All-cause mortality and hospital admissions for nursing home residents during the COVID-19 pandemic: a Norwegian register-based cohort study.

BACKGROUND: This paper investigates the consequences of the COVID-19 pandemic on mortality and hospitalization among nursing home residents in Norway. While existing evidence shows that nursing home residents were overrepresented among COVID-19-related deaths, suggesting inadequate protection measures, this study argues that the observed overrepresentation in mortality and hospitalization may partly stem from the inherent frailty of this demographic. Using nationwide administrative data, we assessed excess deaths and hospitalization by comparing pandemic-era rates to those of a pre-pandemic cohort. METHODS: We compared mortality and hospitalization rates between a pandemic cohort of nursing home residents as of September 2019 (N = 30,052), and a pre-pandemic cohort as of September 2017 (N = 30,429). Both cohorts were followed monthly for two years, beginning in September 2019 and 2017, respectively. This analysis was conducted at the national level and separately for nursing home residents in areas with low, medium, and high SARS-CoV-2 community transmission. Event studies and difference-in-difference models allowed us to separate the impact of the pandemic on mortality and hospitalization from secular and seasonal changes. RESULTS: The pandemic cohort experienced a non-significant 0.07 percentage points (95% confidence interval (CI): - 0.081 to 0.221) increase in all-cause mortality during the 18 months following pandemic onset, compared to the pre-pandemic cohort. Moreover, our findings indicate a substantial reduction in hospitalizations of 0.27 percentage points (95% CI: - 0.464 to - 0.135) and a non-significant decrease of 0.80 percentage points (95% CI: - 2.529 to 0.929) in the proportion of nursing home residents hospitalized before death. The effect on mortality remained consistent across regions with both high and low levels of SARS-CoV-2 community transmission. CONCLUSIONS: Our findings indicate no clear evidence of excess all-cause mortality in Norway during the pandemic, neither nationally nor in areas with high infection rates. This suggests that early implementation of nationwide and nursing home-specific infection control measures during the pandemic effectively protected nursing home residents. Furthermore, our results revealed a decrease in hospitalizations, both overall and prior to death, suggesting that nursing homes adhered to national guidelines promoting on-site treatment for residents.

Variations in older people's emergency care use by social care setting: a systematic review of international evidence.

BACKGROUND: Older adults' use of social care and their healthcare utilization are closely related. Residents of care homes access emergency care more often than the wider older population; however, less is known about emergency care use across other social care settings. SOURCES OF DATA: A systematic review was conducted, searching six electronic databases between January 2012 and February 2022. AREAS OF AGREEMENT: Older people access emergency care from a variety of community settings. AREAS OF CONTROVERSY: Differences in study design contributed to high variation observed between studies. GROWING POINTS: Although data were limited, findings suggest that emergency hospital attendance is lowest from nursing homes and highest from assisted living facilities, whilst emergency admissions varied little by social care setting. AREAS TIMELY FOR DEVELOPING RESEARCH: There is a paucity of published research on emergency hospital use from social care settings, particularly home care and assisted living facilities. More attention is needed on this area, with standardized definitions to enable comparisons between studies.

Assessing the impact of psychiatric genetic counseling on psychiatric hospitalizations.

Psychiatric genetic counseling (pGC) can improve patient empowerment and self-efficacy. We explored the relationship between pGC and psychiatric hospitalizations, for which no prior data exist. Using Population Data BC (a provincial dataset), we tested two hypotheses: (1) among patients (>18 years) with psychiatric conditions who received pGC between May 2010 and Dec 2016 (N = 387), compared with the year pre-pGC, in the year post-pGC there would be fewer (a) individuals hospitalized and (b) total hospital admissions; and (2) using a matched cohort design, compared with controls (N = 363, matched 1:4 for sex, diagnosis, time since diagnosis, region, and age, and assigned a pseudo pGC index date), the pGC cohort (N = 91) would have (a) more individuals whose number of hospitalizations decreased and (b) fewer hospitalizations post-pGC/pseudo-index. We also explored total days in hospital. Within the pGC cohort, there were fewer hospitalizations post-pGC than pre- pGC (p = 0.011, OR = 1.69), and total days in hospital decreased (1085 to 669). However, when compared to matched controls, the post-pGC/pseudo index change in hospitalizations among pGC cases was not statistically significant, even after controlling for the higher number of hospitalizations prior. pGC may lead to fewer psychiatric hospitalizations and cost savings; further studies exploring this are warranted.

