from healthcare organizations to explore how healthcare organizations for people with intellectual disabilities address the challenges stemming from contemporary workforce shortages.FindingsThree pathways were outlined to address workforce shortages in healthcare supply chains, utilizing intellectual disability care as a representative example. These pathways comprise optimizing the potential of the current workforce, illustrating innovative HR practices for enhancing their performance, and proposing strategies for retaining these valuable workers.Originality/valueDespite its potential, the HR domain remains relatively underdeveloped within OSCM research. The authors show how HR practices can potentially mitigate impending workforce shortages. While utilizing intellectual disability care as a representative example, this paper proposes that the impact pathways identified can be extended to various other healthcare settings.