Seamus Coveney

Social deprivation, population dependency ratio and an extended hospital episode — Insights from acute medicine

BACKGROUND Patients from deprived backgrounds have a higher in-patient mortality following an emergency medical admission; this study aimed to investigate the extent to which Deprivation status and the population Dependency Ratio influenced extended hospital episodes. METHODS All Emergency Medical admissions (75,018 episodes of 41,728 patients) over 12 years (2002-2013) categorized by quintile of Deprivation Index and Population Dependency Rates (proportion of non-working/working) were evaluated against length of stay (LOS). Patients with an Extended LOS (ELOS), >30 days, were investigated, by Deprivation status, Illness Severity and Co-morbidity status. Univariate and multi-variable risk estimates (Odds Rates or Incidence Rate Ratios) were calculated, using truncated Poisson regression. RESULTS Hospital episodes with ELOS had a frequency of 11.5%; their median LOS (IQR) was 55.0 (38.8, 97.6) days utilizing 57.6% of all bed days by all 75,018 emergency medical admissions. The Deprivation Index independently predicted the rate of such ELOS admissions; these increased approximately five-fold (rate/1000 population) over the Deprivation Quintiles with model adjusted predicted admission rates of for Q1 0.93 (95% CI: 0.86, 0.99), Q22.63 (95% CI: 2.55, 2.71), Q3 3.84 (95% CI: 3.77, 3.91), Q4 3.42 (95% CI: 3.37, 3.48) and Q5 4.38 (95% CI: 4.22, 4.54). Similarly the Population Dependency Ratio Quintiles (dependent to working structure of the population by small area units) independently predicted extended LOS admissions. CONCLUSION The admission of patients with an ELOS is strongly influenced by the Deprivation status and the population Dependency Ratio of the catchment area. These factors interact, with both high deprivation and Dependency cohorts having a major influence on the numbers of emergency medical admission patients with an extended hospital episode.

Deprivation index and dependency ratio are key determinants of emergency medical admission rates

BACKGROUND Patients from deprived backgrounds have a higher in-patient mortality following an emergency medical admission; there has been debate as to the extent to which deprivation and population structure influences hospital admission rate. METHODS All emergency medical admissions to an Irish hospital over a 12-year period (2002-2013) categorized by quintile of Deprivation Index and Dependency Ratio (proportion of population <15 or ≥ 65 years) from small area population statistics (SAPS), were evaluated against hospital admission rates. Univariate and multivariable risk estimates (Odds Ratios (OR) or Incidence Rate Ratios (IRR)) were calculated, using logistic or zero truncated Poisson regression as appropriate. RESULTS 66,861 admissions in 36,214 patients occured during the study period. The Deprivation Index quintile independently predicted the admission rate/1000 population, Q1 9.4 (95%CI 9.2 to 9.7), Q2 16.8 (95%CI 16.6 to 17.0), Q3 33.8 (95%CI 33.5 to 34.1), Q4 29.6 (95%CI 29.3 to 29.8) and Q5 45.4 (95%CI 44.5 to 46.2). Similarly the population Dependency Ratio was an independent predictor of the admission rate with adjusted predicted rates of Q1 20.8 (95%CI 20.5 to 21.1), Q2 19.2 (95%CI 19.0 to 19.4), Q3 27.6 (95%CI 27.3 to 27.9), Q4 43.9 (95%CI 43.5 to 44.4) and Q5 34.4 (95%CI 34.1 to 34.7). A high concurrent Deprivation Index and Dependency Ratio were associated with very high admission rates. CONCLUSION Deprivation Index and population Dependency Ratio are key determinants of the rate of emergency medical admissions.

