Dynamic Hospital Resource Scheduling During Pandemics with Stochastic Optimization

How should water resources be allocated for shale gas development? An exploratory study in China

Learning Systems as a Path to Improve ICU Staff Wellbeing

The Role of the Long-Term Acute Care Hospital Following Critical Illness-Has the Coronavirus Disease 2019 Pandemic Demonstrated Their Usefulness or Emphasized Their Downside?

The Coronavirus Response in India – World's Largest Lockdown

1Physician, Peachtree Orthopaedic Clinic, Atlanta, GA, USA X. A. Duralde, Peachtree Orthopaedic Clinic, 2045 Peachtree Drive, Suite 700, Atlanta, GA 30309 USA, Email: [email protected] This CORR Insights® is a commentary on the article "What was the Prevalence of COVID-19 in Asymptomatic Patients Undergoing Orthopaedic Surgery in One Large United States City Mid-pandemic?" by Gutman and colleagues available at: DOI: 10.1097/CORR.0000000000001697. The author certifies that neither he, nor any members of his immediate family, has funding or commercial associations (consultancies, stock ownership, equity interest, patent/licensing arrangements, etc.) that might pose a conflict of interest in connection with the submitted article. All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research® editors and board members are on file with the publication and can be viewed on request. The opinions expressed are those of the writer, and do not reflect the opinion or policy of CORR® or The Association of Bone and Joint Surgeons®.

