Excess Admissions Research Articles

Physician performance scores used to predict emergency department admission numbers and excessive admissions burden

BackgroundOvercrowding in hospitals is associated with a panoply of adverse events. Inappropriate decisions in the emergency department (ED) contribute to overcrowding. The performance of individual physicians as part of the...

Combined impact of heat and dust on diabetes hospitalization in Kuwait

IntroductionIn Kuwait, a severe diabetes and obesity epidemic coexists with intense dust storms and harsh summer heat. While, theoretically, this interplay between dust, heat, and diabetes presents a serious public...

Is alcohol and psychoactive medication use associated with excess hospital length-of-stay and admission frequency? A cross-sectional, observational study

BackgroundHospital length-of-stay and admission frequency are commonly used indicators of disease burden and health resource expenditures. However, the impact of psychoactive prescription medication use and harmful alcohol consumption on both the duration and frequency of hospital admissions is under-explored.MethodsWe conducted an analysis of data gathered from 2872 patients admitted to the Emergency Department at Lovisenberg Diaconal Hospital in Oslo, Norway. Psychoactive medicines (benzodiazepines, opioids, and z-hypnotics) were detected via liquid chromatography-mass spectrometry analysis of whole blood, while alcohol consumption was self-reported through the Alcohol Use Disorder Identification Test-4 (AUDIT-4). Using logistic regression, we examined associations with our primary outcomes, which were excess length-of-stay and admission frequency, defined as exceeding the sample median of 3.0 days and 0.2 admissions per year, respectively.ResultsCompared to the absence of psychoactive medication, and after adjusting for age, gender, malignant disease, pre-existing substance use disorder and admission due to intoxication, the detection of two or more psychoactive medicines was associated with both excess length-of-stay (odds ratio [OR], 1.60; 95% confidence interval [CI], 1.20 to 2.14) and yearly hospitalization rate (OR, 3.72; 95% CI, 2.64 to 5.23). This association persisted when increasing the definition for excess length-of-stay to 4 and 5 days and to 1.0 and 1.5 admissions per year for admission frequency. Harmful alcohol consumption (AUDIT-4 scores of 9 to 16) was not associated with excess length-of-stay, but with excess admission frequency when defined as more than 1.0 admission per year when compared to scores of 4 to 6 (OR, 2.68; 95% CI, 1.58 to 4.57).ConclusionsPsychoactive medication use is associated with both excess length-of-stay and increased antecedent admission frequency, while harmful alcohol consumption may be associated with the latter. The utility of our findings as a causal factor should be explored through intervention-based study designs.

Health-care resource use among patients who use illicit opioids in England, 2010-20: A descriptive matched cohort study.

People who use illicit opioids have higher mortality and morbidity than the general population. Limited quantitative research has investigated how this population engages with health-care, particularly regarding planned and primary care. We aimed to measure health-care use among patients with a history of illicit opioid use in England across five settings: general practice (GP), hospital outpatient care, emergency departments, emergency hospital admissions and elective hospital admissions. This was a matched cohort study using Clinical Practice Research Datalink and Hospital Episode Statistics. Primary and secondary care practices in England took part in the study. A total of 57 421 patients with a history of illicit opioid use were identified by GPs between 2010 and 2020, and 172 263 patients with no recorded history of illicit opioid use matched by age, sex and practice. We estimated the rate (events per unit of time) of attendance and used quasi-Poisson regression (unadjusted and adjusted) to estimate rate ratios between groups. We also compared rates of planned and unplanned hospital admissions for diagnoses and calculated excess admissions and rate ratios between groups. A history of using illicit opioids was associated with higher rates of health-care use in all settings. Rate ratios for those with a history of using illicit opioids relative to those without were 2.38 [95% confidence interval (CI) = 2.36-2.41] for GP; 1.99 (95% CI = 1.94-2.03) for hospital outpatient visits; 2.80 (95% CI = 2.73-2.87) for emergency department visits; 4.98 (95% CI = 4.82-5.14) for emergency hospital admissions; and 1.76 (95% CI = 1.60-1.94) for elective hospital admissions. For emergency hospital admissions, diagnoses with the most excess admissions were drug-related and respiratory conditions, and those with the highest rate ratios were personality and behaviour (25.5, 95% CI = 23.5-27.6), drug-related (21.2, 95% CI = 20.1-21.6) and chronic obstructive pulmonary disease (19.4, 95% CI = 18.7-20.2). Patients who use illicit opioids in England appear to access health services more often than people of the same age and sex who do not use illicit opioids among a wide range of health-care settings. The difference is especially large for emergency care, which probably reflects both episodic illness and decompensation of long-term conditions.

