Probability Of Admission Research Articles

End-stage heart failure patients in ICU: the importance of advance planning and effective communication.

During the disease trajectory, patients with advanced heart failure are often hospitalised with a high probability of admission to the intensive care setting. Using a case study, this article explores the care given to a patient with decompensated heart failure in an intensive care unit (ICU). It will discuss the significance of holistic assessment and effective symptom management, in particular the research related to breathlessness management. The importance of effective communication within the ICU multidisciplinary team, including with the patient/family will be explored, as the ICU environment can often lead to communication breakdown, patients being unable to voice their wishes and over-medicalisation. The effectiveness of early involvement of the palliative care team in ICU will be examined, including the use of tools such advance care planning and a treatment escalation plan and whether use of these can enable a better patient and family experience at the end of life. The role of palliative care champions will be discussed.

Optical circuit switched three-stage twisted-folded Clos-network design model guaranteeing admissible blocking probability

Some data center networks have already started to use optical circuit switching (OCS) with potential performance benefits, including high capacity, low latency, and energy efficiency. This paper addresses a switching network design to maximize the network radix, i.e., the number of terminals connected to the network under the condition that a specified number of identical switches with the size N×N and the maximum admissible blocking probability are given. Previous work presented a two-stage twisted and folded Clos network (TF-Clos) with a blocking probability guarantee for OCS, which has a larger network radix than TF-Clos with a strict-sense non-blocking condition. Expanding the number of stages allows for enhancing the network radix. This paper proposes a model designing an OCS three-stage TF-Clos structure with a blocking probability guarantee to increase the network radix compared to the two-stage TF-Clos. We formulate the problem of obtaining the network configuration that maximizes the network radix as an optimization problem. We conduct an algorithm based on an exhaustive search to obtain a feasible solution satisfying the constraints of the optimization problem. This algorithm identifies the structure with the largest network radix in non-increasing order to avoid unnecessary searches. Numerical results show that the proposed model achieves a larger network radix than the two-stage model.

Socioeconomic inequity in the utilization of healthcare among people with eating disorders in Australia.

Little is known about socioeconomic equity in access to healthcare among people with eating disorders in Australia. This study aims to measure the extent of inequity in eating disorder-related healthcare utilization, analyze trends, and explore the sources of inequalities using New South Wales (NSW) administrative linked health data for 2005 to 2020. Socioeconomic inequities were measured using concentration index approach, and decomposition analysis was conducted to explain the factors accounting for inequality. Healthcare utilization included: public inpatient admissions, private inpatient admissions, visits to public mental health outpatient clinics and emergency department visits, with three different measures (probability of visit, total and conditional number of visits) for each outcome. Private hospital admissions due to eating disorders were concentrated among individuals from higher socioeconomic status (SES) from 2005 to 2020. There was no significant inequity in the probability of public hospital admissions for the same period. Public outpatient visits were utilized more by people from lower SES from 2008 to 2020. Emergency department visits were equitable, but more utilized by those from lower SES in 2020. Public hospital and emergency department services were equitably used by people with eating disorders in NSW, but individuals from high SES were more likely to be admitted to private hospitals for eating disorder care. Use of public hospital outpatient services was higher for those from lower SES. These findings can assist policymakers in understanding the equity of the healthcare system and developing programs to improve fairness in eating disorder-related healthcare in NSW.

Avoidable Hospitalizations in the Military Health System, Fiscal Years 2018-2019.

Ongoing health reforms in the Military Health System (MHS) are expected to shift locations of ambulatory care for up to 1.9 million beneficiaries. We sought to model the impact of this policy by determining potentially avoidable hospitalizations in the MHS based on different primary care settings. We used the MHS Data Repository to conduct a retrospective cross-sectional study of TRICARE Prime and Prime Plus beneficiaries aged 18 to 64 years during fiscal years 2018-2019. Crude and adjusted risk ratios for each Agency for Healthcare Research and Quality prevention quality indicator based on primary care setting were calcualated to determine the total probability of admission for any of the Agency for Healthcare Research and Quality prevention indicators. We identified a total of 260,690 hospital admissions by patients in the MHS with a designated primary care manager (PCM) from fiscal year 2018 to 2019. Of the total admissions, 11,067 (4.25%) were for Agency for Healthcare Research and Quality prevention quality indicators, 3.63% by direct care PCM at a military treatment facility, and 0.61% by a civilian private sector PCM. Risk of admission was lower for private sector PCMs for urinary tract infection, hypertension, perforated appendix, and angina without the procedure. We did not observe a statistically significant adjusted odds ratio of admission in patients managed by private sector PCMs (1.04 adjusted odds ratio; 95% CI, 0.97-1.11). Our findings indicate no difference in the likelihood of avoidable hospitalizations for beneficiaries with a private sector PCM when looking at all conditions together. Patients with a private sector PCM are protected against hospitalization for several conditions. Our findings indicate no adverse impact on avoidable hospitalizations for beneficiaries transitioned to private sector care from direct care.

