scholarly journals The Relationship Between Social Deprivation and a Weekend Emergency Medical Admission

2016 ◽  
Vol 15 (3) ◽  
pp. 124-129
Author(s):  
Richard Conway ◽  
◽  
Seán Cournane ◽  
Declan Byrne ◽  
Deirdre O’Riordan ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Poisson Regression ◽  
Small Area ◽  
Social Deprivation ◽  
Specific Effect ◽  
Admission Rate ◽  
Medical Admission ◽  
Admission Rates ◽  
Population Unit ◽  
The Relationship

Background: Deprivation increases admission rates; the specific effect of deprivation with regard to weekend admissions is unknown. Methods: We calculated annual weekend admission rates for each small area population unit and related these to quintiles of Deprivation Index from 2002-2014. Univariate and multivariable risk estimates were calculated using truncated Poisson regression. Results: There were 30,794 weekend admissions in 16,665 patients. The admission rate was substantially higher for more deprived areas, 12.7 per 1000 (95%CI 9.4, 14.7) vs 4.6 per 1000 (95%CI 3.3, 5.8). More deprived patients admitted at the weekend had a significantly lower 30-day in-hospital mortality (10.3% vs 14.5%, p<0.001). Conclusion: Deprivation is a powerful determinant of weekend admissions, however these comprise a group of patients with better outcomes.

scholarly journals Scottish rehabilitation services: their relationship to socio-economic deprivation

1993 ◽  
Vol 17 (6) ◽  
pp. 339-340
Author(s):  
Robin G. McCreadie ◽  
Douglas J. Williamson
Keyword(s):  
Mentally Ill ◽  
Social Deprivation ◽  
Psychiatric Hospitals ◽  
Strong Relationship ◽  
Socioeconomic Deprivation ◽  
Community Resources ◽  
Psychiatric Admission ◽  
Admission Rates ◽  
Catchment Areas ◽  
The Relationship

It is well established that there is a strong relationship between psychiatric admission rates and socioeconomic deprivation; the more deprived the area, the more admissions may be expected (Hirsch, 1988). In the development of community resources for the mentally ill, therefore, an aim might be to site the majority of facilities in areas of greatest social deprivation, as that is where the majority of patients will live. It might also be expected that areas of greater deprivation would have more professional NHS staff. The present survey examines the siting of rehabilitation and support services in the catchment areas of Scottish psychiatric hospitals in relation to measures to socioeconomic deprivation. It also examines the relationship between deprivation and numbers of professional NHS staff in the different catchment areas.

Small Area Analysis of Diabetes Complications: Opportunities for Targeting Public Health and Health Services Interventions

2005 ◽  
Vol 11 (3) ◽  
pp. 72 ◽  
Author(s):  
Z Ansari ◽  
MJ Ackland ◽  
NJ Carson ◽  
BCK Choi
Keyword(s):  
Public Health ◽  
Primary Care ◽  
Health Services ◽  
Small Area ◽  
Diabetes Complications ◽  
Admission Rate ◽  
Primary Care Providers ◽  
Care Providers ◽  
Admission Rates ◽  
Rate Ratios

The objective of this paper is to present small area analyses of diabetes complications in Victoria, Australia, and to illustrate their importance for targeting public health and health services interventions. Local government areas in Victoria were aggregated into 32 Primary Care Partnerships (PCP), which are voluntary alliances of primary care providers. The 32 PCP areas were used as the basic geographic units for small area analyses. Admission rates for diabetes complications were age and sex standardised using the direct method and the 1996 Victorian population as the reference. Admission rate ratios were calculated using the Victorian admission rates as the reference. The 95 per cent confidence intervals for the standardised admission rate ratios were based on the Poisson distribution. There was a wide variation (almost fivefold) in admission rates for diabetes complications across the PCP catchments, with the lowest standardised rate ratio of 0.37 and the highest of 1.75. There were 11 PCPs (seven metropolitan, four rural) with admission rate ratios significantly higher than the Victorian average. The seven metropolitan PCPs contributed more than 43% of all admissions and bed days for diabetes complications in Victoria. Small area analyses of diabetes complications are an exciting new development aimed at stimulating an evidence-based dialogue between local area health service providers, planners and policy-makers. The purpose is to provide opportunities to target public health and health services interventions at the local level to improve the management of diabetes complications in the community.

