Allocation Of Care Resources Research Articles

Utilization of Hospice Resources in Adult Intensive Care Units: A Comparison Between Users and Non-Users

The application of palliative care is limited and challenging in intensive care units (ICUs) because of complex factors such as time constraints and unpredictable disease progression. Although research results and international consensus stress the early use of palliative care, utilization remains low, resulting in increased risks of ineffective medical care and poor quality of death. Improving this situation requires a comprehensive understanding of the palliative condition in ICUs. This study was designed to investigate the utilization of hospice resources in adult ICUs and to compare this utilization between users and non-users. This retrospective correlation study recruited cases from the adult ICU database of a medical center in northern Taiwan between June and July 2022. Descriptive statistics, independent t-test and chi-square were used to analyze the data. A total of 1,181 records were analyzed, including 458 (38.8%) females and 723 (61.2%) males. Two hundred and seventeen cases (18.4%) used hospice resources. Although 124 (10.4%) of the 1181 cases were identified as "in urgent need of hospice resources" (i.e., died within 30 days of ICU admission), 25 (20.2%) did not use these resources. Significant differences between the urgent-need cases who did and did not use hospice resources were found in terms of age, disease type, degree of frailty, cardiac arrest, infection, state of consciousness, intubation and tracheostomy status, inotropic and vasopressor medication, renal replacement, ECMO placement, delirium, and Acute Physiology and Chronic Health Evaluation III and Sequential Organ Failure Assessment Scores. The roughly 20% of ICU patients in urgent needs of palliative care who did not utilize palliative care resources highlight the needs for continued discussion to better assist patients on palliative care decision-making. The findings show multifaceted differences between those who did and did not access palliative care. Future studies should design and test strategies to facilitate the identification of palliative care needs and ensure the effective allocation of palliative care resources in ICUs.

Race and Ethnicity and Emergency Department Discharge Against Medical Advice

Although discharges against medical advice (DAMA) are associated with greater morbidity and mortality, little is known about current racial and ethnic disparities in DAMA from the emergency department (ED) nationally. To characterize current patterns of racial and ethnic disparities in rates of ED DAMA. This cross-sectional study used data from the Nationwide Emergency Department Sample on all hospital ED visits made between January to December 2019 in the US. The main outcome was odds of ED DAMA for Black and Hispanic patients compared with White patients nationally and in analysis adjusted for sociodemographic factors. Secondary analysis examined hospital-level variation in DAMA rates for Black, Hispanic, and White patients. The study sample included 33 147 251 visits to 989 hospitals, representing the estimated 143 million ED visits in 2019. The median age of patients was 40 years (IQR, 22-61 years). Overall, 1.6% of ED visits resulted in DAMA. DAMA rates were higher for Black patients (2.1%) compared with Hispanic (1.6%) and White (1.4%) patients, males (1.7%) compared with females (1.5%), those with no insurance (2.8%), those with lower income (<$27 999; 1.9%), and those aged 35 to 49 years (2.2%). DAMA visits were highest at metropolitan teaching hospitals (1.8%) and hospitals that served greater proportions of racial and ethnic minoritized patients (serving ≥57.9%; 2.1%). Odds of DAMA were greater for Black patients (odds ratio [OR], 1.45; 95% CI, 1.31-1.57) and Hispanic patients (OR, 1.16; 95% CI, 1.04-1.29) compared with White patients. After adjusting for sociodemographic characteristics (age, sex, income, and insurance status), the adjusted OR (AOR) for DAMA was lower for Black patients compared with the unadjusted OR (AOR, 1.18; 95% CI, 1.09-1.28) and there was no difference in odds for Hispanic patients (AOR, 1.03; 95% CI, 0.92-1.15) compared with White patients. After additional adjustment for hospital random intercepts, DAMA disparities reversed, with Black and Hispanic patients having lower odds of DAMA compared with White patients (Black patients: AOR, 0.94 [95% CI, 0.90-0.98]; Hispanic patients: AOR, 0.68 [95% CI, 0.63-0.72]). The intraclass correlation in this secondary analysis model was 0.118 (95% CI, 0.104-0.133). This national cross-sectional study found that Black and Hispanic patients had greater odds of ED DAMA than White patients in unadjusted analysis. Disparities were reversed after patient-level and hospital-level risk adjustment, and greater between-hospital than within-hospital variation in DAMA was observed, suggesting that Black and Hispanic patients are more likely to receive care in hospitals with higher DAMA rates. Structural racism may contribute to ED DAMA disparities via unequal allocation of health care resources in hospitals that disproportionately treat racial and ethnic minoritized groups. Monitoring variation in DAMA by race and ethnicity and hospital suggests an opportunity to improve equitable access to health care.