The COVID-19 pandemic has been associated with global surges in need for hospital-based and other healthcare resources, as well as shortages in vital items such as ICU beds, mechanical ventilators, and personal protective equipment (Fig. 1) (1). During the initial waves of the COVID-19 pandemic, several countries experienced a shortage of mechanical ventilators (2). Decision-making on triage and rationing of scarce resources during a crisis can lead to critical adjustments to what would otherwise be considered standard of care. For patients who are fully ventilator-dependent, decisions surrounding initiation or termination of mechanical ventilation can acutely mean the difference between life and death (2). Although health system surge capacities (both for acute and routine care needs) can be essential to pandemic preparedness (1), it is also of paramount importance that policies on crisis standards of care be informed by both evidence and ongoing reevaluation.Figure 1.: Depiction of mechanical ventilator, ICU bed, and other resources.In this issue of Critical Care Medicine, Keller at al (3) provide key insights regarding the use of a preintubation Sequential Organ Failure Assessment (SOFA) score to predict COVID-19 mortality. In a multicenter, retrospective, large database cohort study of over 15,000 mechanically ventilated COVID-19 patients at 86 U.S. healthcare systems, the authors used electronic health record data to assess the predictive capacity of the SOFA score for inhospital mortality in COVID-19 patients. The authors found that the SOFA score demonstrated poor discriminant accuracy for inhospital mortality in mechanically ventilated patients. The observed area under the receiver operating curve (AUC) for the SOFA score to predict inhospital mortality was 0.66 (95% CI, 0.65–0.67), generally considered poor accuracy (the authors used the cutoffs of less than 0.7 as poor accuracy, 0.7–0.8 as moderate, 0.8–0.9 as good, and greater than 0.9 as excellent) (4). The addition of comorbidities did not substantially improve the predictive model, and age alone performed better for predicting inhospital mortality than the SOFA score. Even when reviewing ventilated patients with COVID-19 who survived hospitalization, the SOFA score poorly predicted those who required long-term acute care. This study adds notable value for several reasons. The findings add multi-institutional external validity, with a large sample size, to an increasing number of smaller studies questioning the utility of using the SOFA score in this context (5,6). In a 2021 research letter published in JAMA, Raschke et al (5) conducted a retrospective review of 675 adult patients with COVID pneumonia requiring mechanical ventilation across 18 ICUs in the southwestern United States. Similar to the findings from Keller et al (3), the authors of the JAMA research letter found poor discriminant accuracy for the SOFA score to predict hospital mortality or discharge to hospice (AUC, 0.59; 95% CI, 0.55–0.63). In both studies, the authors appropriately questioned the value of using a SOFA scoring system not designed for this purpose that distributes points across several domains (i.e., neurologic, cardiovascular, pulmonary, renal, hepatic, and coagulation). The combined scientific rigor and multidisciplinary nature of the study by Keller et al (3) add to the potential for this new study to inform important health policy decisions. The authors of the Keller et al (3) study have affiliations spanning both an academic medical institution, the National Institutes of Health Clinical Center, the National Institute of Allergy and Infectious Disease, and the Frederick National Laboratory for Cancer Research. The authors report that, at the time of their study, several U.S. states with crisis standard-of-care guidelines still had ventilator triage algorithms featuring the SOFA score. In this regard, the findings are particularly timely and relevant for reassessment of crisis standards during a time when ventilators may be more available. Although the study provides valuable findings, it is not without limitations. The authors did not assess outcomes that go beyond hospital discharge. Although inhospital mortality is an important outcome, many other relevant considerations should be taken into account in making these challenging decisions, including resource consumption, quality of life, functional outcomes, long-term sequelae, healthcare disparities, and health equity. As such, the use of SOFA in crisis standards of care may exacerbate racial and ethnic disparities in resource allocation, and a deliberate approach that ensures incorporation of a health equity perspective is key (7,8). There is added value in looking at these important considerations as primary outcomes, similar to how inhospital mortality was assessed for this particular study. There are also limitations related to how certain factors were adjusted, or not adjusted for, in the current analysis. Although the authors performed an additional sensitivity analysis to account for patients who had "an International Classification of Diseases, 10th Edition Major Operating Room procedure code on the same day as intubation (to account for potential preoperative rather than critical illness-related intubation)," there are many other nonoperating room and/or minor procedures that frequently require endotracheal intubation during a hospitalization, including some of the procedures done by interventional radiologists, cardiologists, gastroenterologists, and other procedural subspecialists. Other large database studies have been able to be more granular regarding diagnostic and therapeutic procedures in their assessment of outcomes (9,10). The authors also did not adjust for patients who were transferred to another hospital at the end of their index hospitalization, which may have ultimately led to an inhospital mortality (just in a different hospital). Other large database studies looking at mortality have been able to track and account for these types of hospital transfers (11,12). Although these latter limitations may have been inherent to a combination of the data available to the authors and the selected study design, it is nevertheless encouraging that the authors provided sensitivity analyses spanning several different considerations, all of which were consistent with the primary results. COVID-19 has generated a renewed focus on the concept of pandemic preparedness as an important topic of discussion at the highest levels of healthcare and beyond (1,13). It is important that crisis standards of care be informed by a representative group of multidisciplinary experts reviewing the latest evidence and considering a range of important outcomes and lessons learned from past experience. Similar to how patient safety has been referred to as "…[not] a preoccupation of the past […] not a problem that has been solved, but rather an ongoing requirement" (14,15), preparation for the ever-changing needs of COVID-19, variants, long-term effects, and new developments should be subject to ongoing reappraisal based on evolving evidence.

POINT: Is Considering Social Determinants of Health Ethically Permissible for Fair Allocation of Critical Care Resources During the COVID-19 Pandemic? Yes

The participation in the FIT-based colorectal cancer screening programme and subsequent compliance to colonoscopy after a positive FIT test was only slightly affected during the COVID-19 pandemic in Denmark.