Efficiency of a technology-assisted nutritional screening system: A retrospective analysis of 11,722 admissions in a tertiary hospital

Background and AimNutritional screening is essential for addressing malnutrition and its consequences. However, routine implementation in large hospitals faces several challenges. To overcome these obstacles, the Clinical Nutrition Service of a tertiary hospital developed a technology-assisted nutritional screening system. This study evaluates the system's efficiency in detecting and assessing patients at nutritional risk upon hospital admission. It also examines the association between nutritional risk, clinical outcomes, and sociodemographic characteristics. MethodsThis retrospective, analytical, observational study examined 11,722 hospital admissions of adult patients in 2019, each with a minimum hospital stay of 48 hours in a tertiary hospital. Rates and timing for the detection, referral, and assessment of patients at nutritional risk were calculated. Participants were divided into low (Malnutrition Screening Tool [MST] < 2 points) and moderate/high (MST ≥ 2) nutritional risk groups to evaluate the relationship between nutritional risk and clinical and demographic variables. ResultsWe found that 91% of patients underwent nutritional screening within the first hours of admission, with a median time of 9 hours from admission to screening (interquartile range [IQR] 3-19). The prevalence of nutritional risk (MST ≥ 2) was 21%. All patients identified as being at nutritional risk were immediately referred for a nutritional assessment once identified, with a median referral time of 0 hours (IQR 0-0). This assessment was carried out by a nutritionist for 98% of these patients, with a median time of 19 hours from referral to assessment (IQR 6-24). Compared to the low-risk group, patients with nutritional risk were older, had higher rates of mortality and admission to the intensive care unit (ICU), longer hospital stays, and a higher proportion of men and cancer diagnoses (p=0.00 for all comparisons). After adjusting for age and sex, nutritional risk was significantly associated with a higher probability of ICU admission (Odds Ratio [OR] 1.13; 95% CI 1.02-1.24) and in-hospital mortality (OR 2.32; 95% CI 1.97-2.73). ConclusionThe integration of technology into nutritional screening was highly efficient for early detection and assessment of at-risk patients upon hospital admission. Features of this system could guide other hospitals. The association found between nutritional risk and clinical outcomes emphasizes the importance of prompt and appropriate nutritional interventions.

A Primary Health Care Program and COVID-19. Impact in Hospital Admissions and Mortality.

Most patients with mild or moderate COVID infection did not require hospital admission, but depending on their personal history, they needed medical supervision. In monitoring these patients in primary care, the design of specific surveillance programs was of great help. Between February 2021 and March 2022, EDCO program was designed in Tenerife, Spain, to telemonitor patients with COVID infection who had at least one vulnerability factor to reduce hospital admissions and mortality. The aim of this study is to describe the clinical course of patients included in the EDCO program and to analyze which factors were associated with a higher probability of hospital admission and mortality. Retrospective cohort study. We included 3848 patients with a COVID-19 infection age over 60years old or age over 18years and at least one vulnerability factor previously reported in medical history. Primary outcome was to assess risk of admission or mortality. 278 (7.2%) patients required hospital admission. Relative risks (RR) of hospital admission were oxygen saturation ≤ 92% (RR: 90.91 (58.82-142.86)), respiratory rate ≥ 22 breaths per minute (RR: 20.41 (1.19-34.48), obesity (RR: 1.53 (1.12-2.10), chronic kidney disease (RR:2.31 (1.23-4.35), ≥ 60years of age (RR: 1.44 (1.04-1.99). Mortality rate was 0.7% (27 patients). Relative risks of mortality were respiratory rate ≥ 22 breaths per minute (RR: 24.85 (11.15-55.38), patients with three or more vulnerability factors (RR: 4.10 (1.62-10.38), oxygen saturation ≤ 92% (RR: 4.69 (1.70-15.15), chronic respiratory disease (RR: 3.32 (1.43-7.69) and active malignancy (RR: 4.00 (1.42-11.23). Vulnerable patients followed by a primary care programme had admission rates of 7.2% and mortality rates of 0.7%. Supervision of vulnerable patients by a Primary Care team was effective in the follow-up of these patients with complete resolution of symptoms in 91.7% of the cases.