Social care data in the UK; current landscape, challenges, and future recommendations

ABSTRACT Objectives Social care in the United Kingdom (UK) refers to care provided due to age, illness, disability, or other circumstances. Social care provision offers an intermediary step between hospital discharge and sufficient health for independent living, which subsequently helps with National Health Service (NHS) bed capacity issues. UK Health Technology Assessments (HTAs) do not typically include social care data, possibly due to a lack of high-quality, accessible social care data to generate evidence suitable for submissions. Methods We identified and characterized secondary sources of UK social care data suitable for research (as of 2021). Sources were identified and profiled by desk research, supplemented by information from custodians and data experts. Results We identified twenty-one sources; six high potential (three national, three regional data sources), five future potential, seven limited potential, and three not considered further (outdated or lacking social care data). Conclusion Despite identifying numerous sources of social care data across the UK, opportunities and access for researchers appeared limited and could be improved. This would facilitate a deeper understanding of the clinical and economic burden of disease, the impact of medicines and vaccines on social care, enable better-informed HTA submissions and more efficient allocation of NHS and local council social care resources.

Machine learning prediction of hospital discharge disposition for inpatients with acute ischemic stroke following mechanical thrombectomy in the United States

Background and purposePredicting patient recovery and discharge disposition following mechanical thrombectomy remains a challenge in patients with ischemic stroke. Machine learning offers a promising prognostication approach assisting in personalized post-thrombectomy care plans and resource allocation. As a large national database, National Inpatient Sample (NIS), contain valuable insights amenable to data-mining. The study aimed to develop and evaluate ML models predicting hospital discharge disposition with a focus on demographic, socioeconomic and hospital characteristics. Materials and methodsThe NIS dataset (2006–2019) was used, including 4956 patients diagnosed with ischemic stroke who underwent thrombectomy. Demographics, hospital characteristics, and Elixhauser comorbidity indices were recorded. Feature extraction, processing, and selection were performed using Python, with Maximum Relevance - Minimum Redundancy (MRMR) applied for dimensionality reduction. ML models were developed and benchmarked prior to interpretation of the best model using Shapley Additive exPlanations (SHAP). ResultsThe multilayer perceptron model outperformed others and achieved an AUROC of 0.81, accuracy of 77 %, F1-score of 0.48, precision of 0.64, and recall of 0.54. SHAP analysis identified the most important features for predicting discharge disposition as dysphagia and dysarthria, NIHSS, age, primary payer (Medicare), cerebral edema, fluid and electrolyte disorders, complicated hypertension, primary payer (private insurance), intracranial hemorrhage, and thrombectomy alone. ConclusionMachine learning modeling of NIS database shows potential in predicting hospital discharge disposition for inpatients with acute ischemic stroke following mechanical thrombectomy in the NIS database. Insights gained from SHAP interpretation can inform targeted interventions and care plans, ultimately enhancing patient outcomes and resource allocation.

French mental health care system: Analysis of care utilisation patterns and the case for a stepped care approach

ContextIn France, spending on mental health and psychiatric care, in proportion to GDP, is close to the EU average. However, there are complaints that the French system is overwhelmed and potentially underfunded. ObjectiveTo describe the utilisation of psychiatric and mental health care in different settings to consider the appropriateness of care provision and resource allocation. MethodsFor the year 2018, several national databases on the use of all type of psychiatric care provision (full and part-time hospitalisations, private and public, public ambulatory care, private office-based psychiatrists) were cross-tabulated with diagnosis categories for different age groups and illness severity in order to assess the use of resources and evaluate the appropriateness of resource allocation. ResultsA sizable proportion of patients with mild and moderate mental disorders are treated in psychiatric care whilst there is insufficient continuity of care for patients with severe disorders, who are not adequately followed up after discharge from hospitals. This contributes to increase the rate of re-hospitalisations, the use of emergency departments, and longer stays in hospitals. ConclusionThe several components of the French mental health care system are used inappropriately, not only in geographical terms but also in terms of service use. We argue that strengthening the access to affordable psychotherapy and the implementation of a stepped-care approach could contribute to solve this issue.