Recent trends in hospital admission due to bipolar disorder in 10-19-year-olds in Spain: A nationwide population-based study.

INTRODUCTION: Bipolar disorder (BD) hospitalization rates in children and adolescents vary greatly across place and over time. There are no population-based studies on youth BD hospitalizations in Spain. METHODS: We identified all patients aged 10-19 hospitalized due to BD in Spain between 2000 and 2021, examined their demographic and clinical characteristics, and assessed temporal trends in hospitalizations - overall and stratified by age and presence of additional psychiatric comorbidity. We used Joinpoint regressions to identify inflection points and quantify whole-period and annual percentage changes (APCs) in trends. RESULTS: Of 4770 BD hospitalizations in 10-19-year-olds between 2000 and 2021 (average annual rate: 4.8 per 100,000), over half indicated an additional psychiatric comorbidity, most frequently substance abuse (62.2%), mostly due to cannabis (72.4%). During the study period, admissions increased twofold with an inflection point: Rates increased annually only between 2000 and 2008, for APCs 34.0% (95% confidence interval: 20.0%, 71.1%) among 10-14-year-olds, 10.3% (6.4%, 14.3%) among 15-19-year-olds, and 15.5% (11.5%, 22.7%) among patients with additional psychiatric comorbidity. Between 2009 and 2021, rates decreased moderately among 10-14-year-olds - APC: -8.3% (-14.1%, -4.4%) and slightly among 15-19-year-olds without additional psychiatric comorbidity - APC: -2.6(-5.7, -1.0), remaining largely stable among 15-19-year-olds overall. CONCLUSIONS: Recent trends in hospitalization due to BD in 10-19-year-olds in Spain indicate salient increases in the early 2000s - especially among (i) patients aged 10-14 (decreasing moderately after 2009 among 10-14-year-olds and plateauing among 15-19-year-olds) and (ii) patients with additional psychiatric comorbidity (i.e., cannabis use disorder). These findings suggest links with recent changes in clinical practices for children and recent trends in substance use among Spanish youth.

Improvements in data completeness in health information systems reveal racial inequalities: longitudinal national data from hospital admissions in Brazil 2010-2022.

BACKGROUND: Race and ethnicity are important drivers of health inequalities worldwide. However, the recording of race/ethnicity in data systems is frequently insufficient, particularly in low- and middle-income countries. The aim of this study is to descriptively analyse trends in data completeness in race/color records in hospital admissions and the rates of hospitalizations by various causes for Blacks and Whites individuals. METHODS: We conducted a longitudinal analysis, examining hospital admission data from Brazil's Hospital Information System (SIH) between 2010 and 2022, and analysed trends in reporting completeness and racial inequalities. These hospitalization records were examined based on year, quarter, cause of admission (using International Classification of Diseases (ICD-10) codes), and race/color (categorized as Black, White, or missing). We examined the patterns in hospitalization rates and the prevalence of missing data over a period of time. RESULTS: Over the study period, there was a notable improvement in data completeness regarding race/color in hospital admissions in Brazil. The proportion of missing values on race decreased from 34.7% in 2010 to 21.2% in 2020. As data completeness improved, racial inequalities in hospitalization rates became more evident - across several causes, including assaults, tuberculosis, hypertensive diseases, at-risk hospitalizations during pregnancy and motorcycle accidents. CONCLUSIONS: The study highlights the critical role of data quality in identifying and addressing racial health inequalities. Improved data completeness has revealed previously hidden inequalities in health records, emphasizing the need for comprehensive data collection to inform equitable health policies and interventions. Policymakers working in areas where socioeconomic data reporting (including on race and ethnicity) is suboptimal, should address data completeness to fully understand the scale of health inequalities.

