Spalling of Concrete - Implications for Structural Performance in Fire

This preliminary paper is a progress report on an analytical investigation into the implications of explosive spalling on the fire performance of reinforced concrete structural elements and whole structures. This study does not attempt to predict whether spalling will occur. For accurate prediction of the occurrence of spalling a complete and fully coupled hygro-thermal-mechanical (HTM) analysis is required, as described by a comprehensive review of current research into the parameters and mechanisms that influence spalling, including a review of physical spalling criteria. This paper describes the structural performance of spalled concrete elements, using finite element analysis where spalling is modelled by removing layers of concrete when a set of spalling criteria are met. The method is presented using a case study of a simply supported reinforced concrete beam, where the analytical results indicate that spalling invariably triggers an early failure (well short of the required FRR rating) of a beam exposed to the standard fire

Understanding the impact of interventions to prevent antimicrobial resistant infections in the long-term care facility; a review and practical guide to mathematical modelling

(1) To systematically search for all dynamic mathematical models of infectious disease transmission in long-term care facilities (LTCFs); (2) to critically evaluate models of interventions against antimicrobial resistance (AMR) in this setting; and (3) to develop a checklist for hospital epidemiologists and policy makers by which to distinguish good quality models of AMR in LTCFs. The CINAHL, EMBASE, Global Health, MEDLINE, and Scopus databases were systematically searched for studies of dynamic mathematical models set in LTCFs. Models of interventions targeting methicillin-resistant Staphylococcus aureus in LTCFs were critically assessed. Using this analysis, we developed a checklist for good quality mathematical models of AMR in LTCFs. Overall, 18 papers described mathematical models that characterized the spread of infectious diseases in LTCFs, but no models of AMR in gram-negative bacteria in this setting were described. Future models of AMR in LTCFs require a more robust methodology (ie, formal model fitting to data and validation), greater transparency regarding model assumptions, setting-specific data, realistic and current setting-specific parameters, and inclusion of movement dynamics between LTCFs and hospitals. Mathematical models of AMR in gram-negative bacteria in the LTCF setting, where these bacteria are increasingly becoming prevalent, are needed to help guide infection prevention and control. Improvements are required to develop outputs of sufficient quality to help guide interventions and policy in the future. We suggest a checklist of criteria to be used as a practical guide to determine whether a model is robust enough to test policy

Influenza Hospitalisations in England during the 2022/23 Season: do different data sources drive divergence in modelled waves? A comparison of surveillance and administrative data

Accurate and representative data is vital for precisely reporting the impact of influenza in healthcare systems. Northern hemisphere winter 2022/23 experienced the most substantial influenza wave since the COVID-19 pandemic began in 2020. Simultaneously, new data streams become available within health services because of the pandemic. Comparing these data, surveillance and administrative, supports the accurate monitoring of population level disease trends. We analysed admissions rates per capita from four different collection mechanisms covering National Health Service hospital Trusts in England over the winter 2022/23 wave. We adjust for difference in reporting and extracted key epidemic characteristics including the maximum admission rate, peak timing, cumulative season admissions and growth rates by fitting generalised additive models at national and regional levels. By modelling the admission rates per capita across surveillance and administrative data systems we show that different data measuring the epidemic produce different estimates of key quantities. Nationally and in most regions the data correspond well for the maximum admission rate, date of peak and growth rate, however, in subnational analysis discrepancies in estimates arose, particularly for the cumulative admission rate. This research shows that the choice of data used to measure seasonal influenza epidemics can influence analysis substantially at sub-national levels. For the admission rate per capita there is comparability in the sentinel surveillance approach (which has other important functions), rapid situational reports, operational databases and time lagged administrative data giving assurance in their combined value. Utilising multiple sources of data aids understanding of the impact of seasonal influenza epidemics in the population

Real-time COVID-19 hospital admissions forecasting with leading indicators and ensemble methods in England

Hospitalisations from COVID-19 with Omicron sub-lineages have put a sustained pressure on the English healthcare system. Understanding the expected healthcare demand enables more effective and timely planning from public health. We collect syndromic surveillance sources, which include online search data, NHS 111 telephonic and online triages. Incorporating this data we explore generalised additive models, generalised linear mixed-models, penalised generalised linear models and model ensemble methods to forecast over a two-week forecast horizon at an NHS Trust level. Furthermore, we showcase how model combinations improve forecast scoring through a mean ensemble, weighted ensemble, and ensemble by regression. Validated over multiple Omicron waves, at different spatial scales, we show that leading indicators can improve performance of forecasting models, particularly at epidemic changepoints. Using a variety of scoring rules, we show that ensemble approaches outperformed all individual models, providing higher performance at a 21-day window than the corresponding individual models at 14-days. We introduce a modelling structure used by public health officials in England in 2022 to inform NHS healthcare strategy and policy decision making. This paper explores the significance of ensemble methods to improve forecasting performance and how novel syndromic surveillance can be practically applied in epidemic forecasting