In a telecommunication network, routing and wavelength assignment (RWA) is the problem of finding lightpaths for incoming connection requests. When facing a dynamic traffic, greedy assignment of lightpaths to incoming requests based on predefined deterministic policies leads to a fragmented network that cannot make use of its full capacity because of stranded bandwidth. At this point, service providers try to recover the capacity via a defragmentation process. We study this setting from two perspectives: (i) while granting the connection requests via the RWA problem and (ii) during the defragmentation process by lightpath rerouting. For both problems, we present the first two-stage stochastic integer programming model incorporating incoming request uncertainty to maximize the expected grade of service. We develop a decomposition-based solution approach, which uses various relaxations of the problem and a newly developed problem-specific cut family. Simulation of two-stage policies for a variety of instances in a rolling-horizon framework of 52 stages shows that our stochastic models provide high-quality solutions when compared with traditionally used deterministic ones. Specifically, the proposed provisioning policies yield improvements of up to 19% in overall grade of service and 20% in spectrum saving, while the stochastic lightpath rerouting policies grant up to 36% more requests, using up to just 4% more bandwidth spectrum.Summary of Contribution: For handling the intrinsic uncertainty of demand in the telecommunications industry, this paper proposes novel stochastic models and solution methodology for two fundamental problems in telecommunications at operational level: (i) routing and wavelength assignment (RWA) and (ii) lightpath rerouting problem. Despite the vast literature on the RWA problem, stochastic optimization has not been considered as a viable solution for resource allocation in optical networks. We propose two-stage stochastic programming models for both problems and design efficient decomposition-based solution methods that use various relaxations of the models and a new family of cutting planes. Our extensive and rigorous numerical experiments show the significant merit of incorporating uncertainty into decision making, as well as the effectiveness of the decomposition framework and our newly designed family of cuts in enhancing the solvability of both models. This work opens new avenues to explore where the powerful stochastic programming literature can be leveraged to make operational decisions in telecommunications problems, a field that currently relies mostly on deterministic and heuristic solution methods.

IntroductionThe COVID-19 pandemic overwhelmed healthcare systems with severe shortages in hospital resources such as ICU beds, specialized doctors, and respiratory ventilators. In this situation, reducing COVID-19 readmissions could potentially maintain hospital capacity. By employing machine learning (ML), we can predict the likelihood of COVID-19 readmission risk, which can assist in the optimal allocation of restricted resources to seriously ill patients.MethodsIn this retrospective single-center study, the data of 1225 COVID-19 patients discharged between January 9, 2020, and October 20, 2021 were analyzed. First, the most important predictors were selected using the horse herd optimization algorithms. Then, three classical ML algorithms, including decision tree, support vector machine, and k-nearest neighbors, and a hybrid algorithm, namely water wave optimization (WWO) as a precise metaheuristic evolutionary algorithm combined with a neural network were used to construct predictive models for COVID-19 readmission. Finally, the performance of prediction models was measured, and the best-performing one was identified.ResultsThe ML algorithms were trained using 17 validated features. Among the four selected ML algorithms, the WWO had the best average performance in tenfold cross-validation (accuracy: 0.9705, precision: 0.9729, recall: 0.9869, specificity: 0.9259, F-measure: 0.9795).ConclusionsOur findings show that the WWO algorithm predicts the risk of readmission of COVID-19 patients more accurately than other ML algorithms. The models developed herein can inform frontline clinicians and healthcare policymakers to manage and optimally allocate limited hospital resources to seriously ill COVID-19 patients.

ObjectivesThe COVID-19 pandemic has highlighted insufficiencies and gaps within healthcare systems globally. In most countries, including high-income countries, healthcare facilities were over-run and occupied with too few resources beyond capacity....