Emergency Hospital Admissions of Elderly Patients with Dementia: General Characteristics, Outcome, and Areas of Improvement at an Accident and Emergency Department

Aim: Age-related disorders, such as dementia, are relevant for healthcare services and health systems worldwide. The prevalence of dementia across European countries is estimated to exceed 7 %, and may rise over time. Those patients are at increased risk for hospital admission and prolonged hospitalization, and such care increases the cost for the healthcare system. Less is known regarding patients with dementia in Greece that visit the Accident and Emergency departments (A&amp;E) in general hospitals. The present retrospective study aimed to address this issue. Subjects and methods: The sample of patients and the control group were traced in the A&amp;E department of the University Hospital of Ioannina, Northwest Greece. The study sample consisted of 100 patients with dementia, aged &gt; 65 years and 100 matched controls. The median age of patients with dementia was 85 years, for the control group 83 years, and 63 % were females. In most cases the diagnosis had been made by primary care physicians, and in of patients 21 % by neurologists/psychiatrists. Results: In both groups a median of 2 comorbidities was recorded, with hypertension, heart failure and dyslipidaemia being the most common. Fever and falls were the most common reasons for dementia patients visiting the A&amp;E department. Infection was the most common diagnosis in dementia patients, whereas in 17 % of cases no diagnosis was made and no interventions were needed. The probability of admission after an A&amp;E visit was significantly higher for the dementia group, whereas there were no differences regarding length of hospital stay between patients and controls. Conclusions: The results of the study are in line with international research and highlight the need for the establishment of a national register for patients with dementia, that would enable information exchange between primary and tertiary care and would enable proper diagnosis, management and discharge arrangements.

Associations between BMI and hospital resource use in patients hospitalised for COVID-19 in England: a community-based cohort study

Excess weight is a major risk factor for severe disease after infection with SARS-CoV-2. However, the effect of BMI on COVID-19 hospital resource use has not been fully quantified. This study aimed to identify the association between BMI and hospital resource use for COVID-19 admissions with the intention of informing future national hospital resource allocation. In this community-based cohort study, we analysed patient-level data from 57 415 patients admitted to hospital in England with COVID-19 between April 1, 2020, and Dec 31, 2021. Patients who were aged 20-99 years, had been registered with a general practitioner (GP) surgery that contributed to the QResearch database for the whole preceding year (2019) with at least one BMI value measured before April 1, 2020, available in their GP record, and were admitted to hospital for COVID-19 were included. Outcomes of interest were duration of hospital stay, transfer to an intensive care unit (ICU), and duration of ICU stay. Costs of hospitalisation were estimated from these outcomes. Generalised linear and logit models were used to estimate associations between BMI and hospital resource use outcomes. Patients living with obesity (BMI >30·0 kg/m2) had longer hospital stays relative to patients in the reference BMI group (18·5-25·0 kg/m2; IRR 1·07, 95% CI 1·03-1·10); the reference group had a mean length of stay of 8·82 days (95% CI 8·62-9·01). Patients living with obesity were more likely to be admitted to ICU than the reference group (OR 2·02, 95% CI 1·86-2·19); the reference group had a mean probability of ICU admission of 5·9% (95% CI 5·5-6·3). No association was found between BMI and duration of ICU stay. The mean cost of COVID-19 hospitalisation was £19 877 (SD 17 918) in the reference BMI group. Hospital costs were estimated to be £2736 (95% CI 2224-3248) higher for patients living with obesity. Patients admitted to hospital with COVID-19 with a BMI above the healthy range had longer stays, were more likely to be admitted to ICU, and had higher health-care costs associated with hospital treatment of COVID-19 infection as a result. This information can inform national resource allocation to match hospital capacity to areas where BMI profiles indicate higher demand. National Institute for Health Research.