Spatial coupling relationship between older adults and elderly care resources in the Yangtze River Delta.

The imbalance between supply and demand of elderly care resources in the Yangtze River Delta is increasing. By the older adult agglomeration, spatial cluster analysis, hotspot analysis, and coupling coordination model, this study explores the spatial coupling relationship between older adults and elderly care resources in the Yangtze River Delta in 2020 from the perspective of a supply-and-demand balance. The results demonstrate that: (1) population aging is mainly in the moderate aging stage, followed by the primary aging stage; (2) there are significant spatial differences in elderly care resources on the urban scale in the Yangtze River Delta; and (3) elderly care resources and the older adults in the Yangtze River Delta are mostly highly coupled. However, Nantong, with the highest degree of aging, has a serious mismatch in life service resources and ecological environment resources. The social security resources and medical resources of provincial capital cities with low aging are mismatched. Medical and health resources in underdeveloped areas are seriously mismatched. The social security resources are barely matched in Shanghai. A path for optimizing the spatial allocation of elderly care resources is proposed. This research offers a decision-making reference for coordinating elderly care resources distribution.

Projected Global Trends in Hematological Malignancies: Incidence, Mortality, and Disability-Adjusted Life Years from 2020 to 2030

Introduction: Hematological malignancies encompass a diverse group of conditions affecting the blood and its components, including anemia, bleeding disorders, hematologic malignancies, and inherited blood disorders. These disorders have a substantial impact on global health, posing challenges for health care systems worldwide. Understanding the future trends in the incidence, mortality, and disability-adjusted life years (DALYs) associated with hematological malignancies is crucial for effective health care planning and resource allocation. This study was designed to project the global trends in hematological malignancies from 2020 to 2030 and provide insights into the anticipated burden of these conditions. Methods: Estimated annual percentage changes (EAPCs) were utilized to forecast trends in the incidence, deaths, and DALYs associated with hematological malignancies between 2020 and 2030. EAPCs were derived using generalized additive models and data from the Global Burden of Disease study spanning from 1990 to 2019. The analysis involved utilizing a comprehensive and systematic approach, incorporating data from multiple sources, including population-based surveys, disease registries, health care databases, and vital statistics. Age-specific and sex-specific incidence rates, mortality rates, and DALYs were calculated for each specific hematological disorder. Advanced statistical modeling techniques, including time series analysis and predictive modeling, were employed to estimate future trends. The projections took into account demographic changes, epidemiological transitions, and advancements in medical technology. Results: The projections for the next decade indicate a varied trend in the age-standardized incidence, mortality, and disability-adjusted life year (DALY) rates of hematological malignancies globally. By 2030, the incidence rates per 100,000 individuals are expected to rise to 0.045 for multiple myeloma (EAPC = 1.70%), 0.016 for leukemia (EAPC = 0.79%), 0.012 for non-Hodgkin lymphoma (EAPC = 1.65%), and 0.002 for Hodgkin lymphoma (EAPC = 0.55%). The global age-standardized mortality rates associated with hematological malignancies show a differential trend. The mortality rates per 100,000 population are projected to increase to 0.016 for multiple myeloma (EAPC = 1.68%) and 0.008 for leukemia (EAPC = 0.40%). On the other hand, a decrease in mortality rate is expected for Hodgkin lymphoma (EAPC = -0.13%), while non-Hodgkin lymphoma exhibits a rise in mortality rate to 0.007 (EAPC = 1.31%). Similarly, the DALY rates per 100,000 population are expected to increase to 0.242 for multiple myeloma (EAPC = 1.54%) and 0.174 for non-Hodgkin lymphoma (EAPC = 0.90%). In contrast, the DALY rates for leukemia and Hodgkin lymphoma are projected to decrease to 0.248 (EAPC = -0.62%) and 0.023 (EAPC = -0.50%), respectively. In terms of geographical distribution, China is expected to face a considerable surge in the total number of hematological malignancy cases, with an estimate of approximately 859,692 cases by 2030. Globally, the total number of hematological malignancy cases is projected to reach approximately 4,634,937. The projected total number of hematological malignancy cases by 2030 across different levels of SDI are as follows: 1,113,313 cases in high-SDI areas, 1,004,403 cases in high-middle SDI areas, 475,496 cases in low-SDI areas, 795,475 cases in low-middle SDI areas, and 1,244,424 cases in middle-SDI areas. Conclusions: The projected global trends in hematological malignancies highlight the urgent need for comprehensive strategies to address this growing burden. Prevention and early detection programs should be strengthened to mitigate the increasing incidence of these malignancies . Accurate diagnosis, appropriate management, and access to affordable treatments are crucial for improving patient outcomes. Health care systems must allocate adequate resources, including health care infrastructure, skilled health care professionals, and specialized services, to effectively manage the growing impact of hematological malignancies . Furthermore, collaboration among health care providers, researchers, policy-makers, and patient advocacy groups is essential to develop and implement evidence-based strategies that can alleviate the future challenges posed by hematological malignancies.