scholarly journals Impact of Seasonality and Influenza Rates on Interventions to Reduce Hospital-Acquired Clostridioides difficile Rates

2020 ◽  
Vol 41 (S1) ◽  
pp. s265-s266
Author(s):  
Jenine Leal ◽  
Peter Faris ◽  
Ye Shen ◽  
Lauren Bresee ◽  
Kathryn Bush ◽  
...  
Keyword(s):  
Poisson Regression ◽  
Cross Correlation ◽  
Admission Rates ◽  
Clostridioides Difficile ◽  
Cross Correlation Analysis ◽  
Harmonic Regression ◽  
Harmonic Components ◽  
Hospital Acquired ◽  
The Relationship ◽  
Over Time

Background: Hospital-acquired Clostridioides difficile infection (HA-CDI) rates are highly variable over time, posing problems for research assessing interventions that might improve rates. By understanding seasonality in HA-CDI rates and the impacts that other factors such as influenza admissions might have on these rates, we can account for them when establishing the relationship between interventions and infection rates. We assessed whether there were seasonal trends in HA-CDI and whether they could be accounted for by influenza rates. Methods: We assessed HA-CDI rates per 10,000 patient days, and the rate of hospitalized patients with influenza per 1,000 admissions in 4 acute-care facilities (n = 2,490 beds) in Calgary, Alberta, from January 2016 to December 2018. We used 4 statistical approaches in R (version 3.5.1 software): (1) autoregressive integrated moving average (ARIMA) to assess dependencies and trends in each of the monthly HA-CDI and influenza series; (2) cross correlation to assess dependencies between the HA-CDI and influenza series lagged over time; (3) Poisson harmonic regression models (with sine and cosine components) to assess the seasonality of the rates; and (4) Poisson regression to determine whether influenza rates accounted for seasonality in the HA-CDI rates. Results: Conventional ARIMA approaches did not detect seasonality in the HA-CDI rates, but we found strong seasonality in the influenza rates. A cross-correlation analysis revealed evidence of correlation between the series at a lag of zero (R = 0.41; 95% CI, 0.10–0.65) and provided an indication of a seasonal relationship between the series (Fig. 1). Poisson regression suggested that influenza rates predicted CDI rates (P < .01). Using harmonic regression, there was evidence of seasonality in HA-CDI rates (2 [2 df] = 6.62; P < .05) and influenza rates (2 [2 df] = 1,796.6; P < .001). In a Poisson model of HA-CDI rates with both the harmonic components and influenza admission rates, the harmonic components were no longer predictive of HA-CDI rates. Conclusions: Harmonic regression provided a sensitive means of identifying seasonality in HA-CDI rates, but the seasonality effect was accounted for by influenza admission rates. The relationship between HA-CDI and influenza rates is likely mediated by antibiotic prescriptions, which needs to be assessed. To improve precision and reduce bias, research on interventions to reduce HA-CDI rates should assess historic seasonality in HA-CDI rates and should account for influenza admissions.Funding: NoneDisclosures: None

scholarly journals Influence of social deprivation, overcrowding and family structure on emergency medical admission rates

QJM ◽  
2016 ◽  
Vol 109 (10) ◽  
pp. 675-680 ◽  
Author(s):  
R. Conway ◽  
D. Byrne ◽  
D. O’Riordan ◽  
S. Cournane ◽  
S. Coveney ◽  
...  
Keyword(s):  
Family Structure ◽  
Social Deprivation ◽  
Medical Admission ◽  
Admission Rates ◽  
Emergency Medical

scholarly journals Disparities in access to mobile devices and e-health literacy among breast cancer survivors