Background With increasing national focus on reducing inappropriate antimicrobial use, state and national regulatory mandates require hospitals to develop robust antimicrobial stewardship programs (ASP). Methods BJC HealthCare is a 13 hospital healthcare system serving the St. Louis, mid-Missouri, and Southern Illinois region and includes adult and pediatric academic medical centers, as well as community and critical access hospitals. In 2015, BJC system leaders engaged relevant clinical and executive stakeholders at each hospital to champion formation of a multidisciplinary system ASP Council. A comprehensive gap analysis was performed to assess current stewardship resources and activities. BJC system clinical leads facilitated the development of hospital specific leadership support statements, identification of hospital pharmacy and medical leaders, and all mandated educational components. To facilitate tracking, reporting and improvement activities, a robust antimicrobial use data dashboard was created. Each hospital has a dedicated ASP team that is supported by the system clinical leads. Hospital learnings are shared at monthly system ASP meetings allowing for broad dissemination. Results By leveraging system resources, all 13 BJC HealthCare hospitals met all Joint Commission requirements by January 2017. BJC’s model of ASP allows for the development of broad-based stewardship activities including development of education modules for patients and providers, and clinical decision support tools while allowing individual hospitals to implement activities based on local needs and resource availability. Local hospital teams have developed treatment guidelines, targeted antibiotic pharmacy review, “handshake” stewardship models, and allergy testing protocols. Central support of local hospital ASP has resulted in a 7.6% system decrease in tracked antimicrobial use, including a 16.5% reduction in quinolone usage. Additionally, the C. difficilestandardized infection ratio decreased from 1.08 to 0.622 since program initiation. Conclusion Despite significant differences in hospital resources, a system-supported ASP model focused on implementing the CDC core elements can result in significant reductions in antimicrobial use. Disclosures J. Newland, Merck: Grant Investigator, Research grant; Allergan: Grant Investigator, Research grant

IntroductionThe COVID-19 pandemic has changed health systems across the world, both in general hospitals and in oncology institutes or centres.For cancer specialists, particularly breast cancer (BC), the COVID-19 pandemic represents a combination of challenges since the hospital resources and staff have become more limited; this has obliged oncology specialists to seek a consensus and establish which patients with BC require more urgent attention and which patients can wait until there is a better control of this pandemic. The health system in Latin America has some special characteristics; in some of the countries, there are shortages which limit access to several specialities (surgery, clinical oncology and radiotherapy) in some regions.ObjectiveAfter a systematic review of the most recent literature regarding the management of BC during the COVID-19 pandemic, the main objective is to understand the position of the different Latin American Societies of Mastology in terms of available alternatives for the treatment of BC.MethodsAfter carrying out a comprehensive and exhaustive search of the most recent guides on the management of BC during the COVID-19 pandemic, the board members of the Latin American Federation of Mastology invited, via email, different specialists, all experts in BC care, to complete an anonymous survey online.The survey was distributed between 30 and 10 May 2020. The survey included 27 questions on four topics: demographic information, consultations, imaging and treatment of BC.The questionnaire was sent and then distributed to various health specialists including breast surgeons, clinical oncologists, radiation oncologists and radiologists via the Presidents of the different Latin American Societies of Mastology in 18 countries. The results are summarised as tallies based on the number of responses to each question.ResultsA total of 499 responses were received. The majority of the respondents were males (275 (55.11%)); 290 participants were over 45 years (58.11%).The questionnaire presented those surveyed with three possible answers (agree, disagree and neither agree nor disagree). The results reflect that there was consensus in the majority of situations presented. Only seven questions revealed disagreement among those responding. The results are presented as recommendations.ConclusionThe management of patients with BC presents unique challenges during the current world health situation produced by COVID-19 pandemic. Breast care specialists (surgical oncologists, breast care clinicians, clinical oncologists, radiation oncologists and radiologists) from 18 countries in Central and South America submitted through their responses and recommendations for the treatment of BC during the COVID-19 pandemic.