Social deprivation and hospital admission rates, length of stay and readmissions in emergency medical admissions

BACKGROUND Patients from deprived backgrounds have a higher in-patient mortality following an emergency medical admission. How deprivation relates to the admission or readmission incidence rates, episode length of stay (LOS) and ancillary resource utilization is less clear. METHODS All emergency medical admissions (66,861 episodes in 36,214 patients) between 2002 and 2013, categorized by quintile of Irish National Deprivation Index were assessed against admission or readmission incidence rates (/1000 local population by electoral division), LOS and utilization of five ancillary services. Univariate and multi-variable risk estimates (odds ratios (OR) or incidence rate ratios (IRR)) were calculated, using truncated Poisson regression. RESULTS The deprivation index quintile was strongly correlated with the emergency medical admission rate with IRR (as compared with quintile 1) as follows: Q2 1.99 (95% CI: 1.96, 2.01), Q3 3.45 (95% CI: 3.41, 3.49), Q4 3.27 (95% CI: 3.23, 3.31) and Q5 4.29 (95% CI: 4.23, 4.35). LOS was not influenced by deprivation status; although increasing deprivation resulted in increased utilization of social services (OR 1.04: 95% CI: 1.03, 1.06), with a lower requirement for occupational therapy (OR 0.94: 95% CI: 0.93, 0.96) and speech/language services (OR 0.83: 95% CI: 0.80, 0.86). There was a rather decreased use of ancillary services with increasing deprivation; however, the readmission rate was strongly predicted by deprivation status. CONCLUSION Deprivation status strongly influenced the admission and readmission rates for medical patients admitted as emergencies; however, ancillary resource utilization was not increased. Deprivation index will increase demand on hospital resources due to the aggregate effect on both admission and readmission incidence rates.

Deprivation influences the emergency admission rate of ambulatory care sensitive conditions

Ambulatory care sensitive conditions (ACSCs) are a group of conditions judged to be suitable for healthcare efficiency initiatives to reduce the rate of hospital admissions. All emergency medical admissions to an Irish hospital between 2002 and 2013 were assessed for ACSCs. They were categorised by quintile of deprivation index and evaluated against hospital admission rate. Univariable and multivariable risk estimates were calculated, using logistic regression or zero-truncated Poisson regression. There were 66,861 admissions in 36,214 patients. ACSCs represented 66.4% of admissions. The rate of ACSC admissions increased with deprivation index, Q1 10.4 (95% confidence interval (CI) 10.2-10.5), Q2 17.3 (95% CI 17.2-17.5), Q3 34.0 (95% CI 33.7-34.2), Q4 30.2 (95% CI 30.0-30.4) and Q5 44.5 (95% CI 43.8- 45.1) (p<0.001), corresponding incidence rate ratios compared with Q1 were: Q2 1.67 (95% CI 1.64-1.70), Q3 3.28 (95% CI 3.22-3.33), Q4 2.92 (95% CI 2.87-2.97) and Q5 4.29 (95% CI 4.20-4.39) (p<0.001). ACSCs are common in acute medical admissions and are strongly influenced by the underlying social demographics of the population.

High Risk Subgroups Sensitive to Air Pollution Levels Following an Emergency Medical Admission

For three cohorts (the elderly, socially deprived, and those with chronic disabling disease), the relationship between the concentrations of particulate matter (PM10), sulphur dioxide (SO2), or oxides of nitrogen (NOx) at the time of hospital admission and outcomes (30-day in-hospital mortality) were investigated All emergency admissions (90,423 episodes, recorded in 48,035 patients) between 2002 and 2015 were examined. PM10, SO2, and NOx daily levels from the hospital catchment area were correlated with the outcomes for the older admission cohort (>70 years), those of lower socio-economic status (SES), and with more disabling disease. Adjusted for acuity and complexity, the level of each pollutant on the day of admission independently predicted the 30-day mortality: for PM10–OR 1.11 (95% CI: 1.08, 1.15), SO2–1.20 (95% CI: 1.16, 1.24), and NOx–1.09 (1.06–1.13). For the older admission cohort (≥70 years), as admission day pollution increased (NOx quintiles) the 30-day mortality was higher in the elderly (14.2% vs. 11.3%: p < 0.001). Persons with a lower SES were at increased risk. Persons with more disabling disease also had worse outcomes on days with higher admission particulate matter (PM10 quintiles). Levels of pollutants on the day of admission of emergency medical admissions predicted 30-day hospital mortality.