Does supplemental private health insurance impact health care utilization and seeking behavior of residents covered by social health insurance? Evidence from China National Health Services Survey

BackgroundSupplemental private health insurance (PHI) plays a crucial role in complementing China’s social health insurance (SHI). However, the effectiveness of incorporating PHI as supplementary coverage lacks conclusive evidence regarding its impact on healthcare utilization and seeking behavior among SHI-covered individuals. Therefore, investigating the effects of supplementary PHI on health care utilization and seeking behavior of residents covered by social health insurance is essential to provide empirical evidence for informed decision-making within the Chinese healthcare system.MethodsData from the 2018 China National Health Services Survey were analyzed to compare outpatient and inpatient healthcare utilization and choices between PHI purchasers and non-purchasers across three SHI schemes: urban employee-based basic medical insurance (UEBMI), urban resident-based basic medical insurance (URBMI), and the new rural cooperative medical scheme (NRCMS). Using the Andersen Healthcare Services Utilization Behavior Model as the theoretical framework,binary logistic regression and multinomial logistic regression (MNL) models were employed to assess the impact of PHI on healthcare utilization and provider preferences.ResultsAmong UEBMI, URBMI, and NRCMS participants with PHI, outpatient visit rates were 17.9, 19.8, and 21.7%, and inpatient admission rates were 12.4, 9.9, and 12.9%, respectively. Participants without PHI exhibited higher rates for outpatient visits (23.6, 24.3, and 25.6%) and inpatient admissions (15.2, 12.8, and 14.5%). Binomial logistic regression analyses revealed a higher probability of outpatient visits and inpatient admissions among UEBMI participants with PHI (p < 0.05). NRCMS participants with PHI showed a lower probability of outpatient visits but a higher probability of inpatient admissions (p < 0.05). Multinomial logistic regression indicated that NRCMS participants with PHI were more likely to choose higher-level hospitals, with a 17% increase for county hospitals and 27% for provincial or higher-level hospitals compared to primary care facilities.ConclusionThe findings indicate that the possession of PHI correlated with increased utilization of outpatient and inpatient healthcare services among participants covered by UEBMI. Moreover, for participants under the NRCMS, the presence of PHI is linked to a proclivity for seeking outpatient care at higher-level hospitals and heightened utilization of inpatient services. These results underscore the nuanced influence of supplementary PHI on healthcare-seeking behavior, emphasizing variations across individuals covered by distinct SHI schemes.

Outpatient PCI - early discharge PCI, single center experience

Abstract Funding Acknowledgements None. Background Percutaneous coronary intervention (PCI) has undergone rapid evolution over the last years and is currently a widely generalized therapeutic option. In the past, it was associated with a significant rate of complications, yet, with the improvement of new generation drug eluting stents, and the radial access (RA) development, PCI has become safer and simpler, with a minimum rate of complications. This allows patient’s faster discharge. Besides the pressure from the limited number of beds in wards, the improvement of PCI has given the confidence to urge outpatient PCI programs. However, there are still centers where there is no ambulatory PCI. Purpose This study aims to describe our center experience of ambulatory PCI program, in terms of safety and efficacy. Methods We analyzed our center’s retrospective cohort of 723 PCI, in 2022. Ambulatory PCI was defined as PCI with same day hospital discharge. Our inclusion criteria were patients submitted to PCI. We excluded patients with acute coronary syndromes and patients needing hospital admission for other non-coronary reasons. Results 467 (65%), of the 723 PCI were performed in ambulatory setting. Patients mean age was 67,8±11 years and 23% (n=107) were female. In 12% (n=55) of the cases, the coronary anatomy was previously known, from a differed procedure. 63% (n=298) had a normal left ventricle ejection fraction (LVEF), 6% (n=26) had a moderate depression of LVEF and 3% (n=13) had LVEF severe depression. RA was possible in 82% of the cases (n=384), and 18% (n=83) of PCI was done by femoral access (FA). The access size was 6 Fr in 77% (n=359) of the cases, 7Fr in 22% (n=105) and 8Fr in 1% (n=2). The RA hemostasis was by compression (either manually or by external device) and FA hemostasis was first intended by closing device, however in 17% of the transfemoral PCI (n=14) had to be compressed, due to device hemostasis failure. PCI was successful in 97% of the cases (n=449), with revascularization of the goal lesion. The unsuccessful PCI (3% n=18) were because uncrossable lesion in 2% (n=14), and no reflow after PCI in 1% (n=4). 6 patients had to be admitted, after planned outpatient PCI, 5 due to peripheral access complication with hemorrhage of FA (after closing device and manual compression failure) and 1 due to PCI complication, with small coronary perforation. There was a higher probability of admission in patients submitted to transfemoral PCI (p&amp;lt;0,05), and there was no statistically significant relation between unplanned admission and patient’s LVEF. There were no episodes of death, MACE, non-planned hospital readmission and stent failure in the ambulatory PCI population. PCI has become a predictable and reliable technique, capable to treat outpatients. Patients undergoing successful non-complex PCI, without events, can safely be discharged on the same day. Outpatient PCI helps with the functioning of inpatient care, allowing beds to be freed up for other situations.