Optimization of Nursing Care Resource Allocation in an Aging Population Based on Combinatorial Optimization Algorithm

Abstract This paper first considers population aging as a breakthrough, analyzes the demand for long-term care due to population aging, and classifies the models and characteristics of long-term care. Secondly, the combinatorial optimization algorithm and its classical cases are analyzed, and a care resource allocation system is built based on the solution set performance metrics and multi-objective combinatorial optimization algorithm for an aging population society. In city A, a research experiment examines the elderly population and the allocation of nursing care resources. The results show that the Gini coefficient of the population distribution of nursing institutions is 0.027 and the Gini coefficient of the population distribution of the number of institutional beds is 0.296, both of which are less than 0.3, thus indicating that the overall structure of the current social nursing resource allocation is relatively fair.

Development of a Scoring Method Based on a Chest CT Scan to Determine the Outcomes of COVID-19 Patients.

Introduction As COVID-19 shifts from pandemic urgency to endemic management, healthcare systems are faced with the evolving challenge of providing optimized care and adept resource allocation in this evolving landscape of the disease. However, the timely management and accurate assessment of disease severity remains a cornerstone of effective treatment. This study presents a pioneering scoring system, based on the primary chest CT scan findings, to predict patient outcomes and to equip clinicians with a tool that can expedite decision-making. Method A retrospective cohort study was conducted involving 406 confirmed COVID-19 cases referred to two of our hospitals in Tehran, between February and April 2020. Radiographic and CT scan data were sourced from the imaging archive system and evaluated by a certified radiologist. We devised distinct severity scores for CT findings, demographic factors, and clinical indicators. These were synthesized into a comprehensive severity score to forecast critical patient outcomes, such as mortality, ICU admission, intubation, or extended hospitalization. Of the total cases, 161 (39.7%) were classified as severe, while 245 (60%) fell into the low or moderate severity category. Results The mean score of demographic, CT scan, and clinical characteristics was significantly higher for those in the severe COVID-19 than the non-severe group. The cutoff score for predicting the outcomes in COVID-19 patients for demographic, clinical, and chest CT scan factors was 2.5, 9.5, and 8.5, respectively. Multivariate analysis indicated that each unit increase in these scores elevated the odds of fatal outcomes by 24%, 2.8%, and 12%, respectively. Then, using the comprehensive severity score, which is the sum of the above scores, we further predicted the disease severity. Conclusion The findings suggest that our innovative scoring system, based on initial chest CT scan findings, serves as a robust predictor of COVID-19 outcomes.