The impact of inpatient bloodstream infections caused by antibiotic-resistant bacteria in low- and middle-income countries: A systematic review and meta-analysis.

Bloodstream infections (BSIs) produced by antibiotic-resistant bacteria (ARB) cause a substantial disease burden worldwide. However, most estimates come from high-income settings and thus are not globally representative. This study quantifies the excess mortality, length of hospital stay (LOS), intensive care unit (ICU) admission, and economic costs associated with ARB BSIs, compared to antibiotic-sensitive bacteria (ASB), among adult inpatients in low- and middle-income countries (LMICs). We conducted a systematic review by searching 4 medical databases (PubMed, SCIELO, Scopus, and WHO's Global Index Medicus; initial search n = 13,012 from their inception to August 1, 2022). We only included quantitative studies. Our final sample consisted of n = 109 articles, excluding studies from high-income countries, without our outcomes of interest, or without a clear source of bloodstream infection. Crude mortality, ICU admission, and LOS were meta-analysed using the inverse variance heterogeneity model for the general and subgroup analyses including bacterial Gram type, family, and resistance type. For economic costs, direct medical costs per bed-day were sourced from WHO-CHOICE. Mortality costs were estimated based on productivity loss from years of potential life lost due to premature mortality. All costs were in 2020 USD. We assessed studies' quality and risk of publication bias using the MASTER framework. Multivariable meta-regressions were employed for the mortality and ICU admission outcomes only. Most included studies showed a significant increase in crude mortality (odds ratio (OR) 1.58, 95% CI [1.35 to 1.80], p < 0.001), total LOS (standardised mean difference "SMD" 0.49, 95% CI [0.20 to 0.78], p < 0.001), and ICU admission (OR 1.96, 95% CI [1.56 to 2.47], p < 0.001) for ARB versus ASB BSIs. Studies analysing Enterobacteriaceae, Acinetobacter baumanii, and Staphylococcus aureus in upper-middle-income countries from the African and Western Pacific regions showed the highest excess mortality, LOS, and ICU admission for ARB versus ASB BSIs per patient. Multivariable meta-regressions indicated that patients with resistant Acinetobacter baumanii BSIs had higher mortality odds when comparing ARB versus ASB BSI patients (OR 1.67, 95% CI [1.18 to 2.36], p 0.004). Excess direct medical costs were estimated at $12,442 (95% CI [$6,693 to $18,191]) for ARB versus ASB BSI per patient, with an average cost of $41,103 (95% CI [$30,931 to $51,274]) due to premature mortality. Limitations included the poor quality of some of the reviewed studies regarding the high risk of selective sampling or failure to adequately account for relevant confounders. We provide an overview of the impact ARB BSIs in limited resource settings derived from the existing literature. Drug resistance was associated with a substantial disease and economic burden in LMICs. Although, our results show wide heterogeneity between WHO regions, income groups, and pathogen-drug combinations. Overall, there is a paucity of BSI data from LMICs, which hinders implementation of country-specific policies and tracking of health progress.

The Costs Of Disparities In Preventable Heart Failure Hospitalizations In The US South, 2015-17.

Black Americans in the US South have high rates of preventable heart failure hospitalizations, which reflects systemic inequities that also produce economic costs. We measured the direct medical costs of disparities in preventable heart failure admissions (that is, excess admissions) among Medicare beneficiaries living in six states in the US South (Kentucky, Arkansas, Florida, Georgia, Mississippi, and North Carolina). We used 2015-17 data from the Healthcare Cost and Utilization Project and constructed negative binomial models with state-level fixed effects to calculate adjusted admission rates with heart failure as the principal diagnosis. We calculated the number of these admissions that would have been avoided if Black, Hispanic, Asian/Pacific Islander, and American Indian/Alaska Native Medicare beneficiaries had the same admission rates as White beneficiaries. We found 28,213 excess admissions (48percent excess) with $60,845,855 annual costs among Black beneficiaries, 3,499 (14percent excess) with $8,179,381 annual costs among Hispanic beneficiaries, and 550 (51percent excess) with $1,093,472 in annual costs among American Indian/Alaska Native beneficiaries. Failure to address heart failure treatment inequities in the community has a high opportunity cost.