Regional Variation in Lifetime Probability of Admission to Residential Aged Care in Australia.

This paper aims to apply a novel demographic technique to update - and extend to sub-national regions - estimates of the lifetime probability of admission to residential aged care. Making optimal use of Australian data sources on aged care usage, mortality and population, this study adopts a two-population life table approach to produce an updated set of national probability estimates and first-time regional estimates. The probability of admission generally increases with age: nationally, lifetime probability at age 65 is 50% for women and 37% for men, rising to 55% and 46%, respectively, at age 85. This general pattern varied somewhat across regions. The regional results point to inequities in the uptake of care, thereby informing providers, governments, aged care advocates and anyone interested in equity of access.

EngiWave: Engineering College Recommendation System using Decision Tree and Random Forest Algorithm

Students face numerous challenges when trying to enroll in their desired institution, particularly in engineering programs. The admissions process is complex, often resulting in students being accepted into lower-ranked institutions than they deserve. To address this, the Council Entrance Predictor utilizes historical acceptance data to forecast the most likely institutions for students. Engiwave, another tool, employs similar data to predict potential institutions based on academic performance, background, and admission criteria. These predictions are facilitated by a machine learning model trained on a dataset containing student profiles and university details, including admission outcomes. By leveraging machine learning and database techniques, the system provides students with a prioritized list of engineering institutions where they have the highest probability of admission, aiding them in preparing their applications effectively.

Improving College Choice in Centralized Admissions: Experimental Evidence on the Importance of Precise Predictions

Abstract This paper provides the first experimental evidence of how admission outcomes in centralized systems depend on strategic college choice behaviors. Centralized college admissions simplify the application process and reduce students' informational barriers. However, such systems also reward informed and strategic college choices. In particular, centralized admissions can be difficult to navigate because they require students to understand how application portfolios and placement priorities map to admission probabilities. Using administrative data from one of the poorest provinces in China, I document that students made undermatched college choices that correlated with inaccurate predictions of admission probabilities. I then implemented a large-scale randomized experiment (N= 32,834) to provide treated students with either (a) an application guidebook or (b) a guidebook plus a school workshop. Results suggest that informing students on choosing colleges and majors based on precise predictions of admission probabilities can effectively improve student–college academic match by 0.1 to 0.2 standard deviation among compliers without substantially changing their college-major preferences.