Seasonality of urinary tract infections in the United Kingdom in different age groups: longitudinal analysis of The Health Improvement Network (THIN)

Evidence regarding the seasonality of urinary tract infection (UTI) consultations in primary care is conflicting and methodologically poor. To our knowledge, this is the first study to determine whether this seasonality exists in the UK, identify the peak months and describe seasonality by age. The monthly number of UTI consultations (N = 992 803) and nitrofurantoin and trimethoprim prescriptions (N = 1 719 416) during 2008-2015 was extracted from The Health Improvement Network (THIN), a large nationally representative UK dataset of electronic patient records. Negative binomial regression models were fitted to these data to investigate seasonal fluctuations by age group (14-17, 18-24, 25-45, 46-69, 70-84, 85+) and by sex, accounting for a change in the rate of UTI over the study period. A September to November peak in UTI consultation incidence was observed for ages 14-69. This seasonality progressively faded in older age groups and no seasonality was found in individuals aged 85+, in whom UTIs were most common. UTIs were rare in males but followed a similar seasonal pattern than in females. We show strong evidence of an autumnal seasonality for UTIs in individuals under 70 years of age and a lack of seasonality in the very old. These findings should provide helpful information when interpreting surveillance reports and the results of interventions against UTI

International comparison of health spending and utilization among people with complex multimorbidity.

OBJECTIVE: The objective of this study was to explore cross-country differences in spending and utilization across different domains of care for a multimorbid persona with heart failure and diabetes. DATA SOURCES: We used individual-level administrative claims or registry data from inpatient and outpatient health care sectors compiled by the International Collaborative on Costs, Outcomes, and Needs in Care (ICCONIC) across 11 countries: Australia, Canada, England, France, Germany, the Netherlands, New Zealand, Spain, Sweden, Switzerland, and the United States (US). DATA COLLECTION/EXTRACTION METHODS: Data collected by ICCONIC partners. STUDY DESIGN: We retrospectively analyzed age-sex standardized utilization and spending of an older person (65-90 years) hospitalized with a heart failure exacerbation and a secondary diagnosis of diabetes across five domains of care: hospital care, primary care, outpatient specialty care, post-acute rehabilitative care, and outpatient drugs. PRINCIPAL FINDINGS: Sample sizes ranged from n = 1270 in Spain to n = 21,803 in the United States. Mean age (standard deviation [SD]) ranged from 76.2 (5.6) in the Netherlands to 80.3 (6.8) in Sweden. We observed substantial variation in spending and utilization across care settings. On average, England spent $10,956 per person in hospital care while the United States spent$30,877. The United States had a shorter length of stay over the year (18.9 days) compared to France (32.9) and Germany (33.4). The United States spent more days in facility-based rehabilitative care than other countries. Australia spent $421 per person in primary care, while Spain (Aragon) spent$1557. The United States and Canada had proportionately more visits to specialist providers than primary care providers. Across almost all sectors, the United States spent more than other countries, suggesting higher prices per unit. CONCLUSION: Across 11 countries, there is substantial variation in health care spending and utilization for a complex multimorbid persona with heart failure and diabetes. Drivers of spending vary across countries, with the United States being the most expensive country due to high prices and higher use of facility-based rehabilitative care

Differences in health care spending and utilization among older frail adults in high-income countries: ICCONIC hip fracture persona.