Particulate matter (PM10) and oxides of Nitrogen (NOx) each independently predict respiratory emergency outcomes

Background: The impact of environmental air pollutants on the outcome of an emergency hospitalisation of respiratory patients has received limited study. We report on how levels of pollutants, particulate matter levels (PM10) and oxides of Nitrogen (NOx) infl uence hospital outcomes (30-day inhospital mortality). Methods: All emergency respiratory admissions (35,523 episodes, in 15,037 patients) were tracked between (2002-2015). Daily levels of PM10 and NOx from the hospital catchment area were correlated with outcome; univariate and multivariate logistic regression examined relationships between air pollution and outcome following adjustment for complexity. Results: There was a signifi cant reduction between 2002 and 2015 in levels of both PM10 20.4 to 12.9 (μg/m3) and NOx levels 76.5 to 38.2 (μg/m 3). An increase in PM10 on the day of admission from lowest (Q1) to highest quintiles (Q5) increased the mortality riskOR 1.31 (1.08–1.60) with absolute deaths rates increasing from 17.1% to 21.1%. Similarly, an increase in NOx at admission from lowest to highest quintiles increased mortality risk OR 1.43 (1.17–1.74) and hospital mortality from 17.4% to 20.7%. Low Socio-Economic status (SES) conferred a greater mortality risk, if admitted on days with higher levels of pollution PM10 (p<0.01) Odds Ratio 1.02 (95% CI: 1.01, 1.04) and NOx (p=0.04) – OR 1.02 (95% CI: 1.00, 1.04). Conclusion: Levels of PM10 and NOx on the day of which respiratory patients had an emergency medical admission independently predicted the 30-day hospital mortality. Low SES status patients admitted on high pollution days had a worse outcome. Research Article Particulate matter (PM10) and oxides of Nitrogen (NOx) each independently predict respiratory emergency outcomes Seán Cournane1, Richard Conway2, Declan Byrne2, Deirdre O’Riordan2, Seamus Coveney3 and Bernard Silke2* 1Medical Physics and Bioengineering Department, St James’s Hospital, Dublin 8, Ireland 2Department of Internal Medicine, St James’s Hospital, Dublin 8, Ireland 3Envo-Geo Environmental Geoinformatics, Ireland Dates: Received: 21 April, 2017; Accepted: 29 June, 2017; Published: 30 June, 2017 *Corresponding author: Bernard Silke, Department of Internal Medicine, St James’s Hospital, Dublin 8, Ireland, Tel: 353 1 416 2777; Email:

Social Factors Determine the Emergency Medical Admission Workload

We related social factors with the annual rate of emergency medical admissions using census small area statistics. All emergency medical admissions (70,543 episodes in 33,343 patients) within the catchment area of St. James’s Hospital, Dublin, were examined between 2002 and 2016. Deprivation Index, Single-Parent status, Educational level and Unemployment rates were regressed against admission rates. High deprivation areas had an approximately fourfold (Incidence Rate Ratio (IRR) 4.0 (3.96, 4.12)) increase in annual admission rate incidence/1000 population from Quintile 1(Q1), from 9.2/1000 (95% Confidence Interval (CI): 9.0, 9.4) to Q5 37.3 (37.0, 37.5)). Single-Parent families comprised 40.6% of households (95% CI: 32.4, 49.7); small areas with more Single Parents had a higher admission rate-IRR (Q1 vs. for Q5) of 2.92 (95% CI: 2.83, 3.01). The admission incidence rate was higher for Single-Parent status (IRR 1.50 (95% CI: 1.46, 1.52)) where the educational completion level was limited to primary level (Incidence Rate Ratio 1.45 (95% CI: 1.43, 1.47)). Small areas with higher educational quintiles predicted lower Admission Rates (IRR 0.85 (95% CI: 0.84, 0.86)). Social factors strongly predict the annual incidence rate of emergency medical admissions.