Spatiotemporal evolution and influencing factors of the allocation of social care resources for the older adults in China

BackgroundThe reasonable allocation of social care resources for the older adults is a key measure to actively respond to population aging. This study aims to evaluate the evolutionary trend, spatial differences and influencing factors of the social elderly care resources (SECR) allocation in China.MethodsThis study constructed a comprehensive index system consisting of three dimensions: material resources, human resources and financial resources, to measure the level of SECR in mainland China. The Kernel density estimation was used to reveal the dynamic evolution trend, and Dagum Gini Coefficient and its decomposition method were used to investigate the equity of SECR allocation. Spatial panel regression models were used to analyze the influencing factors of the allocation of SECR.ResultsThe level of SECR is rising from 0.197 in 2013 to 0.208 in 2019. The middle-high- and high-level areas of SECR were mainly distributed in the eastern and western China. The Gini coefficient of SECR decreased from 0.262 in 2013 to 0.249 in 2019. Per capita GDP, the proportion of social welfare expenditure in GDP and the proportion of the tertiary industry in GDP have significant positive effects on the allocation of SECR. Population aging and the development of service industry exhibit significant negative spatial spillover effects on the allocation of SECR.ConclusionsThe fairness of the allocation of SECR in China has been improved, while the spatial distribution is imbalanced. Economic development, fiscal input and the development of service industry have significant positive effects while population aging has significant negative effects on the SECR allocation.

Relative Jitter Measurement Methodology and Comparison of Clocking Resources Jitter in Artix 7 FPGA

Phase jitter is one of the crucial factors in modern digital electronics, determining the reliability of a design. This paper presents a novel approach to designing a jitter comparison system and methodology for FPGA chips using a Tapped Delay Line (TDL)—commonly used to implement a Time-to-Digital Converter (TDC). The design and its revision utilizing latches replacing some of the flip-flops are presented and discussed, with potential further improvements. A minimal temperature influence is verified and presented. The methodology of automated relative jitter measurements is discussed. Multiple different FPGA clock signal path configurations are measured, and the results are presented. The influence of clock routing is identified as critical when MMCM or PLL modules are omitted. It is demonstrated that with careful resource and routing allocation, the clock signal’s jitter performance does not have to be deteriorated by the absence of jitter filtering blocks. The proposed technique was implemented and verified and relative jitter performance was measured in the AMD/Xilinx Artix 7 35T FPGA platform.

The Use of Parenteral Nutrition and Disparities in Its Allocation Following Traumatic Injury

IntroductionSevere traumatic injury requires rapid and extensive deployment of resources to save the lives of the critically injured. The sequelae of traumatic injuries frequently require extensive intervention obligating patients to a complicated recovery process devoid of meaningful nutrition. In this setting, parenteral nutrition (PN) is key in enabling appropriate wound healing, recovery, and rehabilitation. We sought to examine the use of PN in adult trauma management and to highlight any disparities in the utilization of PN in adult trauma patients. MethodsWe queried the 2017-2019 Trauma Quality Improvement Program (TQIP) for adult patients (aged > 18 y) who sustained blunt or penetrating traumatic injuries and received PN as part of their hospitalization. We compared time to PN administration based on demographics. We then used a multivariable logistic regression model to identify factors associated with the use of PN. We hypothesized that PN would be less commonly employed in the uninsured and minority groups. ResultsWe identified 2,449,498 patients with sufficient data for analysis. Of these, 1831 patients were treated with PN. On univariate analysis, PN patients were more commonly male (74.7% PN versus 60.2% non-PN; P < 0.001). PN use was more frequent in the Black population (24.3% PN versus 15.5% non-PN; P < 0.001) and less frequent in the White population (72.7% PN versus 81.2% non-PN; P < 0.001). PN use was also much more common among patients covered by Medicaid. Penetrating trauma was over twice as common among PN recipients relative to non-PN patients (% PN versus % non-PN). PN patients had higher injury severity scores (ISSs), more intensive care unit days, longer hospitalizations, and increased mortality compared to non-PN patients. PN patients were half as likely to discharge home and twice as likely to discharge to a long-term care facility. Multivariable analysis including age, race, trauma mechanism, primary payer, and ISS, demonstrated an association of PN use with increasing age (OR 1.01, P < 0.001), cases of penetrating trauma (odds ratio [OR], 2.47; P < 0.001), and patients with high ISS (OR, 0.1.06; P < 0.001). There was decreased use in Uninsured patient (OR, 0.54; P < 0.001). ConclusionsPN use following traumatic injury is rarely required. Patients treated with PN typically have a resource-intense hospital course. More severe injuries, penetrating trauma, and increased age are more likely to result in PN use. Variations in PN use are apparent based on insurance payer, further examination into allocation of hospital and intensive care resources, as it pertains to patient socioeconomic status, is warranted in light of these findings.