Sex perspective on mandatory admission in acute psychotic patients

IntroductionPsychotic disorders are strongly linked to a higher risk of mandatory hospitalization, often affecting men more, though some studies report the opposite. Recent investigations also show a higher rate of involuntary admissions in younger individuals. Knowledge in this area is still limited despite extensive research.ObjectivesAnalyze whether there is an association between sex and age with involuntary admissions of individuals with psychotic disorders.MethodsRetrospectively, 254 people with psychotic disorders admitted between 2018-2023 to the adult psychiatric inpatient unit at Hospital Universitari Germans Trias i Pujol were selected, collecting their nature of admission, sex, age, and discharge diagnosis. Comparisons between voluntary and involuntary admissions, with respect to sex and age variables, were conducted using independent sample t-tests, Mann-Whitney U tests, Fisher’s exact test, and chi-square tests. A logistic regression model was used to identify variables significantly associated with mandatory admission.ResultsIn both the male and female groups, there were no statistically significant differences in terms of the mean age at admission (p = 0.162) or the nature of admission (p = 0.586) ( Table 1). When analyzing the voluntary nature of admission based on age and sex, statistically significant differences were only found in the female group (p = 0.01), resulting in a 9.18 year age difference among those admitted voluntarily ( Table 2). The model that best predicted the probability of involuntary admission in individuals with psychotic disorders included the sex variable (OR = 4.88) and the interaction between sex and age (OR = 0.97) ( Table 3). Table 1:Differences between sex regarding voluntariness of patients with psychotic disorders.MaleFemalep valueN (%)122 (48%)132 (52%)Age, m (SD)38.39 (16.64)44.15 (18.44)0.162Admissions, N (%)Voluntary38 (31.1%)37 (28.0%)0.586Involuntary84 (68.9%)95 (72.0%) Table 2:Analysis of voluntariness by sex and age.Age, m (SD)VoluntaryInvoluntaryp valueMale37.45 (16.38)38.81 (16.84)0.677Female50.76 (18.19)41.58 (17.98)0.01*Total44.01 (18.44)40.28 (17.46)0.127 Table 3:Predictors of involuntariness in psychotic patients: Logistic regression model (ENTER METHOD). Predictor -2log likelihood Nagelkerke R2 x2 (df*) OR* (95% CI*)p value301.220.0390.03 (1)Age1.01 (0.98; 1.03)0.674Sex4.88 (1.15; 20.72)0.032*Age x Sex Interaction0.97 (0.94; 0.99)0.046*ConclusionsYoung women with psychotic disorders face a higher risk of involuntary admissions, emphasizing the need for gender-specific strategies to improve care of these patients.Disclosure of InterestNone Declared

Adult use cannabis legalization and cannabis use disorder treatment in California, 2010–2021

IntroductionMany nations and jurisdictions have legalized non-medical adult use of cannabis, or are considering doing so. This paper contributes to knowledge of adult use legalization's associations with cannabis use disorder (CUD) treatment utilization. MethodsThis study collected data from a dataset of all publicly funded substance use disorder treatment delivered in California from 2010 to 2021 (1,460,066 episodes). A logistic regression model estimates adult use legalization's impacts on CUD treatment utilization using an individual-level pre-post time series model, including individual and county-level characteristics and county and year-fixed effects. ResultsAdult use legalization was associated with a significant decrease in the probability of admission to CUD treatment (average marginal effect (AME): −0.005, 95 % CI: −0.009, 0.000). Adult use legalization was also associated with a decrease in the probability of admission to CUD treatment for males (AME: −0.025, 95 % CI: −0.027, −0.023) Medi-Cal beneficiaries (AME: −0.025, 95 % CI: −0.027, −0.023) adults ages 21+ (AME: −0.011, 95 % CI: −0.014, −0.009) and Whites (AME: −0.012, 95 % CI: −0.015, −0.010), and an increase in the probability of admission to CUD treatment for patients referred from the criminal justice system (AME: 0.017, 95 % CI: 0.015, 0.020) and Blacks (AME: 0.004, 95 % CI: 0.000, 0.007) and Hispanics (AME: 0.009, 95 % CI: 0.006, 0.011). ConclusionsAdult use legalization is associated with declining CUD treatment admissions, even though cannabis-related problems are becoming more prevalent. Policies and practices that protect public health, and engage people with CUD in treatment are needed.

The association of prehospital systemic corticosteroids with emergency department and in-hospital outcomes for patients with asthma exacerbations.