Adherence to the asthma pathway, including pre-triage bronchodilator history, reduces hospitalizations.

Objective: To determine if adherence to an asthma treatment pathway is associated with a decrease in hospitalizations.Methods: A prospective cohort design was conducted of Thai children aged 2-15 years who visited the emergency department with severe asthma exacerbations, defined as a Buddhasothorn Asthma Severity Score ≥ 8. Patients who received systemic corticosteroids and nebulized short-acting beta-2 agonists combined with ipratropium bromides were classified as the adherence group. The timing of steroid and bronchodilator administration, length of hospital stay, and hospitalization rate were examined in relation to adherence to the asthma pathway. Multivariable logistic regression models and adjusted odds ratios were used to assess associations.Results: A total of 118 episodes of asthma exacerbations (EAEs) from 59 participants were included. Patients who adhered to the pathway had a significantly higher rate of systemic corticosteroid administration within 1 h of arrival at triage (88.6% vs. 41.9%, adjusted Odds Ratio: aOR 10.21; 95%CI 3.52-29.62). A higher proportion of the patients who adhered to the pathway also received inhaled ipratropium bromide ≥ 2 doses within 1 h of arrival at triage (72.7% vs. 12.2%, aOR 23.51; 95%CI 7.73-71.54) and it was administered significantly faster by 31 min (5 min vs. 36 min, p < 0.001) compared to non-adherence group. The hospitalization rate was significantly lower by almost half of EAEs for adherence group (36.4% vs. 63.5%, aOR 0.41; 95%CI 0.18-0.93).Conclusions: Accurate assessment of severity and adherence to the clinical pathway can reduce hospitalization in pediatric patients with severe asthma exacerbations.

Patterns of acute hospital and specialist palliative care use among people with non-curative upper gastrointestinal cancer.

PURPOSE: Upper gastrointestinal (GI) cancers contribute to 16.7% of UK cancer deaths. These patients make high use of acute hospital services, but detail about palliative care use is lacking. We aimed to determine the patterns of use of acute hospital and hospital specialist palliative care services in patients with advanced non-curative upper GI cancer. METHODS: We conducted a service evaluation of hospital use and palliative care for all patients with non-curative upper GI cancer seen in one large hospital, using routinely collected data (2019-2022). We report and characterise hospital admissions and palliative care within the study time period, using descriptive statistics, and multivariable Poisson regression to estimate the unadjusted and adjusted incidence rate ratio of hospital admissions. RESULTS: The total with non-curative upper GI cancer was 960. 86.7% had at least one hospital admission, with 1239 admissions in total. Patients had a higher risk of admission to hospital if: aged ≤ 65 (IRR for 66-75 years 0.71, IRR 76-85 years 0.68; IRR > 85 years 0.53; p < 0.05), or lived in an area of lower socioeconomic status (IMD Deciles 1-5) (IRR 0.90; p < 0.05). Over the 4-year period, the rate of re-admission was higher in patients not referred to palliative care (rate 0.52 readmissions/patient versus rate 1.47 readmissions/patient). CONCLUSION: People with advanced non-curative gastrointestinal cancer have frequent hospital admissions, especially if younger or from areas of lower socioeconomic status. There is clear association between specialist palliative care referral and reduced risk of hospitalisation. This evidence supports referral to specialist palliative care.

Short-term impact of air pollution, noise and temperature on emergency hospital admissions in Madrid (Spain) due to liver and gallbladder diseases.