2021 ◽  
Author(s):  
Zoe Moon ◽  
Mira Zuchowski ◽  
Rona Moss-Morris ◽  
Myra S. Hunter ◽  
Sam Norton ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Health Literacy ◽  
Cancer Survivors ◽  
Mobile Devices ◽  
Breast Cancer Survivors ◽  
Social Deprivation ◽  
Logistic Regressions ◽  
Widespread Access ◽  
The Relationship ◽  
Questionnaire Pack

Abstract Background The number of e-health interventions developed for breast cancer survivors continues to increase. However, issues with engagement and retention are common. This study aimed to explore e-health literacy rates and access to smartphones and tablets in a large sample of breast cancer survivors. Methods In study 1, women were recruited from outpatient breast clinics across England and Wales. Eligible women were asked to complete a questionnaire pack to assess their access to devices and their e-health literacy. Multiple regression analyses were run to assess the relationship between technology access and e-health literacy with sociodemographic variables such as age, social deprivation, and education. Study 2 presents a smaller sample recruited through social media who answered a questionnaire relating to use of mobile devices and e-health, and apps. Results Two thousand nine women participated in the study. Seventy-one percent had access to a smartphone, 54% had access to a tablet, and 20% did not have access to either device. Multiple logistic regressions showed that women who were younger, had higher levels of education, and who were from less deprived areas were more likely to have access to either device. Poorer e-health literacy was associated with being older, having less education, and not having access to a mobile device. Conclusions Whilst the results show relatively widespread access to mobile devices, there is evidence of a digital divide across some groups. Online interventions should be developed with consideration of individuals who are less e-health-literate and less technologically adept in order to increase the likelihood of engagement.

scholarly journals Relationship between 24-h venous blood glucose variation and mortality among patients with acute respiratory failure

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaoling Zhang ◽  
Jingjing Zhang ◽  
Jiamei Li ◽  
Ya Gao ◽  
Ruohan Li ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Respiratory Failure ◽  
Hospital Mortality ◽  
Acute Respiratory Failure ◽  
Venous Blood ◽  
Sensitivity Analyses ◽  
Icu Mortality ◽  
Logistic Regression Models ◽  
The Mean ◽  
The Relationship

AbstractEvidence indicates that glucose variation (GV) plays an important role in mortality of critically ill patients. We aimed to investigate the relationship between the coefficient of variation of 24-h venous blood glucose (24-hVBGCV) and mortality among patients with acute respiratory failure. The records of 1625 patients in the Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC II) database were extracted. The 24-hVBGCV was calculated as the ratio of the standard deviation (SD) to the mean venous blood glucose level, expressed as a percentage. The outcomes included ICU mortality and in-hospital mortality. Participants were divided into three subgroups based on tertiles of 24-hVBGCV. Multivariable logistic regression models were used to evaluate the relationship between 24-hVBGCV and mortality. Sensitivity analyses were also performed in groups of patients with and without diabetes mellitus. Taking the lowest tertile as a reference, after adjustment for all the covariates, the highest tertile was significantly associated with ICU mortality [odds ratio (OR), 1.353; 95% confidence interval (CI), 1.018–1.797] and in-hospital mortality (OR, 1.319; 95% CI, 1.003–1.735), especially in the population without diabetes. The 24-hVBGCV may be associated with ICU and in-hospital mortality in patients with acute respiratory failure in the ICU, especially in those without diabetes.