Timely administration of systemic corticosteroids is a cornerstone of asthma exacerbation treatment, yet little is known regarding potential benefits of prehospital administration by emergency medical services (EMS) clinicians. We examined factors associated with prehospital corticosteroid administration with hospitalization and hospital length of stay (LOS). We performed a retrospective study of EMS encounters for patients 2-50 years of age with suspected asthma exacerbation from a national data set. We evaluated factors associated with systemic corticosteroid administration using generalized estimating equations. We performed propensity matching based on service level, age, encounter duration, vital signs, and treatments to evaluate the association of prehospital corticosteroid administration with hospitalization and LOS using weighted logistic regression. We evaluated the association of prehospital corticosteroid administration with admission using Bayesian models. Of 15,834 encounters, 4731 (29.9%) received prehospital systemic corticosteroids. Administration of corticosteroids was associated with older age; sex; urbanicity; advanced life support provider; vital sign instability; increasing doses of albuterol; and provision of ipratropium bromide, magnesium, epinephrine, and supplementary oxygen. Within the matched sample, prehospital corticosteroids were not associated with hospitalization (odds ratio [OR] 0.86, 95% confidence interval [CI] 0.73-1.01) or LOS (multiplier 0.76, 95% CI 0.56-1.05). Administration of corticosteroids was associated with lower odds of admission and shorter LOS in longer EMS encounters (>34 min), lower admission odds in patients with documented wheezing, and shorter LOS among patients treated with albuterol. In a Bayesian model with noninformative priors, the OR for admission among encounters given corticosteroids was 0.86 (95% credible interval 0.77-0.96). Prehospital systemic corticosteroid administration was not associated with hospitalization or LOS in the overall cohort of asthma patients treated by EMS, though they had a lower probability of admission within Bayesian models. Improved outcomes were noted among subgroups of longer EMS encounters, documented wheezing, and receipt of albuterol.

Association between social vulnerability index and admission urgency for transcatheter aortic valve replacement

BackgroundTranscatheter aortic valve replacement (TAVR) are not offered equitably to vulnerable population groups. Adequate levels of insurance may narrow gaps among patients with higher social vulnerability index (SVI). Among a national population of individuals with commercial or Medicare insurance, we sought to determine whether SVI was associated with urgency of receipt of TAVR for aortic stenosis. Methods and resultsUsing Optum's de-identified Clinformatics Data Mart Database (CDM), we identified admissions for TAVR with aortic stenosis between January 2018 and March 2022. Admission urgency was identified by CDM claims codes. SVI was cross-referenced to patient zip codes and grouped into quintiles. Generalized linear mixed effects models were used to predict the probability of a TAVR admission being urgent based on SVI quintiles, adjusting for patient and hospital-level covariates. ResultsAmong 6680 admissions for TAVR [median age 80 years (interquartile range 75–85), 43.9 % female], 8.5 % (n = 567) were classified as urgent. After adjusting for patient and hospital-level variables, there were no significant differences in the odds of urgent admission for TAVR according to SVI quintiles [OR 5th (greatest social vulnerability) vs 1st quintile (least social vulnerability): 1.29 (95 % CI: 0.90–1.85)]. ConclusionsAmong commercial or Medicare beneficiaries with aortic stenosis, SVI was not associated with admission urgency for TAVR. To clarify whether cardiovascular care delivery is improved across SVI with higher paying beneficiaries, future investigation should identify whether relationships between SVI and TAVR urgency vary for Medicaid beneficiaries compared to commercial beneficiaries.

Prognostic value of bioelectrical impedance analysis in head and neck cancer patients undergoing radiotherapy: a VALOR® study.

Bioelectrical impedance analysis (BIA) serves as a method to estimate body composition. Parameters such as phase angle (PA), standardized phase angle (SPA), body mass cell (BCM), BCM index (BCMI), and fat-free mass (FFM) might significantly impact the prognosis of head and neck cancer (HNC) patients. The present study aimed to investigate whether bioelectrical parameters can be used to predict survival in the HNC population and establish the optimal cutoff points for predictive accuracy. A multicenter observational study was performed across 12 tertiary hospitals in Andalusia (a region from the south of Spain). A total of 494 patients diagnosed with HNC between 2020 and 2022 at different stages were included in this study, with a minimum follow-up period of 12 months. The BIA assessment was carried out during the first 2 weeks of radical radiotherapy treatment with chemotherapy or other systemic treatments. A multivariate logistic regression analysis of overall survival, complications, hospital admission, and palliative care and its relationship with BIA nutritional assessment was performed. Significant prognostic factors identified in the multivariable analysis encompassed phase angle (PA), standardized phase angle (SPA), body cell mass (BCM), and BCM index (BCMI). Lower PA and BCM values were significantly associated with adverse clinical outcomes. A BCM threshold above 17 kg/m2 was the most significant predictor for predicting survival within the overall HNC population. The PA values of <5.1° in male and <4.8° in female patients showed the best predictive potential for mortality. Increased PA (as a continuous variable) demonstrated a significantly reduced risk for mortality (OR, 0.64; 95% CI, 0.43-0.94; p < 0.05) and a decreased likelihood of hospital admission (OR, 0.75; 95% CI, 0.52-1.07; p < 0.05). Higher BCM correlated with a lower risk of mortality (OR, 0.88; 95% CI, 0.80-0.96; p < 0.01) and a diminished probability of hospital admission (OR, 0.91; 95% CI, 0.83-0.99; p < 0.05). BIA is a crucial tool in the nutritional assessment of HNC patients. BCM and PA are the main bioelectrical parameters used to predict clinical outcomes in this population. Future studies are needed to validate BIA variables in a large cohort to ensure whether early intensification of nutritional treatment would improve survival.

