skip to main content


Title: Minimization of Drug Shortages in Pharmaceutical Supply Chains: A Simulation-Based Analysis of Drug Recall Patterns and Inventory Policies
The drug shortage crisis in the last decade not only increased health care costs but also jeopardized patients’ health across the United States. Ensuring that any drug is available to patients at health care centers is a problem that official health care administrators and other stakeholders of supply chains continue to face. Furthermore, managing pharmaceutical supply chains is very complex, as inevitable disruptions occur in these supply chains (exogenous factors), which are then followed by decisions members make after such disruptions (internal factors). Disruptions may occur due to increased demand, a product recall, or a manufacturer disruption, among which product recalls—which happens frequently in pharmaceutical supply chains—are least studied. We employ a mathematical simulation model to examine the effects of product recalls considering different disruption profiles, e.g., the propagation in time and space, and the interactions of decision makers on drug shortages to ascertain how these shortages can be mitigated by changing inventory policy decisions. We also measure the effects of different policy approaches on supply chain disruptions, using two performance measures: inventory levels and shortages of products at health care centers. We then analyze the results using an approach similar to data envelopment analysis to characterize the efficient frontier (best inventory policies) for varying cost ratios of the two performance measures as they correspond to the different disruption patterns. This analysis provides insights into the consequences of choosing an inappropriate inventory policy when disruptions take place.  more » « less
Award ID(s):
1638302
NSF-PAR ID:
10128720
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Complexity
Volume:
2018
ISSN:
1076-2787
Page Range / eLocation ID:
1 to 14
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Reverse logistics has been gaining recognition in practice (and theory) for helping companies better match supply with demand, and thus reduce costs in their supply chains. In this paper, we study reverse logistics from the perspective of a supply chain in which each location can initiate multiple flows of product. Our first objective is to jointly optimize ordering decisions pertaining to regular, reverse and expedited flows of product in a stochastic, multi-stage inventory model of a logistics supply chain, in which the physical transformation of the product is completed at the most upstream location in the system. Due to those multiple flows of product, the feasible region for the problem acquires multi-dimensional boundaries that lead to the curse of dimensionality. To address this challenge, we develop a different solution method that allows us to reduce the dimensionality of the feasible region and, subsequently, identify the structure of the optimal policy. We refer to this policy as a nested echelon base-stock policy, as decisions for different product flows are sequentially nested within each other. We show that this policy renders the model analytically and numerically tractable. Our results provide actionable policies for firms to jointly manage three different product flows in their supply chains, and allow us arrive at insights regarding the main drivers of the value of reverse logistics. One of our key findings is that, when it comes to the value generated by reverse logistics, demand variability (i.e., demand uncertainty across periods) matters more than demand volatility (i.e., demand uncertainty within each period). This is because, in the absence of demand variability, it is effectively never optimal to return product upstream, regardless of the level of inherent demand volatility. Our second objective is to extend our analysis to product transforming-supply chains, in which product transformation is allowed to occur at each location. In such a system, it becomes necessary to keep track of both the location and stage of completion of each unit of inventory, so that the number of state and decisions variables increases with the square of the number of locations in the system. To analyze such a supply chain, we first identify a policy that provides a lower bound on the total cost. Then, we establish a special decomposition of the objective cost function that allows us to propose a novel heuristic policy. We find that the performance gap of our heuristic policy relative to the lower-bounding policy averages less than 5% across a range of parameters and supply chain lengths. 
    more » « less
  2. Ghate, A ; Krishnaiyer, K. ; Paynabar, K. (Ed.)
    Maintaining an appropriate staffing level is essential to providing a healthy workplace environment at nursing homes and ensuring quality care among residents. With the widespread Covid-19 pandemic, staff absenteeism frequently occurs due to mandatory quarantine and providing care to their inflicted family members. Even though some of the staff show up for work, they may have to perform additional pandemic-related protection duties. In combination, these changes lead to an uncertain reduction in the quantity of care each staff member able to provide in a future shift. To alleviate the staff shortage concern and maintain the necessary care quantity, we study the optimal shift scheduling problem for a skilled nursing facility under probabilistic staff shortage in the presence of pandemic-related service provision disruptions. We apply a two-stage stochastic programming approach to our study. Our objective is to assign staff (i.e., certified nursing aids) to shifts to minimize the total staffing cost associated with contract staff workload, the adjusted workload for the changing resident demand, and extra workload due to required sanitization. Thus, the uncertainties considered arise from probabilistic staff shortage in addition to resident service need fluctuation. We model the former source of uncertainty with a geometric random variable for each staffer. In a proof-of-the-concept study, we consider realistic COVID-19 pandemic response measures recommended by the Indiana state government. We extract payment parameter estimates from the COVID-19 Nursing Home Dataset publicly available by the Centers for Medicare and Medicaid Services (CMS). We conclude with our numerical experiments that when a skilled nursing facility is at low risk of the pandemic, the absenteeism rate and staff workload increase slightly, thus maintaining the current staffing level can still handle the service disruptions. On the other hand, under high-risk circumstances, with the sharp increase of the absence rate and workload, a care facility likely needs to hire additional full-time staff as soon as possible. Our research offers insights into staff shift scheduling in the face of uncertain staff shortages and service disruption due to pandemics and prolonged disasters. 