BACKGROUND: Very few epidemiological studies have explored the environmental and meteorological risk factors that influence liver diseases and gallbladder disorders, and no studies have addressed the specific case of Spain. METHODS: This is a retrospective ecological study conducted during 2013-2018. We analysed emergency admissions in the central area of the Region of Madrid for the following causes: Liver and gallbladder diseases (L&GB) (ICD-10: K70-K81); disorders of gallbladder (DGB) (ICD 10: K80-K81); liver disease (LD) (ICD 10: K70-K77); alcoholic liver disease (ALD) (ICD-10: K70); viral hepatitis (VH) (ICD10:B15-B19); and hepatic failure, not elsewhere classified (HFNS) (ICD-10: K72). Independent variables used: meteorological (maximum daily temperature (Tmax in °C), minimum daily temperature (Tmin in °C), and relative humidity (RH in %)); chemical air pollution (8-hO3, NO2, PM10, PM2.5 in µg/m3); and noise pollution (equivalent level of daily noise (Ld in dB(A)). Transformed variables: extreme heat in degrees (Theat); wet cold (WC); and high ozone. We fitted Poisson models, negative binomials and zero-inflated Poisson controlled for seasonality, day of the week, holidays, trend, and autoregressive trend. Based on these models, the percentage of cases attributable to statistically significant risk factors was then estimated. RESULTS: In L&GB emergency admissions daily noise is related to 4.4% (CI95%: 0.8 7.9) of admissions; NO2 to 2.9% (CI95%: 0.1 5.7) and wet cold to 0.2% (CI95%: 0.8 7.9). Heat wave temperature was only related to ALD. In addition, the wet cold association with L&GB is also related to HFNS attributing 1.0% (CI95%: 0.3 1.8) of admissions for this cause. CONCLUSIONS: Daily noise and NO2 are associated with more than 7% of urgent L&GB admissions. Both pollutants, are mainly emitted by road traffic. A reduction of traffic in cities would result in a reduction of emergency admissions due to this cause.

Green and blue space exposure and non-communicable disease related hospitalizations: A systematic review.

The global increase in non-communicable diseases (NCDs) presents a critical public health concern. Emerging evidence suggests that exposure to natural environments may reduce the risk of developing NCDs through multiple pathways. The present systematic review aims to synthesize and evaluate the observational evidence regarding associations between exposure to green and blue spaces and hospital admissions related to NCDs. A comprehensive literature search strategy was conducted in Embase (Ovid), PubMed, and Web of Science. The risk of bias and quality of the evidence were assessed using The Navigation Guide methodology, an approach specifically designed for environmental health research. Of 3060 search results, 17 articles were included. Notably, the majority of the studies (n = 14; 82.4%) were published from 2020 onwards. Most studies were conducted in the United States (n = 6; 35.3%) and China (n = 4; 23.5%). Exposure to green spaces was assessed through all studies, while only three included blue spaces. In terms of study design, cohort design was employed in nearly half of the studies (n = 8; 47.1%), followed by case-crossover design (n = 3, 17.6%). Over 75% of the included studies (n = 13) had a high or probably high rating in the risk of bias assessment. The studies encompassed diverse NCD outcome domains; cardiovascular diseases (CVDs) (n = 10), respiratory diseases (RSDs) (n = 2), heat-related diseases (n = 1), metabolic diseases (n = 2), cancer (n = 1), neurodegenerative diseases (NDDs) (n = 2), and mental health disorders (n = 2). The present review suggests that a clear link between blue space exposure and NCD hospital admissions is not evident. However, exposure to green spaces appears to predominantly have a protective effect, although the direction of the association varies across different outcome domains. The heterogeneity among the outcome domains together with the limited number of studies, emphasizes the need for more robust evidence.

Hospital Admissions for Eating Disorders in Children and Adolescents in Spain: A Population-Based Study.

OBJECTIVE: Limited evidence exists regarding the impact of the COVID-19 pandemic on the onset and trajectory of eating disorders (EDs) among young in Spain. This study aims to analyze the characteristics and recent trends in hospital admissions for EDs within the pediatric population. METHODS: A retrospective analysis was conducted on hospital admissions for EDs among patients aged 10-19 years between 2016 and 2022. The main outcomes examined included hospital rates (overall, stratified by ED type and age group), psychiatric comorbidities, and length of stay. RESULTS: A total of 8275 hospitalizations due to EDs were identified, constituting 1 in 6 hospital admissions for mental illness and behavioral disorders. Predominant characteristics of this population included female sex (93%), aged 15-19 years (58.3%), admission primarily for anorexia nervosa (71.6%), and psychiatric comorbidity (35.6%). Hospital admissions for EDs in the pediatric population showed an increasing trend, with an annual average increase of 11.1% (95% CI: 2.6, 22.6). This rise was led by children aged 10-14 years, with a yearly increase in EDs hospitalization rates of 28.4% (95% CI: 13.5, 56.3) since 2019. Each discharge related to EDs was associated with a median stay of 24 days (IQR: 10, 40). DISCUSSION: Efforts in community healthcare should prioritize early detection and intervention for symptoms indicative of EDs in the pediatric population, aiming to mitigate the severity of cases requiring hospitalization. These findings underscore the necessity for targeted health planning policies to address the growing burden of EDs among Spanish youth.