Infection management processes in intensive care and their association with mortality

2021 ◽  
Author(s):  
Leigh P. Fitzpatrick ◽  
Bianca Levkovich ◽  
Steve McGloughlin ◽  
Edward Litton ◽  
Allen C. Cheng ◽  
...  
Keyword(s):  
Intensive Care ◽  
New Zealand ◽  
Hospital Mortality ◽  
Process Of Care ◽  
Infection Management ◽  
Hierarchical Logistic Regression ◽  
Management Processes ◽  
Patient Database ◽  
Improving Patient Care ◽  
The Relationship

Abstract Background ICU-specific tables of antimicrobial susceptibility for key microbial species (‘antibiograms’), antimicrobial stewardship (AMS) programmes and routine rounds by infectious diseases (ID) physicians are processes aimed at improving patient care. Their impact on patient-centred outcomes in Australian and New Zealand ICUs is uncertain. Objectives To measure the association of these processes in ICU with in-hospital mortality. Methods The Australian and New Zealand Intensive Care Society (ANZICS) Adult Patient Database and Critical Care Resources registry were used to extract patient-level factors, ICU-level factors and the year in which each process took place. Descriptive statistics and hierarchical logistic regression were used to determine the relationship between each process and in-hospital mortality. Results The study included 799 901 adults admitted to 173 ICUs from July 2009 to June 2016. The proportion of patients exposed to each process of care was 38.7% (antibiograms), 77.5% (AMS programmes) and 74.0% (ID rounds). After adjusting for confounders, patients admitted to ICUs that used ICU-specific antibiograms had a lower risk of in-hospital mortality [OR 0.95 (99% CI 0.92–0.99), P = 0.001]. There was no association between the use of AMS programmes [OR 0.98 (99% CI 0.94–1.02), P = 0.16] or routine rounds with ID physicians [OR 0.96 (99% CI 0.09–1.02), P = 0.09] and in-hospital mortality. Conclusions Use of ICU-specific antibiograms was associated with lower in-hospital mortality for patients admitted to ICU. For hospitals that do not perform ICU-specific antibiograms, their implementation presents a low-risk infection management process that might improve patient outcomes.

scholarly journals 272 Morbid Obesity in Lower Limb Arthroplasty: Short Length of Stay and Favourable One-Year Outcomes

2021 ◽  
Vol 108 (Supplement_2) ◽  
Author(s):  
M Sharrock ◽  
A Nugur ◽  
S Hossain
Keyword(s):  
Morbid Obesity ◽  
Length Of Stay ◽  
Lower Limb ◽  
Average Length ◽  
Perioperative Complications ◽  
Joint Infection ◽  
Admission Rate ◽  
Tendon Injury ◽  
Morbidly Obese ◽  
Admission Rates

Abstract Introduction There are concerns that BMI is associated with a greater length of stay (LOS) and perioperative complications in lower limb arthroplasty. Method We analysed data from a six-month period to see if there was a correlation between BMI and LOS. We performed a subgroup analysis for patients with morbid obesity (BMI &gt;40). Results 285 TKRs and 195 THRs were analysed. For TKRs, the average length of stay was 2.7 days. There was no significant correlation between BMI and LOS (r=-0.0447, p = 0.2267). The morbidly obese category (n = 33) had the shortest LOS (2.5 days) compared to other BMI categories. 30-day readmission rate was 6%. 90-day re-admission rate was 12%. Six patients had minor wound issues requiring no intervention or antibiotics only. The was one prosthetic joint infection, one stitch abscess, one DVT and one patellar tendon injury. For THRs, the average LOS was 2.9 days. There was no significant correlation between BMI and LOS (r = 0.007, p = 0.4613). The morbid obese category (n = 9) had the shortest LOS (1.9 days) compared to other BMI categories. No patients were readmitted within 90 days or had documented complications. Conclusions Increased BMI is not associated with increased LOS. The morbidly obese had the shortest LOS, and commendable complication and re-admission rates.

scholarly journals Impact of an acute medical admission unit on hospital mortality: a 5-year prospective study

QJM ◽  
2008 ◽  
Vol 101 (6) ◽  
pp. 457-465 ◽  
Author(s):  
T. Rooney ◽  
E.D. Moloney ◽  
K. Bennett ◽  
D. O'Riordan ◽  
B. Silke
Keyword(s):  
Hospital Mortality ◽  
Prospective Study ◽  
Medical Admission
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