Economic evaluation of prenatal screening for fetal aneuploidies in Thailand.

Historically, there has been a lack of cost-effectiveness data regarding the inclusion of universal non-invasive prenatal testing (NIPT) for trisomy 21, 18, and 13 in the benefit package of the Universal Health Coverage (UHC) in Thailand. Therefore, this study aimed to perform the cost-benefit analysis of prenatal screening tests and calculate the budget impact that would result from the implementation of a universal NIPT program. A decision-tree model was employed to evaluate cost and benefit of different prenatal chromosomal abnormalities screenings: 1) first-trimester screening (FTS), 2) NIPT, and 3) definitive diagnostic (amniocentesis). The comparison was made between these screenings and no screening in three groups of pregnant women: all ages, < 35 years, and ≥ 35 years. The analysis was conducted from societal and governmental perspectives. The costs comprised direct medical, direct non-medical, and indirect costs, while the benefit was cost-avoidance associated with caring for children with trisomy and the loss of productivity for caregivers. Parameter uncertainties were evaluated through one-way and probabilistic sensitivity analyses. From a governmental perspective, all three methods were found to be cost-beneficial. Among them, FTS was identified as the most cost-beneficial, especially for pregnant women aged ≥ 35 years. From a societal perspective, the definitive diagnostic test was not cost-effective, but the other two screening tests were. The most sensitive parameters for FTS and NIPT strategies were the productivity loss of caregivers and the incidence of trisomy 21. Our study suggested that NIPT was the most cost-effective strategy in Thailand, if the cost was reduced to 47 USD. This evidence-based information can serve as a crucial resource for policymakers when making informed decisions regarding the allocation of resources for prenatal care in Thailand and similar context.

The Attitude of Egyptian Patients with Autoimmune and Rheumatic Diseases towards Telemedicine.

Background and Objectives: The use of telemedicine (TM) has recently undergone rapid growth and proliferation. Professional stakeholders anticipate that TM will aid in the efficient allocation of limited resources in rheumatology care. The aim of the study was to evaluate the acceptance and willingness of Egyptian patients with autoimmune and rheumatic diseases (ARDs) to incorporate TM into rheumatological care and to assess their requirements and concerns regarding TM. Materials and Methods: A cross-sectional questionnaire-based study was conducted among Egyptian patients with ARDs. The questionnaire covered sociodemographic characteristics, clinical and therapeutic data, attitudes, barriers, and motivators towards TM. Results: The study included 189 patients with ARDs, with a mean age of 37 years (SD = 11.71), and 88.4% were females. Participants were divided into two groups based on their acceptance of TM: the non-acceptant group (133, 70.4%) and the acceptant group (56, 29.6%). There was a significant difference in educational level (p = 0.001), chronic kidney and heart disease (p = 0.008 and 0.014, respectively) and hydroxychloroquine administration (p = 0.037) between the two groups. During the coronavirus disease 2019 (COVID-19) pandemic, 96 (50.8%) of participants used virtual rheumatology consultations, mainly using WhatsApp (64.6%). Approximately 87% would require assistance in operating TM technology. The preference for direct conversation with the rheumatologist and the need for physical examination were the main barriers to teleconsultation. Conclusions: TM is opposed by the vast majority of Egyptian patients with ARDs. They are concerned since it does not include a physical examination and prevents them from undergoing additional procedures such as ultrasound and blood testing. The majority of Egyptian patients with ARDs need help using TM technology, which is the most significant barrier to the spread of TM.

Physician and administrator experience of preparing to implement Ontario's intensive care unit Triage Emergency Standard of Care during the COVID-19 pandemic: a qualitative study.