    more » « less
  3. Throughout history, urban agriculture practitioners have adapted to various challenges by continuing to provide food and social benefits. Urban gardens and farms have also responded to sudden political, economic, ecological, and social crises: wartime food shortages; urban disinvestment and property abandonment; earthquakes and floods; climate-change induced weather events; and global economic disruptions. This paper examines the effects on, and responses by, urban farms and gardens to the COVID-19 pandemic. The paper is based on data collected in the summer of 2020 at the onset of the pandemic when cities were struggling with appropriate responses to curb its spread. It builds on an international research project (FEW-meter) that developed a methodology to measure material and social benefits of urban agriculture (UA) in five countries (France, Germany, Poland, UK and USA) over two growing seasons, from a Food-Energy-Water nexus perspective. We surveyed project partners to ascertain the effects of COVID-19 on those gardens and farms and we interviewed policy stakeholders in each country to investigate the wider impacts of the pandemic on UA. We report the results with respect to five key areas: (1) garden accessibility and service provision during the pandemic; (2) adjustments to operational arrangements; (3) effects on production; (4) support for urban farms and gardens through the pandemic; and (5) thoughts about the future of urban agriculture in the recovery period and beyond. The paper shows that the pandemic resulted in multiple challenges to gardens and farms including the loss of ability to provide support services, lost income, and reductions in output because of reduced labor supply. But COVID-19 also created several opportunities: new markets to sell food locally; more time available to gardeners to work in their allotments; and increased community cohesion as neighboring gardeners looked out for one another. By illustrating the range of challenges faced by the pandemic, and strategies to address challenges used by different farms and gardens, the paper illustrates how gardens in this pandemic have adapted to become more resilient and suggests lessons for pandemic recovery and longer-term planning to enable UA to respond to future public health and other crises. 
    more » « less
  4. null (Ed.)
    Background The COVID-19 pandemic has caused several disruptions in personal and collective lives worldwide. The uncertainties surrounding the pandemic have also led to multifaceted mental health concerns, which can be exacerbated with precautionary measures such as social distancing and self-quarantining, as well as societal impacts such as economic downturn and job loss. Despite noting this as a “mental health tsunami”, the psychological effects of the COVID-19 crisis remain unexplored at scale. Consequently, public health stakeholders are currently limited in identifying ways to provide timely and tailored support during these circumstances. Objective Our study aims to provide insights regarding people’s psychosocial concerns during the COVID-19 pandemic by leveraging social media data. We aim to study the temporal and linguistic changes in symptomatic mental health and support expressions in the pandemic context. Methods We obtained about 60 million Twitter streaming posts originating from the United States from March 24 to May 24, 2020, and compared these with about 40 million posts from a comparable period in 2019 to attribute the effect of COVID-19 on people’s social media self-disclosure. Using these data sets, we studied people’s self-disclosure on social media in terms of symptomatic mental health concerns and expressions of support. We employed transfer learning classifiers that identified the social media language indicative of mental health outcomes (anxiety, depression, stress, and suicidal ideation) and support (emotional and informational support). We then examined the changes in psychosocial expressions over time and language, comparing the 2020 and 2019 data sets. Results We found that all of the examined psychosocial expressions have significantly increased during the COVID-19 crisis—mental health symptomatic expressions have increased by about 14%, and support expressions have increased by about 5%, both thematically related to COVID-19. We also observed a steady decline and eventual plateauing in these expressions during the COVID-19 pandemic, which may have been due to habituation or due to supportive policy measures enacted during this period. Our language analyses highlighted that people express concerns that are specific to and contextually related to the COVID-19 crisis. Conclusions We studied the psychosocial effects of the COVID-19 crisis by using social media data from 2020, finding that people’s mental health symptomatic and support expressions significantly increased during the COVID-19 period as compared to similar data from 2019. However, this effect gradually lessened over time, suggesting that people adapted to the circumstances and their “new normal.” Our linguistic analyses revealed that people expressed mental health concerns regarding personal and professional challenges, health care and precautionary measures, and pandemic-related awareness. This study shows the potential to provide insights to mental health care and stakeholders and policy makers in planning and implementing measures to mitigate mental health risks amid the health crisis. 
    more » « less
  5. Adolescence is a time when patients are approaching autonomy, both developmentally and legally. Yet they are still minors and are likely to encounter contradictions between situations in which they are treated as children and ones in which they are treated as adults. Being able to access their medical information may enable adolescents to take on a participatory role in their health care. However, federal policy, state law, and community norms are not consistent regarding adolescent healthcare and privacy. For example, in some regions and under some circumstances, adolescents may have consent and privacy rights similar to those of adults, with the right to make some, or all, of their own sensitive medical decisions privately. In other cases, parental notification is the norm, or guidance is unclear or lacking. In the absence of national guidelines, medical centers encounter serious challenges when developing policies about adolescent access to medical records via patient portals. The American Academy of Pediatrics has made recommendations, but these are not binding. To explore diversity in adolescent privacy policies and identify common approaches, we are conducting a qualitative study with key informants from different types of medical organizations in different regions of the country. The main objective is to identify diversity in adolescent privacy features within the patient portal. Another objective is to enumerate the factors involved in making portal access decisions. A third objective is to identify the potential need for more formalized guidance and standards on privacy features within the patient portal 
    more » « less