Eating Disorder and Other Psychiatric Hospitalizations in New Zealand During the COVID-19 Pandemic.

OBJECTIVE: An unprecedented rise in eating disorder presentations has been documented in several countries during the COVID-19 pandemic. We explored this phenomenon by analyzing nationwide psychiatric admissions over 5 years, controlling for demographic variables. METHODS: We retrospectively analyzed all hospitalizations in New Zealand with a primary psychiatric diagnosis from 2017 to 2021, using Poisson regression to calculate admission rates by diagnosis, before and during the pandemic. Using Fisher's exact test and Poisson modeling, national data were validated against a manually collected sample of eating disorder admissions. RESULTS: Eating disorder admissions rose significantly during the pandemic (RR 1.48, p < 0.0001), while other diagnoses remained unchanged or decreased slightly. Anorexia nervosa in 10 to 19-year-old females drove increases, with persistent elevations noted in the 10-14 age group. Pandemic-associated increases were more striking for Maori (RR 2.55), the indigenous Polynesian population, compared with non-Maori (RR 1.43). CONCLUSIONS: Eating disorder hospital presentations increased during the COVID-19 pandemic, while other psychiatric presentations to hospital remained relatively unchanged. Possible drivers include disrupted routines, barriers to healthcare access, altered social networks, and increased social media use. Clinical services require additional resources to manage the increased disease burden, especially in vulnerable pediatric and indigenous populations. Ongoing monitoring will be required to establish the time-course of pandemic-related clinical demand.

Impact of heat waves on human morbidity and hospital admissions in a city of the western mediterranean area.

PURPOSE: The effect of heat waves on mortality is well known, but current evidence on morbidity is limited. Establishing the consequences of these events in terms of morbidity is important to ensure communities and health systems can adapt to them. METHODS: We thus collected data on total daily emergency hospital admissions, admissions to critical care units, emergency department admissions, and emergency admissions for specific diagnoses to Hospital Universitario de Son Espases from 1 January 2005 to 31 December 2021. A heat wave was defined as a period of ≥ 2 days with a maximum temperature ≥ 35 °C, including a 7 day lag effect (inclusive). We used a quasi-Poisson generalized linear model to estimate relative risks (RRs; 95%CI) for heat wave-related hospital admissions. RESULTS: Results showed statistically significant increases in total emergency admissions (RR 1.06; 95%CI 1 - 1.12), emergency department admissions (RR 1.12; 95%CI 1.07 - 1.18), and admissions for ischemic stroke (RR 1.26; 95%CI 1.02 - 1.54), acute kidney injury (RR 1.67; 95%CI 1.16 - 2.35), and heat stroke (RR 18.73, 95%CI 6.48 - 45.83) during heat waves. CONCLUSION: Heat waves increase hospitalization risk, primarily for thromboembolic and renal diseases and heat strokes.

Associations between outpatient care and later hospital admissions for patients with chronic obstructive pulmonary disease - a registry study from Norway.