As the COVID-19 pandemic created a surge in demand for critical care resources, the province of Ontario, Canada, released the Adult Critical Care Clinical Emergency Standard of Care for Major Surge (Emergency Standard of Care [ESoC]), a triage framework to guide the allocation of critical care resources in the expectation that intensive care units would be overwhelmed. Our aim was to understand physicians' and administrators' experiences and perceptions of planning to implement the ESoC, and to identify ways to improve critical care triage processes for future pandemics. We conducted semistructured qualitative interviews with critical care, emergency and internal medicine physicians, and hospital administrators from various Ontario health regions who were involved in their hospital's or region's ESoC implementation planning. Interviews were conducted virtually between April and October 2021. We analyzed the data using thematic analysis. We conducted interviews with 11 physicians and 10 hospital administrators representing 9 health regions. We identified 4 themes regarding participants' preparation to implement the ESoC: infrastructure to enable effective triage implementation; social, medical and political supports to enable effective triage implementation; moral dimensions of triage implementation; and communication of triage results. Participants outlined administrative and implementation-related improvements that could be provided at the provincial level, such as billing codes for ESoC. They also suggested improving ethical supports for the usability and quality of the ESoC (e.g., designating an ethicist in each region), and ways to improve the efficiency and usability of the tools for assessing short-term mortality risk (e.g., create information technology solutions such as a dashboard). The implementation of a jurisdiction-level triage framework poses moral challenges for a health care system, but it also requires dedicated infrastructure, as well as institutional supports. Lessons learned from Ontario's process to prepare for ESoC implementation, as well as participants' suggestions, can be used for planning for current and future pandemics.

Triage Procedures for Critical Care Resource Allocation During Scarcity

During the COVID-19 pandemic, many US states issued or revised pandemic preparedness plans guiding allocation of critical care resources during crises. State plans vary in the factors used to triage patients and have faced criticism from advocacy groups due to the potential for discrimination. To analyze the role of comorbidities and long-term prognosis in state triage procedures. This cross-sectional study used data gathered from parallel internet searches for state-endorsed pandemic preparedness plans for the 50 US states, District of Columbia, and Puerto Rico (hereafter referred to as states), which were conducted between November 25, 2021, and June 16, 2023. Plans available on June 16, 2023, that provided step-by-step instructions for triaging critically ill patients were categorized for use of comorbidities and prognostication. Prevalence and contents of lists of comorbidities and their stated function in triage and instructions to predict duration of postdischarge survival. Overall, 32 state-promulgated pandemic preparedness plans included triage procedures specific enough to guide triage in clinical practice. Twenty of these (63%) included lists of comorbidities that excluded (11 of 20 [55%]) or deprioritized (8 of 20 [40%]) patients during triage; one state's list was formulated to resolve ties between patients with equal triage scores. Most states with triage procedures (21 of 32 [66%]) considered predicted survival beyond hospital discharge. These states proposed different prognostic time horizons; 15 of 21 (71%) were numeric (ranging from 6 months to 5 years after hospital discharge), with the remaining 6 (29%) using descriptive terms, such as long-term. In this cross-sectional study of state-promulgated critical care triage policies, most plans restricted access to scarce critical care resources for patients with listed comorbidities and/or for patients with less-than-average expected postdischarge survival. This analysis raises concerns about access to care during a public health crisis for populations with high burdens of chronic illness, such as individuals with disabilities and minoritized racial and ethnic groups.

Spatial Equality of Urban Care Facilities from the Perspective of Refinement: An Example from Changchun, China

Care facilities are the mainstay of social services for the elderly. As the trend of empty nesting among elderly families intensifies due to the aging population, it is becoming difficult for families to take on the responsibility of caring for the elderly on their own, and the elderly need more formal care to be provided by society. The contradiction between the lag in the construction of care facilities and the growth in the social demand for elderly care has been highlighted, and the spatial equality of care facilities is an important means of achieving an optimal allocation of resources for elderly care. In this paper, we use the two-step floating catchment method to measure the spatial accessibility of care facilities from a fine-grained perspective, using big data, including mobile phone signaling data and points of interest. Then, we use the Gini coefficient to analyze the equality of the spatial allocations of different types of urban care facilities. The results of the study show that, first, the spatial equality of care facilities is good in terms of the Gini coefficient, but the overall spatial accessibility of care facilities is at a relatively low level compared to that in developed cities. This means that the layout of Changchun’s care facilities is good, but there is insufficient service capacity. Second, the spatial accessibility of residential care facilities is characterized by a gradual decline, with high levels in the core and low levels in the periphery. Fewer facilities are located in the peripheral areas of the city, and spatial accessibility is at a lower level, a characteristic different from that seen in cities with a higher level of economic development, such as Beijing. Third, the spatial accessibility of community care facilities showed a polycentric, contiguous distribution. The effect of the study scale on the spatial accessibility of community care facilities was more pronounced, with large scales obscuring the high values of the spatial accessibility of community care facilities in peripheral areas. Fourth, Changchun has better overall equality of care facilities, with differences in the different types and areas of care provided. The spatial balance of care facilities in the core area is better than that observed in other regions. In conclusion, this paper underscores the value of big data, such as mobile phone signaling data, in supporting refined urban research. Furthermore, our comprehensive analysis of social care facility equality can inform policy making and spatial planning.