Ozone pollution and hospital admissions for cardiovascular events.

The available literature on morbidity risk of cardiovascular diseases associated with ambient ozone pollution is still limited. This study examined the potential acute effects of exposure to ambient ozone pollution on hospital admissions of cardiovascular events in China. A two-stage multi-city time-series study approach was used to explore the associations of exposure to ambient ozone with daily hospital admissions (n = 6 444 441) for cardiovascular events in 70 Chinese cities of prefecture-level or above during 2015-17. A 10 μg/m3 increment in 2-day average daily 8 h maximum ozone concentrations was associated with admission risk increases of 0.46% [95% confidence interval (CI): 0.28%, 0.64%] in coronary heart disease, 0.45% (95% CI: 0.13%, 0.77%) in angina pectoris, 0.75% (95% CI: 0.38%, 1.13%) in acute myocardial infarction (AMI), 0.70% (95% CI: 0.41%, 1.00%) in acute coronary syndrome, 0.50% (95% CI: 0.24%, 0.77%) in heart failure, 0.40% (95% CI: 0.23%, 0.58%) in stroke and 0.41% (95% CI: 0.22%, 0.60%) in ischemic stroke, respectively. The excess admission risks for these cardiovascular events associated with high ozone pollution days (with 2-day average 8-h maximum concentrations ≥100 µg/m3 vs. < 70 µg/m3) ranged from 3.38% (95% CI: 1.73%, 5.06%) for stroke to 6.52% (95% CI: 2.92%, 10.24%) for AMI. Ambient ozone was associated with increased hospital admission risk for cardiovascular events. Greater admission risks for cardiovascular events were observed under high ozone pollution days. These results provide evidence for the harmful cardiovascular effects of ambient ozone and call for special attention on the control of high ozone pollution.

Hospitalisation for mental health disorders in Australians with type 1 or type 2 diabetes

AimsTo determine the burden and leading reasons for mental health hospitalisation among Australians with diabetes. MethodsWe determined the incidence of hospitalisation for all mental health disorders in people with type 1 or type 2 diabetes of all ages by linking the National Diabetes Services Scheme to hospital admission datasets from 2010 to 2017. We compared those with type 2 diabetes aged 15 and above to the general population using excess hospitalisations per 100,000 person-years associated with diabetes. ResultsDepressive disorders were the leading reason for mental health admission in Australians with diabetes, responsible for 6.09 (95% CI 5.78–6.42) and 7.05 (6.95–7.14) admissions per 1,000 person-years in those with type 1 and type 2 diabetes, respectively. When considering only one admission per person, mental health admission rates were up to 90% lower. Among males with type 2 diabetes, stress and adjustment disorders were the leading cause of excess admissions compared to the general population, while depressive disorders were the leading cause in females. ConclusionsWe found a substantial burden of psychiatric hospitalisations among Australians with diabetes, reinforcing the importance of mental health awareness among diabetes clinicians, and support by psychiatric teams for those with diabetes to prevent readmission.

Seasonal Effects on Hospitalizations Due to Mood and Psychotic Disorders: A Nationwide 31-Year Register Study.

PurposeTo examine seasonal patterns of hospital admissions due to mood and psychotic disorders and to investigate whether the admission rates show variation according to the seasonal daylength (photoperiods).Patients and MethodsA retrospective nationwide register-based cohort of all psychiatric admissions (N=978,079) during 1987–2017 in Finland was utilized. The smoothed time-series of adjusted ratio of observed and expected (O/E) daily counts were estimated to examine seasonal variation. The mean O/E with 95% confidence intervals (CI) was used to study the admission rates by photoperiods. The calendar days were classified into the 71-day photoperiods based on the daylength (long/summer, short/winter, equal/spring, equal/fall) and the pace of change in daylength (slowly/rapidly increasing/decreasing daylength).ResultsManic episodes peaked in summer during the long (mean O/E=1.10, 95% CI=1.06–1.13) and slowly decreasing (1.09, 1.06–1.13) photoperiods and had a nadir in winter during the slowly increasing (0.93, 0.89–0.98) photoperiod. Admissions for unipolar depressive (UPD) episodes peaked in autumn and in spring at the end of the rapidly decreasing (1.03, 1.02–1.04) and increasing (1.03, 1.01–1.04) photoperiod, and dropped in summer during the long and slowly decreasing (0.95, 0.94–0.96) photoperiods. Bipolar depressive (BPD) and mixed episodes signaled excess admissions in autumn and in spring. Admissions for schizophrenia were higher than expected from summer to early-autumn, during the long and slowly decreasing photoperiods (1.02, 1.02–1.03), and lower than expected in other seasons, especially in mid-spring during the rapidly increasing photoperiod (0.98, 0.98–0.99).ConclusionThe study indicates the seasonality and photoperiodicity of mental disorders, especially for manic episodes. The seasonal pattern is similar between schizophrenia and manic episodes, and between UPD, BPD, and mixed episodes.