Design model of a twisted and folded Clos network with multi-step grouped intermediate switches guaranteeing admissible blocking probability

A future data center network is expected to be constructed by a Clos network consisting of optical-circuit switches to deal with traffic growth. A previous model addressed a Clos-network design problem that divides the set of intermediate switches by each role for request routing to guarantee an admissible blocking probability to maximize the switching capacity. However, the previous model divides the set of intermediate switches into at most only two groups, and there is room for a more flexible design by increasing the number of divisions. This paper proposes a design model that generalizes the number of divisions to increase the switching capacity while guaranteeing an admissible blocking probability. We formulate the design model as an optimization problem. We introduce two algorithms to obtain a feasible solution that satisfies the constraints of the optimization problem. Numerical results showed that the proposed model can increase the switching capacity as the number of divisions increases.

Hospitalization forecast to inform COVID-19 pandemic planning and resource allocation using discrete event simulation

Purpose: This study aims to address the pressing need for accurate forecasting of healthcare resource demands during the COVID-19 pandemic. It presents a novel approach that combines a stochastic Markov model and a discrete event simulation model to dynamically predict hospital admissions and daily occupancy of hospital and ICU beds.Design/methodology/approach: The research builds upon existing work related to predicting COVID-19 spread and patient influx to hospital emergency departments. The proposed model was developed and validated at San Juan de Alicante University Hospital from July 10, 2020, to January 10, 2022, and externally validated at Hospital Vega Baja. The model involves an admissions generator based on a stochastic Markov model, feeding data into a discrete event simulation model in the R programming language. The probabilities of hospital admission were calculated based on age-stratified positive SARS-COV-2 results from the health department's catchment population. The discrete event simulation model simulates distinct patient pathways within the hospital to estimate bed occupancy for the upcoming week. The performance of the model was measured using the median absolute difference (MAD) between predicted and actual demand.Findings: When applied to data from San Juan hospital, the admissions generator demonstrated a MAD of 6 admissions/week (interquartile range [IQR] 2-11). The MAD between the model's predictions and actual bed occupancy was 20 beds/day (IQR 5-43), equivalent to 5% of total hospital beds. For ICU occupancy, the MAD was 4 beds/day (IQR 2-7), constituting 25% of ICU beds. Evaluation with data from Hospital Vega Baja showcased an admissions generator MAD of 2.42 admissions/week (IQR 1.02-7.41). The MAD between the model's predictions and actual bed occupancy was 18 beds/day (IQR 19.57-38.89), approximately 5.1% of hospital beds. The ICU occupancy MAD was 3 beds/day (IQR 1-5), making up 21.4% of ICU beds.Practical implications: The dynamic predictions of hospital admissions, ward beds, and ICU occupancy for COVID-19 patients proved highly valuable to hospital managers, facilitating early and informed planning of resource allocation. Additionally, this study underscores the importance of utilizing simulation techniques to predict and manage hospital occupancy levels, thereby enhancing decision-making in hospital bed management, not only during pandemics but also during regular periods.Originality/value: This study introduces a novel hybrid approach that combines stochastic modeling and discrete event simulation to forecast healthcare resource demands during the COVID-19 pandemic. The methodology's effectiveness in predicting admissions and bed occupancy contributes to improved resource planning and situational awareness.