BACKGROUND: Although chronic obstructive pulmonary disease (COPD) admissions put a substantial burden on hospitals, most of the patients' contacts with health services are in outpatient care. Traditionally, outpatient care has been difficult to capture in population-based samples. In this study we describe outpatient service use in COPD patients and assess associations between outpatient care (contact frequency and specific factors) and next-year COPD hospital admissions or 90-day readmissions. METHODS: Patients over 40 years of age residing in Oslo or Trondheim at the time of contact in the period 2009-2018 were identified from the Norwegian Patient Registry (in- and outpatient hospital contacts, rehabilitation) and the KUHR registry (contacts with GPs, contract specialists and physiotherapists). These were linked to the Regular General Practitioner registry (characteristics of the GP practice), long-term care data (home and institutional care, need for assistance), socioeconomic and-demographic data from Statistics Norway and the Cause of Death registry. Negative binomial models were applied to study associations between combinations of outpatient care, specific care factors and next-year COPD hospital admissions and 90-day readmissions. The sample consisted of 24,074 individuals. RESULTS: A large variation in the frequency and combination of outpatient service use for respiratory diagnoses (GP, emergency room, physiotherapy, contract specialist and outpatient hospital contacts) was apparent. GP and outpatient hospital contact frequency were strongly associated to an increased number of next-year hospital admissions (1.2-3.2 times higher by increasing GP frequency when no outpatient hospital contacts, 2.4-5 times higher in combination with outpatient hospital contacts). Adjusted for healthcare use, comorbidities and sociodemographics, outpatient care factors associated with lower numbers of next-year hospitalisations were fees indicating interaction between providers (7% reduction), spirometry with GP or specialist (7%), continuity of care with GP (15%), and GP follow-up (8%) or rehabilitation (18%) within 30 days vs. later following any current year hospitalisations. For 90-day readmissions results were less evident, and most variables were non-significant. CONCLUSION: As increased use of outpatient care was strongly associated with future hospitalisations, this further stresses the need for good communication between providers when coordinating care for COPD patients. The results indicated possible benefits of care continuity within and interaction between providers.

Impact of a complex health services intervention in long-term care nursing homes on 3-year overall survival: results from the CoCare study.

BACKGROUND: The Coordinated medical Care (CoCare) project aimed to improve the quality of medical care in nursing homes by optimizing collaboration between nurses and physicians. We analyze the impact of the CoCare intervention on overall survival. METHODS: The effect of time-varying treatment on 3-year overall survival was analyzed with treatment as time-varying covariate within the entire cohort. To reduce bias due to non-random assignment to treatment groups, regression adjustment was applied. Therefore, age, sex, and level of care were used as potential confounders. RESULTS: The study population consisted of 8,893 nursing home residents (NHRs), of which 1,330 participated in the CoCare intervention. The three-year overall survival was 49.8% in the entire cohort. NHRs receiving the intervention were associated with a higher survival probability compared to NHRs of the control group. In a univariable cox model with time-dependent treatment, the intervention was associated with a hazard ratio of 0.70 [95%CI 0.56-0.87, p = 0.002]. After adjustment for age, sex and level of care, the hazard ratio increased to 0.82 but was still significant [95%CI 0.71-0.96, p = 0.011]. CONCLUSION: The analysis shows that optimizing collaboration between nurses and physicians leads to better survival of NHRs in Germany. This adds to the already published favorable cost-benefit ratio of the CoCare intervention and shows that a routine implementation of optimized collaboration between nurses and physicians is highly recommended.

Development and Validation of a Robust and Interpretable Early Triaging Support System for Patients Hospitalized With COVID-19: Predictive Algorithm Modeling and Interpretation Study.