Short-Term Coarse Particulate Exposure and Daily Cardio-Respiratory Hospital Admissions in the Helsinki Capital Region

BACKGROUND AND AIM Short-term exposure to coarse inhalable particles (2.5 µg/m3&amp;#x3e;PMcoarse&amp;#x3c;10 µg/m3) has been suggested to increase the risk of respiratory disease independently of fine particles, but studies present mixed findings which are even less clear for other outcomes. This study aims to assess the relationship between short-term exposure to PMcoarse and total admissions for cardio-pulmonary diseases. METHODS We conducted a seventeen-year (01/2001-12/2017) time-series study of the daily admissions for cardio-respiratory disease in relation to the mean levels of coarse particles. We obtained air pollution data from the Helsinki Region Environmental Services Authority, meteorological data from the Finnish Meteorological Institute, and hospital exit records from the Finnish Institute for Health and Welfare. We modelled the association between particles and cardiorespiratory admissions using log-linked quasi-Poisson regression. Penalised splines were used to adjust for the time-trend and the meteorological variables. These models were also adjusted for the weekday, pollen concentration, and influenza outbreaks. Different lag structures were explored in both single-pollutant and multipollutant models. The multipollutant models were simultaneously adjusted for PM2.5, NO2, and O3. RESULTS The mean(standard deviation) concentration of PMcoarse was 6.6(5.9) (µg/m3), while the mean (standard deviation) daily numbers of cardiovascular and respiratory admissions were 25.9(7.3) and 21.3(7.4), respectively. A 10 µg/m3 increase in the same day PMcoarse was associated with a 1.7% (95% CI, 0.4%—3.1%) and a 1.9% (95% CI, 0.5%—3.4%) excess daily risk of respiratory admissions in the single-pollutant and multipollutant models, respectively; same-day excess cardiovascular admissions risks were 0.6% (95% CI, -0.5%—1.7%) and 0.3% (95% CI, -0.9%—1.4%) in similar models. CONCLUSIONS Short-term exposure to PMcoarse can increase respiratory admission risks independently of co-pollutants but has a less determinate effect on cardiovascular admissions. A guideline framework should be considered for PMcoarse. KEYWORDS Coarse Particles, Cardiovascular Admissions, Respiratory Admissions, Time-Series, Fine Particles

Black-White Risk Differentials in Pediatric COVID-19 Hospitalization and Intensive Care Unit Admissions in the USA.

PurposeThe COVID-19 morbidity with SARS-CoV-2 as a causative pathogenic microbe remains a pandemic with children experiencing less mortality but with severe manifestations. The current study aimed to assess SARS-CoV-2 cumulative incidence, COVID-19 hospitalization, and ICU admission with respect to racial differentials.Materials and MethodsA cross-sectional nonexperimental epidemiologic design was used to examine pediatric COVID-19 data from CDC during 2020. The variables assessed were ICU admissions, hospitalization, sex, race, and region. The Chi-Square (X2) statistic was used to examine the independence of the variables by race, while the binomial regression model was used to predict racial risk differentials in hospitalization and ICU admissions.ResultsThe pediatric COVID-19 data observed the cumulative incidence of hospitalization to be 96,376, while ICU admission was 12,448. Racial differences were observed in hospitalization, ICU admissions, sex, and region. With respect to COVID-19 hospitalization, Black/African American (AA) children were two times as likely to be hospitalized compared to their White counterparts, prevalence risk ratio (pRR) = 2.20, 99% confidence interval (CI = 2.12–2.28). Similarly, Asians were 45% more likely to be hospitalized relative to their White counterparts, pRR = 1.45, 99% CI = 1.32–1.60. Regarding ICU admission, there was a disproportionate racial burden, implying excess ICU admission among Black/AA children relative to their White counterparts, pRR = 5.18, 99% CI = 4.44–6.04. Likewise, Asian children were 3 times as likely to be admitted to the ICU compared to their White counterparts, pRR = 3.36, 99% CI = 2.37–4.77. Additionally, American Indians/Alaska Natives were 2 times as likely to be admitted to ICU, pRR = 2.54, 99% CI = 0.82–7.85.ConclusionRacial disparities were observed in COVID-19 hospitalization and ICU admission among the US children, with Black/AA children being disproportionately affected, implying health equity transformation.