Functional connectomic profile correlates with effective anterior thalamic stimulation for refractory epilepsy

BackgroundDeep brain stimulation of the anterior nucleus of the thalamus (ANT-DBS) is an effective treatment for refractory epilepsy; however, seizure outcome varies among individuals. Identifying a reliable noninvasive biomarker to predict good responders would be helpful. ObjectivesTo test whether the functional connectivity between the ANT-DBS sites and the seizure foci correlates with effective seizure control in refractory epilepsy. MethodsWe performed a proof-of-concept pilot study of patients with focal refractory epilepsy receiving ANT-DBS. Using normative human connectome data derived from 1000 healthy participants, we investigated whether intrinsic functional connectivity between the seizure foci and the DBS site was associated with seizure outcome. We repeated this analysis controlling for the extent of seizure foci, distance between the seizure foci and DBS site, and using functional connectivity of the ANT instead of the DBS site to test the contribution of variance in DBS sites. ResultsEighteen patients with two or more seizure foci were included. Greater functional connectivity between the seizure foci and the DBS site correlated with more favorable outcome. The degree of functional connectivity accounted for significant variance in clinical outcomes (DBS site: |r| = 0.773, p < 0.001 vs ANT-atlas: |r| = 0.715, p = 0.001), which remained significant when controlling for the extent of the seizure foci (|r| = 0.773, p < 0.001) and the distance between the seizure foci and DBS site (|r| = 0.777, p < 0.001). Significant correlations were independent of variance in the DBS sites (|r| = 0.148, p = 0.57). ConclusionThese findings suggest that functional connectomic profile is a potential reliable non-invasive biomarker to predict ANT-DBS outcomes. Accordingly, the identification of ANT responders could decrease the surgical risk for patients who may not benefit and optimize the cost-effective allocation of health care resources.

Highly multiplexed targeted sequencing strategy for infectious disease surveillance

BackgroundGlobal efforts to characterize diseases of poverty are hampered by lack of affordable and comprehensive detection platforms, resulting in suboptimal allocation of health care resources and inefficient disease control. Next generation sequencing (NGS) can provide accurate data and high throughput. However, shotgun and metagenome-based NGS approaches are limited by low concentrations of microbial DNA in clinical samples, requirements for tailored sample and library preparations plus extensive bioinformatics analysis. Here, we adapted molecular inversion probes (MIPs) as a cost-effective target enrichment approach to characterize microbial infections from blood samples using short-read sequencing. We designed a probe panel targeting 2 bacterial genera, 21 bacterial and 6 fungi species and 7 antimicrobial resistance markers (AMRs).ResultsOur approach proved to be highly specific to detect down to 1 in a 1000 pathogen DNA targets contained in host DNA. Additionally, we were able to accurately survey pathogens and AMRs in 20 out of 24 samples previously profiled with routine blood culture for sepsis.ConclusionsOverall, our targeted assay identifies microbial pathogens and AMRs with high specificity at high throughput, without the need for extensive sample preparation or bioinformatics analysis, simplifying its application for characterization and surveillance of infectious diseases in medium- to low- resource settings.

Using measures of race to make clinical predictions: Decision making, patient health, and fairness

The use of race measures in clinical prediction models is contentious. We seek to inform the discourse by evaluating the inclusion of race in probabilistic predictions of illness that support clinical decision making. Adopting a static utilitarian framework to formalize social welfare, we show that patients of all races benefit when clinical decisions are jointly guided by patient race and other observable covariates. Similar conclusions emerge when the model is extended to a two-period setting where prevention activities target systemic drivers of disease. We also discuss non-utilitarian concepts that have been proposed to guide allocation of health care resources.