Healthcare Supply Chain Management under COVID-19 Settings: The Existing Practices in Hong Kong and the United States

Lau, Yui‐yip; Dulebenets, Maxim A.; Yip, Ho-Tung; Tang, Yuk Ming

doi:10.3390/healthcare10081549

Cited by 21 publications

(6 citation statements)

References 45 publications

(70 reference statements)

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“…During the COVID-19 period, supply-based services, which include family planning and vaccinations, were more volatile than what models had predicted. The pandemic’s impact on global healthcare systems and supply chain management has been profound—the outbreak of COVID-19 created one of the most vital supply chain disruptions of the past 50 years ( 38 ). A number of major healthcare facilities (e.g., distribution centers, factories, and warehouses) were situated in COVID-19 quarantine zones in China, Italy, India, the United States, Japan, Russia, and Australia ( 39 ), which resulted in a severe scarcity of critical medical supplies.…”

Section: Discussionmentioning

confidence: 99%

Estimating the effects of COVID-19 on essential health services utilization in Uganda and Bangladesh using data from routine health information systems

Angeles,

Silverstein,

Ahsan

et al. 2023

Front. Public Health

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BackgroundSince March 2020, the coronavirus disease 2019 (COVID-19) pandemic has been a major shock to health systems across the world. We examined national usage patterns for selected basic, essential health services, before and during the COVID-19 pandemic in Uganda and Bangladesh, to determine whether COVID-19 affected reporting of service utilization and the use of health services in each country.MethodsWe used routine health information system data since January 2017 to analyze reporting and service utilization patterns for a variety of health services. Using time series models to replicate pre-COVID-19 trajectories over time we estimated what levels would have been observed if COVID-19 had not occurred during the pandemic months, starting in March 2020. The difference between the observed and predicted levels is the COVID-19 effect on health services.ResultsThe time trend models for Uganda and Bangladesh closely replicated the levels and trajectories of service utilization during the 38 months prior to the COVID-19 pandemic. Our results indicate that COVID-19 had severe effects across all services, particularly during the first months of the pandemic, but COVID-19 impacts on health services and subsequent recovery varied by service type. In general, recovery to expected levels was slow and incomplete across the most affected services.ConclusionOur analytical approach based on national information system data could be very useful as a form of surveillance for health services disruptions from any cause leading to rapid responses from health service managers and policymakers.

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Section: Discussionmentioning

confidence: 99%

Estimating the effects of COVID-19 on essential health services utilization in Uganda and Bangladesh using data from routine health information systems

Angeles,

Silverstein,

Ahsan

et al. 2023

Front. Public Health

View full text Add to dashboard Cite

show abstract

“…Participants also reported that the shortages of essential testing supplies and equipment amid the high testing demands elevated their stress levels. The pandemic affected the demand and supply of healthcare supplies and equipment, causing disruptions to the supply chain [39]. Participants noted that the lack of necessary supplies impeded their work, leading to delays in testing and diagnoses, compromising patient care.…”

Section: Pandemic Stressorsmentioning

confidence: 99%

Hidden and Understaffed: Exploring Canadian Medical Laboratory Technologists’ Pandemic Stressors and Lessons Learned

Dignos,

Khan,

Gardiner-Davis

et al. 2023

Healthcare

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(1) Background: The COVID-19 pandemic has highlighted the critical role of medical laboratory technologists (MLTs) in the healthcare system. Little is known about the challenges MLTs faced in keeping up with the unprecedented demands posed by the pandemic, which contributed to the notable staff shortage in the profession. This study aims to identify and understand the stressors of MLTs in Canada and the lessons learned through their lived experiences during the pandemic. (2) Methods: In this descriptive qualitative study, we conducted five semi-structured focus groups with MLTs working during the pandemic. The focus group sessions were audio-recorded and then transcribed verbatim. Thematic analysis was used to inductively code data and identify themes. (3) Results: A total of 27 MLTs across Canada participated in the study. Findings highlighted four key themes: (i) unexpected challenges navigating through the uncertainties of an ever-evolving pandemic; (ii) implications of staff shortage for the well-being of MLTs and quality of patient care; (iii) revealing the realities of the hidden, yet indispensable role of MLTs in predominantly non-patient-facing roles; and (iv) leveraging insights from the COVID-19 pandemic to enhance healthcare practices and preparedness. (4) Conclusion: The study provides in-depth insight into the experiences of MLTs across Canada during the pandemic. Based on our findings, we provide recommendations to enhance the sustainability of the laboratory workforce and ensure preparedness and resiliency among MLTs for future public health emergencies, as well as considerations as to combating the critical staff shortage.

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“…A limitation is that there is no meaningful symbolic representation of the learned patterns, and the interpretation of the learned routine is done manually. The complexity of home healthcare under pandemic situations such as COVID-19 has been addressed in [31,32]. Routing and scheduling caregivers to visit patients' homes considering economic, environmental, and social criteria is rather difficult.…”

Section: Related Workmentioning

confidence: 99%

Identification of Daily Living Recurrent Behavioral Patterns Using Genetic Algorithms for Elderly Care

et al. 2022

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A person’s routine is a sequence of activities of daily living patterns recurrently performed. Sticking daily routines is a great tool to support the care of persons with dementia, and older adults in general, who are living in their homes, and also being useful for caregivers. As state-of-the-art tools based on self-reporting are subjective and rely on a person’s memory, new tools are needed for objectively detecting such routines from the monitored data coming from wearables or smart home sensors. In this paper, we propose a solution for detecting the daily routines of a person by extracting the sequences of recurrent activities and their duration from the monitored data. A genetic algorithm is defined to extract activity patterns featuring small differences that relate to the day-to-day contextual variations that occur in a person’s daily routine. The quality of the solutions is evaluated with a probabilistic-based fitness function, while a tournament-based strategy is employed for the dynamic selection of mutation and crossover operators applied for generating the offspring. The time variability of activities of daily living is addressed using the dispersion of the values of duration of that activity around the average value. The results are showing an accuracy above 80% in detecting the routines, while the optimal values of population size and the number of generations for fitness function evolution and convergence are determined using multiple linear regression analysis.

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Healthcare Supply Chain Management under COVID-19 Settings: The Existing Practices in Hong Kong and the United States

Cited by 21 publications

References 45 publications

Estimating the effects of COVID-19 on essential health services utilization in Uganda and Bangladesh using data from routine health information systems

Estimating the effects of COVID-19 on essential health services utilization in Uganda and Bangladesh using data from routine health information systems

Hidden and Understaffed: Exploring Canadian Medical Laboratory Technologists’ Pandemic Stressors and Lessons Learned

Identification of Daily Living Recurrent Behavioral Patterns Using Genetic Algorithms for Elderly Care

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