Performance of the CURB-65, ISARIC-4C and COVID-GRAM scores in terms of severity for COVID-19 patients.

BackgroundIn the COVID‐19 pandemic, difficulties have been experienced in the provision of healthcare services because of excessive patient admissions to hospitals and emergency departments. It has become important to use clear and objective criteria for the early diagnosis of patients with high‐risk classification and clinical worsening risk.ObjectiveThe aim of this study was to assess the prognostic accuracy of CURB‐65, ISARIC‐4C and COVID‐GRAM scores in patients hospitalised for COVID‐19 and to compare the scoring systems in terms of predicting in‐hospital mortality and intensive care unit requirement.MethodsThe files of all COVID‐19 patients over the age of 18 who were admitted to the emergency department and hospitalised between September 1, 2020 and December 1, 2020 were retrospectively scanned. The area under the receiver operating characteristic curve and Youden J Index were used to compare scoring systems for predicting in‐hospital mortality and intensive care requirement.ResultsThere were 481 patients included in this study. The median age of the patients was 67 (52‐79). In terms of in‐hospital mortality, the AUC of CURB‐65, ISARIC‐4C and COVID‐GRAM were 0.846, 0.784 and 0.701 respectively. In terms of intensive care requirement, the AUC of CURB‐65, ISARIC‐4C and COVID‐GRAM were 0.898, 0.797 and 0.684 respectively. In our study, Youden's J indexes of CURB‐65, ISARIC‐4C and COVID‐GRAM scores were found to be 0.59, 0.27 and 0.01 respectively, for mortality prediction of COVID‐19 patients. Whereas Youden's J indexes were found to be 0.63, 0.26 and 0.01 respectively for determining intensive care requirement.ConclusionsAmong the scoring systems assessed, CURB‐65 score had better performance in predicting in‐hospital mortality and ICU requirement in COVID‐19 patients. ISARIC‐4C has been found successful in identifying low‐risk patients and the use of the ISARIC‐4C score with CURB‐65 increases the accuracy of risk assessment.

Estimating the Acute Health Impacts of Fire-Originated PM2.5 Exposure During the 2017 California Wildfires: Sensitivity to Choices of Inputs.

Exposure to wildfire smoke increases the risk of respiratory and cardiovascular hospital admissions. Health impact assessments, used to inform decision‐making processes, characterize the health impacts of environmental exposures by combining preexisting epidemiological concentration–response functions (CRFs) with estimates of exposure. These two key inputs influence the magnitude and uncertainty of the health impacts estimated, but for wildfire‐related impact assessments the extent of their impact is largely unknown. We first estimated the number of respiratory, cardiovascular, and asthma hospital admissions attributable to fire‐originated PM2.5 exposure in central California during the October 2017 wildfires, using Monte Carlo simulations to quantify uncertainty with respect to the exposure and epidemiological inputs. We next conducted sensitivity analyses, comparing four estimates of fire‐originated PM2.5 and two CRFs, wildfire and nonwildfire specific, to understand their impact on the estimation of excess admissions and sources of uncertainty. We estimate the fires accounted for an excess 240 (95% CI: 114, 404) respiratory, 68 (95% CI: −10, 159) cardiovascular, and 45 (95% CI: 18, 81) asthma hospital admissions, with 56% of admissions occurring in the Bay Area. Although differences between impact assessment methods are not statistically significant, the admissions estimates' magnitude is particularly sensitive to the CRF specified while the uncertainty is most sensitive to estimates of fire‐originated PM2.5. Not accounting for the exposure surface's uncertainty leads to an underestimation of the uncertainty of the health impacts estimated. Employing context‐specific CRFs and using accurate exposure estimates that combine multiple data sets generates more certain estimates of the acute health impacts of wildfires.