Rationale: Though the United States has the highest number of ICU beds per capita in the world, the regional distribution of these beds is variable. Rural areas have 1% of American ICU beds despite having 16% of the country's population. Telehealth is frequently promoted as a tool that can augment care for the critically ill in rural communities. Yet, ICU telehealth still requires clinicians at the bedside who are able to provide critical care. We sought to examine telemedicine within rural ICUs in the context of potential workforce shortages related to the COVID-19 pandemic. Methods: We identified all hospitals with ICUs in Michigan using the 2018 American Hospital Association annual survey database and internet searches. Within each hospital, an ICU physician or nurse leader was surveyed between April 6, 2020 and May 8, 2020. At that time, the state of Michigan had the fifth highest total of COVID-19 hospitalizations within the country. Participants were asked about current telehealth utilization in the ICU. Participants were also asked to rate their concern on a 4-point Likert scale regarding exceeding existing ICU capacity and ICU staffing capabilities due to the pandemic. Results: Of the 28 rural hospitals in Michigan, 14 were surveyed (response rate 50%). Among responding hospitals, 12 (86%) had fewer than 11 ICU beds and an average pre-COVID-19 census of fewer than 4 patients. At the time of the survey, ten hospitals (71%) reported using ICU telehealth support, of which two used telehealth providers exclusively overnight. Of the four hospitals without telehealth, two planned to add telehealth in response to the pandemic. In the context of the COVID-19 pandemic, 11 hospitals (79%) reported concern about exceeding their ICU capacity, and 12 hospitals (86%) planned to create more ICU beds. The majority of rural hospitals worried about impending ICU workforce shortages, with 78% of hospitals concerned about having enough nurses, 64% about having enough respiratory therapists, and 50% about having enough physicians as a result of the pandemic. Conclusions: At the onset of the COVID-19 pandemic, most rural hospitals in Michigan utilized ICU telehealth support in some capacity. Despite broad use of telemedicine, rural hospitals remained concerned about exceeding ICU capacity and a lack of ICU nurses, respiratory therapists, and physicians. Expansion of existing telehealth infrastructures within rural hospitals may improve access to critical care clinicians virtually but would not ease concerns related to capacity and workforce shortages, particularly among ICU-trained nurses.

Background The COVID-19 pandemic has had a significant impact on the healthcare system, resulting in overall reduction in access to healthcare services, including the suspension of screening programs and postponement of surgeries and medical treatments. The aim of this study was to evaluate the effects of the pandemic on breast cancer positivity from cases received at a laboratory in São Paulo, Brazil. Methods A retrospective analysis of a database from a pathology laboratory in São Paulo, Brazil, was performed during the 2017-2023 period and classified as following: pre-pandemic (January 2017-February 2020), pandemic (March 2020 - April-2022), and post-pandemic (May 2022-December 2023). Cases were classified as negative or positive for malignancies. Positive anatomopathological examinations (breast biopsies and surgical specimens) considered primary, metastatic mesenchymal or endothelial malignancies. The Mann-Kendall test was used to evaluate the trend, and the PACF (Partial Autocorrelation Function) correlogram was used to analyze historical memory for definition of the autoregressive model. The augmented Dickey-Fuller hypothesis test was applied to analyze whether the series is stationary or not, and the first differences test was applied. The ARIMA model was used for the estimates (1,1,1). Statistics were performed using the gretl software and pymannkendall library in the Python language. Results A total of 74,973 samples were evaluated during the 2017-2023 period. In the three-year pre-pandemic period, 32,644 tests were recorded, with an average of 29.34% positive cases. From the analysis of the pre-pandemic time series, there was a positive trend towards an increase in cases (p < 0.0001, z=6.1360, Tau=0.6955). In a non-pandemic scenario, from March 2020 to February 2021, the number of new tests expected would be 11,535; however, in the pandemic period, only 8,904 were observed, a 22.81% reduction on expected cases. According to the historical average positivity rate in the pre-pandemic period, the expected and observed total were, respectively, 3,384 and 2,566 positive cases for malignancy. Conclusions This study reveals a significant decrease of approximately 22.81% in new breast anatomopathological diagnoses during the COVID-19 pandemic in a laboratory in São Paulo, Brazil. For comparison purposes, we identified a 24.17% of missed opportunities on diagnoses of new malignancy-positive cases, compared to the pre-pandemic period. These findings highlight the need for strategies to mitigate the negative effects of the pandemic on the early detection and treatment of breast cancer.