BACKGROUND: Robust and accurate prediction of severity for patients with COVID-19 is crucial for patient triaging decisions. Many proposed models were prone to either high bias risk or low-to-moderate discrimination. Some also suffered from a lack of clinical interpretability and were developed based on early pandemic period data. Hence, there has been a compelling need for advancements in prediction models for better clinical applicability. OBJECTIVE: The primary objective of this study was to develop and validate a machine learning-based Robust and Interpretable Early Triaging Support (RIETS) system that predicts severity progression (involving any of the following events: intensive care unit admission, in-hospital death, mechanical ventilation required, or extracorporeal membrane oxygenation required) within 15 days upon hospitalization based on routinely available clinical and laboratory biomarkers. METHODS: We included data from 5945 hospitalized patients with COVID-19 from 19 hospitals in South Korea collected between January 2020 and August 2022. For model development and external validation, the whole data set was partitioned into 2 independent cohorts by stratified random cluster sampling according to hospital type (general and tertiary care) and geographical location (metropolitan and nonmetropolitan). Machine learning models were trained and internally validated through a cross-validation technique on the development cohort. They were externally validated using a bootstrapped sampling technique on the external validation cohort. The best-performing model was selected primarily based on the area under the receiver operating characteristic curve (AUROC), and its robustness was evaluated using bias risk assessment. For model interpretability, we used Shapley and patient clustering methods. RESULTS: Our final model, RIETS, was developed based on a deep neural network of 11 clinical and laboratory biomarkers that are readily available within the first day of hospitalization. The features predictive of severity included lactate dehydrogenase, age, absolute lymphocyte count, dyspnea, respiratory rate, diabetes mellitus, c-reactive protein, absolute neutrophil count, platelet count, white blood cell count, and saturation of peripheral oxygen. RIETS demonstrated excellent discrimination (AUROC=0.937; 95% CI 0.935-0.938) with high calibration (integrated calibration index=0.041), satisfied all the criteria of low bias risk in a risk assessment tool, and provided detailed interpretations of model parameters and patient clusters. In addition, RIETS showed potential for transportability across variant periods with its sustainable prediction on Omicron cases (AUROC=0.903, 95% CI 0.897-0.910). CONCLUSIONS: RIETS was developed and validated to assist early triaging by promptly predicting the severity of hospitalized patients with COVID-19. Its high performance with low bias risk ensures considerably reliable prediction. The use of a nationwide multicenter cohort in the model development and validation implicates generalizability. The use of routinely collected features may enable wide adaptability. Interpretations of model parameters and patients can promote clinical applicability. Together, we anticipate that RIETS will facilitate the patient triaging workflow and efficient resource allocation when incorporated into a routine clinical practice.

Identifying the process and agency characteristics associated with poor utilization outcomes in home healthcare.

This study identified the process and agency characteristics associated with poor utilization outcomes - higher percentages of patients (i) admitted to an acute care organization and (ii) visited an emergency room (ER) unplanned without hospitalization - for home health agencies (HHAs) in the United States. We conducted a secondary analysis of data about HHAs' various characteristics, process adherence levels, and utilization outcomes collected from disparate public repositories for 2010-2022. We developed descriptive tree-based models using HHAs' hospital admission or ER visit percentages as response variables. Across the board, hospital admission percentages have steadily improved while ER percentages deteriorated for an extended period. Recently, checking for fall risks and depression was associated with improved outcomes for urban agencies. In general, rural HHAs had worse utilization outcomes than urban HHAs. Targeted investments and improvement initiatives can help rural HHAs close the urban-rural gap in the future.

Dental and maxillofacial injuries associated with domestic violence against women in Israel: A report for 2011-2021.

BACKGROUND/AIM: The WHO, in its 2002 report, indicated the dramatic worldwide increase in the incidence of intentional injuries affecting people of all ages and both sexes, but especially children, women, and the elderly. The aim of this study was to analyze dental and maxillofacial injuries associated with domestic violence against women in Israel between the years 2011-2021. METHODS: This was a retrospective cohort study based on data from the Israeli National Trauma Registry (INTR). The INTR provides comprehensive data on hospitalized patients from all six Level I trauma centers (TC) and 15 of the 20 Level II TCs in Israel. Women, ages 14 and older, injured and hospitalized due to domestic violence between 2011 and 2021 were identified. RESULTS: Between 2011 and 2021, there were 1818 cases of women ages 14 + that were hospitalized due to violence, excluding terror, occupational trauma, and attempted suicide. Out of these injuries, 753 cases were attributed to domestic violence, 537 were defined as non-domestic violence and 528 were a result of a brawl/fight. Of the domestic violence cases, 5% (38) exhibited maxillofacial injuries compared to the non-domestic violence cases where 6.2% (33) exhibited maxillofacial injuries and the brawl group where 5.7% (30) exhibited maxillofacial injuries. The most injured areas in domestic violence cases were the maxilla followed by the zygomatic bone and the mandible. Almost half of the domestic violence cases (47.7%) required surgical intervention during their hospitalization. The spouse was the perpetrator responsible for the domestic violence in the majority of the cases. CONCLUSIONS: Dental professionals might be able, in some cases, to identify and report domestic violence signs and thus, better understanding of the specific characteristics of domestic violence related to traumatic injuries is important.