A RETROSPECTIVE STUDY TO DETERMINE THE EFFECT OF “REFERRAL-IN” ADMISSIONS ON THE FUNCTIONING OF GYNECOLOGY & OBSTETRICS DEPARTMENT IN A TERTIARY CARE HOSPITAL OF NORTH INDIA.

Introduction: Regionalization envisages a two-way ow of patients &amp; services designated as “Referralin” and “Referral-out” cases.”Referral-in” generally means patients from Sub Center, Primary Health Center, Community Health Center &amp; District Hospitals Referred to Tertiary Care Hospital for Specialized care.”Referred-out” Generally means patients from Tertiary Care Hospitals to Higher Centers like Apex Institutions including AIIMS (New Delhi),SKIMS(Srinagar).PGIMER(Chandigarh, SGPGI(Lucknow), etc. for Super specialized treatment. Objective: To determine the effect of Referral- in admissions on the functioning of Gynecology &amp; Obstetrics Department in a Teaching Hospital. Methodology: An Observational study was conducted over a period of 12 months from February 2019 to January 2020 in a 750 –bedded Tertiary Care Hospital of Jammu(UT) popularly Known as Shri Maharaja Gulab Singh(SMGS) Hospital, Jammu. Observations &amp; Results: A detailed description of academic as well as functional status of Gynae &amp; Obs. Department including Faculty-position, OPD patients, Inpatients admitted, Deliveries conducted(LSCS &amp; MLE), Surgical Operations(Major as well as Minor) along with Bed-Occupancy Rate(BOR) &amp; Referred-in Admissions during the study duration was recon ciliated &amp; put forth in Tabulated Form after collecting from the Medical Records Department of the Hospital &amp; displayed Statistically in Bar-Charts &amp; pie-Chart. Discussion: Excessive Referral-in admissions to Teaching Hospital from PHC,SDH,DH &amp; AH Level results in Overcrowding/Congestion in Hospital Wards culminating in Exhaustion of Resources like Drugs, Medicines, Reagents &amp; other logistics. Supportive Services like Sanitation, Ambulance Transportation &amp; Dietary facilities get worsened thereby exaggerating the Sepsis as well as nasocomial infection rate. There are increased chances of Corruption, &amp; Violence/Verbal Scufes between Hospital Staff &amp; Attendants of patients. Conclusion &amp; Recommendation: Instead of irrationally referring the patients to Teaching Hospitals from Lower level Health Care Facilities(HCF), they should be rst sent to Associated Medical College Hospitals established at different Districts before being referred to Provincial Tertiary care Hospital thereby reducing the extra-load over Teaching Hospitals resulting in rapid depletion of resources as well as Medico- Social and Law &amp; Order problems.

A Multi-Faceted Intervention to Reduce Obstetric Hemorrhage Risk at University Hospitals [01M

INTRODUCTION: We describe a systematic approach to mitigating obstetric hemorrhage risk at University Hospitals (UH), a northeast Ohio-based system of eighteen hospitals, including seven hospitals providing obstetric services and delivering approximately 8000 women/year. METHODS: From 2009-2015, obstetric hemorrhage (OBH) led to two maternal deaths and other harms in the form of excessive transfusions, ICU admissions, and hysterectomies as definitive treatment. OBH accounted for 11% of litigation costs ($7.4 M) during this period. To reduce harm associated with OBH, we implemented the following interventions: 1. Clinical Practice Guideline for management of anemia in pregnancy; 2. EMR field to capture hemorrhage risk factors and prompt type and cross on admission; 3. Mandating transfer of high risk patients for delivery at a tertiary care center; 4. Clinical Practice Guideline for management of OBH (including active management of third stage of labor); 5. Shifting from estimating to quantifying blood loss by weight; and 6. Standardization of OBH carts on all L&amp;D units. RESULTS: From 2015-2017, there was: 40% increase in the number of patients admitted to L&amp;D with hemoglobin &gt;10 mg/dl; 68% decrease in the number of obstetric patients requiring transfusions of ≥four units of packed red blood cells; 77% decrease in the number of peri-partum hysterectomies; and 91% decrease in the number of patients admitted to ICU for OBH. There were no maternal deaths from OBH and no new suits or claims related to OBH between 2014 and 2018. CONCLUSION: This multifaceted intervention was associated with decreased patient harm and reduced litigation costs associated with obstetric hemorrhage.