ObjectiveThis study explores differences in spending and utilization of health care services for an older person with frailty before and after a hip fracture.Data sourcesWe used individual-level patient data from five care settings.Study designWe compared utilization and spending of an older person aged older than 65 years for 365 days before and after a hip fracture across 11 countries and five domains of care as follows: acute hospital care, primary care, outpatient specialty care, post-acute rehabilitative care, and outpatient drugs. Utilization and spending were age and sex standardized..Data collection/extraction methodsThe data were compiled by the International Collaborative on Costs, Outcomes, and Needs in Care (ICCONIC) across 11 countries as follows: Australia, Canada, England, France, Germany, the Netherlands, New Zealand, Spain, Sweden, Switzerland, and the United States.Principal findingsThe sample ranged from 1859 patients in Spain to 42,849 in France. Mean age ranged from 81.2 in Switzerland to 84.7 in Australia. The majority of patients across countries were female. Relative to other countries, the United States had the lowest inpatient length of stay (11.3), but the highest number of days were spent in post-acute care rehab (100.7) and, on average, had more visits to specialist providers (6.8 per year) than primary care providers (4.0 per year). Across almost all sectors, the United States spent more per person than other countries per unit ($13,622 per hospitalization,$233 per primary care visit, $386 per MD specialist visit). Patients also had high expenditures in the year prior to the hip fracture, mostly concentrated in the inpatient setting.ConclusionAcross 11 high-income countries, there is substantial variation in health care spending and utilization for an older person with frailty, both before and after a hip fracture. The United States is the most expensive country due to high prices and above average utilization of post-acute rehab care

Differences in health outcomes for high-need high-cost patients across high-income countries.

ObjectiveThis study explores variations in outcomes of care for two types of patient personas-an older frail person recovering from a hip fracture and a multimorbid older patient with congestive heart failure (CHF) and diabetes.Data sourcesWe used individual-level patient data from 11 health systems.Study designWe compared inpatient mortality, mortality, and readmission rates at 30, 90, and 365 days. For the hip fracture persona, we also calculated time to surgery. Outcomes were standardized by age and sex.Data collection/extraction methodsData was compiled by the International Collaborative on Costs, Outcomes and Needs in Care across 11 countries for the years 2016-2017 (or nearest): Australia, Canada, England, France, Germany, the Netherlands, New Zealand, Spain, Sweden, Switzerland, and the United States.Principal findingsThe hip sample across ranged from 1859 patients in Aragon, Spain, to 42,849 in France. Mean age ranged from 81.2 in Switzerland to 84.7 in Australia, and the majority of hip patients across countries were female. The congestive heart failure (CHF) sample ranged from 742 patients in England to 21,803 in the United States. Mean age ranged from 77.2 in the United States to 80.3 in Sweden, and the majority of CHF patients were males. Average in-hospital mortality across countries was 4.1%. for the hip persona and 6.3% for the CHF persona. At the year mark, the mean mortality across all countries was 25.3% for the hip persona and 32.7% for CHF persona. Across both patient types, England reported the highest mortality at 1 year followed by the United States. Readmission rates for all periods were higher for the CHF persona than the hip persona. At 30 days, the average readmission rate for the hip persona was 13.8% and 27.6% for the CHF persona.ConclusionAcross 11 countries, there are meaningful differences in health system outcomes for two types of patients

A methodology for identifying high-need, high-cost patient personas for international comparisons.

ObjectiveTo establish a methodological approach to compare two high-need, high-cost (HNHC) patient personas internationally.Data sourcesLinked individual-level administrative data from the inpatient and outpatient sectors compiled by the International Collaborative on Costs, Outcomes, and Needs in Care (ICCONIC) across 11 countries: Australia, Canada, England, France, Germany, the Netherlands, New Zealand, Spain, Sweden, Switzerland, and the United States.Study designWe outline a methodological approach to identify HNHC patient types for international comparisons that reflect complex, priority populations defined by the National Academy of Medicine. We define two patient profiles using accessible patient-level datasets linked across different domains of care-hospital care, primary care, outpatient specialty care, post-acute rehabilitative care, long-term care, home-health care, and outpatient drugs. The personas include a frail older adult with a hip fracture with subsequent hip replacement and an older person with complex multimorbidity, including heart failure and diabetes. We demonstrate their comparability by examining the characteristics and clinical diagnoses captured across countries.Data collection/extraction methodsData collected by ICCONIC partners.Principal findingsAcross 11 countries, the identification of HNHC patient personas was feasible to examine variations in healthcare utilization, spending, and patient outcomes. The ability of countries to examine linked, individual-level data varied, with the Netherlands, Canada, and Germany able to comprehensively examine care across all seven domains, whereas other countries such as England, Switzerland, and New Zealand were more limited. All countries were able to identify a hip fracture persona and a heart failure persona. Patient characteristics were reassuringly similar across countries.ConclusionAlthough there are cross-country differences in the availability and structure of data sources, countries had the ability to effectively identify comparable HNHC personas for international study. This work serves as the methodological paper for six accompanying papers examining differences in spending, utilization, and outcomes for these personas across countries