Short-term associations between ambient PM1, PM2.5, and PM10 and hospital admissions, length of hospital stays, and hospital expenses for patients with cardiovascular diseases in rural areas of Fuyang, East China.

Evidence on the impacts of PM1, PM2.5, and PM10 on the hospital admissions, length of hospital stays (LOS), and hospital expenses among patients with cardiovascular disease (CVD) is still limited in China, especially in rural areas. This study was performed in eight counties of Fuyang from 1 January 2015 to 30 June 2017. We use a three-stage time-series analysis to explore the effects of short-term exposure to PM1, PM2.5, and PM10 on hospital admissions, LOS, and hospital expenses for CVDs. An increment of 10 ug/m3 in PM1, PM2.5, and PM10 corresponded to an increment of 1.82% (95% CI: 1.34, 2.30), 0.96% (95% CI: 0.44, 1.48), and 0.79% (95% CI: 0.63%, 0.95%) in CVD hospital admissions, respectively. We observed that daily concentrations of PMs were associated with an increase in hospital admissions, LOS, and expenses for CVDs. Sustained endeavors are required to reduce air pollution so as to attenuate disease burdens from CVDs.

Short-term association between air pollution and daily genitourinary disorder admissions in Lanzhou, China.

The aim of this study was to determine the relationship between short-term exposure to ambient air pollution and the number of daily hospital admissions for genitourinary disorders in Lanzhou. Hospital admission data and air pollutants, including PM2.5, PM10, SO2, NO2, O38h and CO, were obtained from the period 2013 to 2020. A generalized additive model (GAM) combined with distribution lag nonlinear model (DLNM) based on quasi-Poisson distribution was used by the controlling for trends, weather, weekdays and holidays. Short-term exposure to PM2.5, NO2 and CO increased the risk of genitourinary disorder admissions with RR of 1.0096 (95% CI 1.0002-1.0190), 1.0255 (95% CI 1.0123-1.0389) and 1.0686 (95% CI 1.0083-1.1326), respectively. PM10, O38h and SO2 have no significant effect on genitourinary disorders. PM2.5 and NO2 are more strongly correlated in female and ≥ 65 years patients. CO is more strongly correlated in male and < 65 years patients. PM2.5, NO2 and CO are risk factors for genitourinary morbidity, and public health interventions should be strengthened to protect vulnerable populations.

Predicting hospital admissions for upper respiratory tract complaints: An artificial neural network approach integrating air pollution and meteorological factors.

This study uses artificial neural networks (ANNs) to examine the intricate relationship between air pollutants, meteorological factors, and respiratory disorders. The study investigates the correlation between hospital admissions for respiratory diseases and the levels of PM10 and SO2 pollutants, as well as local meteorological conditions, using data from 2017 to 2019. The objective of this study is to clarify the impact of air pollution on the well-being of the general population, specifically focusing on respiratory ailments. An ANN called a multilayer perceptron (MLP) was used. The network was trained using the Levenberg-Marquardt (LM) backpropagation algorithm. The data revealed a substantial increase in hospital admissions for upper respiratory tract diseases, amounting to a total of 11,746 cases. There were clear seasonal fluctuations, with fall having the highest number of cases of bronchitis (N = 181), sinusitis (N = 83), and upper respiratory infections (N = 194). The study also found demographic differences, with females and people aged 18 to 65 years having greater admission rates. The performance of the ANN model, measured using R2 values, demonstrated a high level of predictive accuracy. Specifically, the R2 value was 0.91675 during training, 0.99182 during testing, and 0.95287 for validating the prediction of asthma. The comparative analysis revealed that the ANN-MLP model provided the most optimal result. The results emphasize the effectiveness of ANNs in representing the complex relationships between air quality, climatic conditions, and respiratory health. The results offer crucial insights for formulating focused healthcare policies and treatments to alleviate the detrimental impact of air pollution and meteorological factors.