The effect of extreme temperature on emergency admissions across vulnerable populations in England: an observational study

BackgroundClimate change poses an unfamiliar challenge to population health and health-systems resilience. Although previous studies have estimated morbidity attributable to heat or cold across cities, we provide, to our knowledge, the first large-scale, population-wide assessment of the effect of extreme temperatures on excess emergency admissions in England and among vulnerable populations, who could be disproportionately affected. MethodsIn this observational study, we combined all daily inpatient admissions during 2001–12 in England with meteorological data using inverse distance weighting. We exploited random daily variation in temperature experienced by hospitals and a 30-day lag period, using a distributed lag model with multiple fixed-effects controlling for seasonal factors, to examine interaction effects across diseases with age and the indices of multiple deprivation. FindingsWe analysed 29 371 084 emergency admissions. A day with temperature above 30°C was associated with 3·5 more admissions per hospital (SE 0·45), relative to a 10–15°C day. This increased to 14·1 excess admissions per hospital (SE 5·56) over the following 30 days, generating 786 excess admissions across England per heatwave day. A day under –5°C generated 3·8 more admissions per hospital (SE 0·33), or 966 excess admissions across England. This increased to 62·3 admissions per hospital (SE 4·83) over the following 30 days. These effects were heterogeneous across age and deprivation level. Populations older than 74 years were up to 8 times more affected by extreme temperatures. Individuals living in low-employment and low-income areas were 2–10 times more likely to be admitted during a temperature shock. These results were statistically significant (p<0·0001) and passed several robustness and falsification tests. InterpretationTo our knowledge, this is the first study to determine heterogeneous morbidity risks of temperature across an entire population using a robust, near-causal methodology. Population health is negatively affected by hot and cold temperature shocks, with older people and those living in low-employment and low-income areas disproportionately affected. Findings were unadjusted for pollution and possible individual protective behaviours, providing underestimated—yet policy-applicable—risks of temperature. A heterogeneous lag effect indicates the importance of considering vulnerable populations in policy making to ensure mitigation and resilience policies are not restricted to immediate temperature shocks only and are sensitive to vulnerable populations, mitigating inequalities in access to health care. FundingBritish Academy and Imperial College Business School.

Causes of hospital admission and mortality among 6683 people who use heroin: A cohort study comparing relative and absolute risks

BackgroundMortality in high-risk groups such as people who use illicit drugs is often expressed in relative terms such as standardised ratios. These measures are highest for diseases that are rare in the general population, such as hepatitis C, and may understate the importance of common long-term conditions. Population6683 people in community-based treatment for heroin dependence between 2006 and 2017 in London, England, linked to national hospital and mortality databases with 55,683 years of follow-up. MethodAge- and sex-specific mortality and hospital admission rates in the general population of London were used to calculate the number of expected events. We compared standardised ratios (relative risk) to excess deaths and admissions (absolute risk) across ICD-10 chapters and subcategories. ResultsDrug-related diseases had the highest relative risks, with a standardised mortality ratio (SMR) of 48 (95% CI 42–54) and standardised admission ratio (SAR) of 293 (95% CI 282–304). By contrast, other diseases had an SMR of 4.4 (95% CI 4.0–4.9) and an SAR of 3.15 (95% CI 3.11–3.19). However, the majority of the 621 excess deaths (95% CI 569–676) were not drug-related (361; 58%). The largest groups were liver disease (75 excess deaths) and COPD (45). Similarly, 80% (11,790) of the 14,668 excess admissions (95% CI 14,382–14,957) were not drug-related. The largest groups were skin infections (1073 excess admissions), alcohol (1060), COPD (812) and head injury (612). ConclusionsAlthough relative risks of drug-related diseases are very high, most excess morbidity and mortality in this cohort was caused by common long-term conditions.

A comprehensive home-care program for health promotion of mothers with preeclampsia: protocol for a mixed method study

BackgroundOne of the most common complications of pregnancy and the third cause of maternal death is preeclampsia. Thus this group of mothers should be supported, trained and received efficient health care services. Home-care is one strategy to improvement complications of Pregnancy. In Iran, high-risk pregnancies care provide in health care centers, hospitals and clinics by midwives and obstetricians. In this mixed method study, at first, a qualitative approach will be used to identify preeclampsia mothers’ health needs and home-care strategies for them. Then, the qualitative results will be emerged with literature review and expert ideas to develop a comprehensive home-care program which fits with the needs of these mothers in Iran.MethodsThis study is a qualitative- quantitative mixed exploratory research that consists of three sequential phases. In the first step, in qualitative study, all the women with preeclampsia, obstetricians, midwives, and maternal health policy makers will select purposefully. Health care needs and home-care strategies for mothers with preeclampsia will be determined. Sampling continues until data saturation. In the second step, an expert panel will be formed to prioritization of home-care needs and strategies extracted from result of qualitative study and review of literature. Afterwards, Primary home care program will be designed. In the third step, Delphi method will be used of minimum 10–15 experts including: obstetricians, midwives, and reproductive health professionals about validation of this home-care program by questionnaires in three rounds, then the final program is being developed.DiscussionIt is expected conducting a mixed method study to develop a home care program mothers with preeclamsia to improve their health status and wellbeing while reducing additional health care costs through preventing excessive admissions and interventions. Moreover it wants to follow up properly and timely high risk pregnant women. This study might be helpful in improvement quality of health services and promote health equity.ConclusionDeveloping a home care program for maternal health care especially for high risk pregnancy by considering Iran socio-cultural context.

Improving Health Care Management Through Persistent Homology of Time-Varying Variability of Emergency Department Patient Flow.

Excessive admissions at the emergency department (ED) is a phenomenon very closely linked to the propagation of viruses. It is a cause of overcrowding for EDs and a public health problem. The aim of this work is to give EDs' leaders more time for decision making during this period. Based on the admissions time series associated with specific clinical diagnoses, we will first perform a detrended fluctuation analysis to obtain the corresponding variability time series. Next, we will embed this time series on a manifold to obtain a point cloud representation and use topological data analysis through persistent homology technic to propose two early real-time indicators. One is the early indicator of abnormal arrivals at the ED whereas the second gives the information on the time index of the maximum number of arrivals. The performance of the detectors is parameter dependent and it can evolve each year. That is why we also propose to solve a biobjective optimization problem to track the variations of this parameter.

The Melbourne epidemic thunderstorm asthma event 2016: an investigation of environmental triggers, effect on health services, and patient risk factors

A multidisciplinary collaboration investigated the world's largest, most catastrophic epidemic thunderstorm asthma event that took place in Melbourne, Australia, on Nov 21, 2016, to inform mechanisms and preventive strategies. Meteorological and airborne pollen data, satellite-derived vegetation index, ambulance callouts, emergency department presentations, and data on hospital admissions for Nov 21, 2016, as well as leading up to and following the event were collected between Nov 21, 2016, and March 31, 2017, and analysed. We contacted patients who presented during the epidemic thunderstorm asthma event at eight metropolitan health services (each including up to three hospitals) via telephone questionnaire to determine patient characteristics, and investigated outcomes of intensive care unit (ICU) admissions. Grass pollen concentrations on Nov 21, 2016, were extremely high (>100 grains/m3). At 1800 AEDT, a gust front crossed Melbourne, plunging temperatures 10°C, raising humidity above 70%, and concentrating particulate matter. Within 30 h, there were 3365 (672%) excess respiratory-related presentations to emergency departments, and 476 (992%) excess asthma-related admissions to hospital, especially individuals of Indian or Sri Lankan birth (10% vs 1%, p<0·0001) and south-east Asian birth (8% vs 1%, p<0·0001) compared with previous 3 years. Questionnaire data from 1435 (64%) of 2248 emergency department presentations showed a mean age of 32·0 years (SD 18·6), 56% of whom were male. Only 28% had current doctor-diagnosed asthma. 39% of the presentations were of Asian or Indian ethnicity (25% of the Melbourne population were of this ethnicity according to the 2016 census, relative risk [RR] 1·93, 95% CI 1·74-2·15, p <0·0001). Of ten individuals who died, six were Asian or Indian (RR 4·54, 95% CI 1·28-16·09; p=0·01). 35 individuals were admitted to an intensive care unit, all had asthma, 12 took inhaled preventers, and five died. Convergent environmental factors triggered a thunderstorm asthma epidemic of unprecedented magnitude, tempo, and geographical range and severity on Nov 21, 2016, creating a new benchmark for emergency and health service escalation. Asian or Indian ethnicity and current doctor-diagnosed asthma portended life-threatening exacerbations such as those requiring admission to an ICU. Overall, the findings provide important public health lessons applicable to future event forecasting, health care response coordination, protection of at-risk populations, and medical management of epidemic thunderstorm asthma. None.