Deirdre O'Riordan

Emergency department census of patients awaiting admission following reorganisation of an admissions process

Objectives: To determine the impact of reorganisation of an acute admissions process on numbers of people in the emergency department (ED) awaiting admission to a hospital bed in a major teaching hospital. Methods: We studied all emergency medical patients admitted to St James’ Hospital, Dublin, between 1 January 2002 and 31 December 2004. In 2002, patients were admitted to a variety of wards from the ED when a hospital bed became available. In 2003, two centrally located wards were reconfigured to function as an acute medical admissions unit (AMAU) (bed capacity 59), and all emergency patients were admitted directly to this unit from the ED (average 15 admissions per day). The maximum permitted length of stay on the AMAU was 5 days. We recorded the number of patients in the ED, who were awaiting the availability of a hospital bed, at 0700 and 1700 on the days of recording during the 36 month study period. Results: The impact of the AMAU reduced overall hospital length of stay from 7 days in 2002 to 5 days in 2003 and 2004 (p<0.0001). The median number of patients waiting in the ED for a hospital bed reduced from 14 in 2002 to 9 in 2003 and 8 in 2004 (p<0.0001). While age and sex of patients did not differ over the years, the factors that independently contributed to the number of patients awaiting admission were the day of the week, the month of the year, and and the extent of the comorbidity index on the previous day’s intake (p<0.0001). Conclusions: This study found that reorganisation of a system for acute medical admissions can significantly impact on the number of patients awaiting admission to a hospital bed, and allow an ED to operate efficiently and at a level of risk acceptable to patients.

Disabling disease codes predict worse outcomes for acute medical admissions

Concurrent with an extension in longevity, a prodrome of ill‐health (‘disability’ identifiable by certain International Classification of Disease (ICD) 9/ICD10 codes) predates the acute emergency presentation. To date, no study has assessed the effect of such ‘disability’ on outcomes of emergency medical admissions.

Serum albumin as an outcome predictor in hospital emergency medical admissions

BACKGROUND To examine the relationship between admission serum albumin and 30-day mortality during an emergency medical admission. METHODS An analysis was performed of all emergency medical patients admitted to St. Jamess Hospital (SJH), Dublin between 1st January 2002 and 31st December 2008, using the hospital in-patient enquiry (HIPE) system, linked to the patient administration system, and laboratory datasets. Mortality was defined as an in-hospital death within 30 days. Logistic regression was used to calculate unadjusted and adjusted odds ratios (ORs) and 95% confidence intervals for defined albumin subsets. FINDINGS Univariate analysis using predefined criteria based on distribution, identified the groups of <10% and between 10 and 25% of the serum albumin frequency distribution as at increased mortality risk. Their mortality rates were 31.7% and 15.4% respectively; their unadjusted odds rates were 6.35 (5.68, 7.09) and 2.11 (1.90, 2.34). Patients in the lowest 25% of the distribution had a 30-day mortality of 19.9% and this significantly increased risk persisted, after adjustment for other outcome predictors including co-morbidity and illness severity (OR 2.95 (2.49, 3.48): p<0.0001). INTERPRETATION Serum albumin is predictive of 30-day mortality in emergency medical patients; mortality is non-linearly related to baseline albumin. The disproportionate increased death risk for patients in the lowest 25% of the frequency distribution (<36 g/L) is not due to co-morbidity factors or acute illness severity.

Blood cultures in emergency medical admissions: a key patient cohort.

Objectives Blood cultures are performed in the emergency room when sepsis is suspected, and a cohort of patients is thereby identified. The present study investigated the outcomes (mortality and length of hospital stay) in this group following an emergency medical admission. Methods Prospective assessment of all emergency medical admissions presenting to the emergency department at St James’s Hospital, Dublin, over an 11-year period (2002–2012) was carried out. Outcomes including 30-day in-hospital mortality and length of stay were explored in the context of an admission blood culture. Generalized estimating equations, logistic or zero-truncated Poisson multivariate models were used, with adjustment for confounding variables including illness severity, comorbidity, and chronic disabling disease, to assess the effect of an urgent blood culture on mortality and length of stay. Results A total of 60 864 episodes were recorded in 35 168 patients admitted over the time period assessed. Patients more likely to undergo blood cultures in the emergency department were male, younger, and had more comorbidity. Univariate and multivariate analyses showed that those who had a blood culture, irrespective of result, had increased mortality and a longer in-hospital stay. This was highest for those with a positive culture, irrespective of the organism isolated. Conclusion A clinical decision to request a blood culture identified a subset of emergency admissions with markedly worse outcomes. This patient cohort warrants close monitoring in the emergency setting.

High-sensitivity troponin as an outcome predictor in acute medical admissions.

Background Troponin estimation is increasingly performed on emergency medical admissions. We report on a high-sensitivity troponin (hscTn) assay, introduced in January 2011, and its relevance to in-hospital mortality in such patients. Aim To evaluate the impact of hscTn results on in-hospital mortality and the value of incorporating troponin into a predictive score of in-hospital mortality. Methods All patients admitted as general medical emergencies between January 2011 and October 2012 were studied. Patients admitted under other admitting services including cardiology were excluded. We examined outcomes using generalised estimating equations, an extension of generalised linear models that permitted adjustment for correlated observations (readmissions). Margins statistics used adjusted predictions to test for interactions of key predictors while controlling for other variables using computations of the average marginal effect. Results A total of 11 132 admission episodes were recorded. The in-hospital mortality for patients with predefined cut-offs was 1.9% when no troponin assay was requested, 5.1% when the troponin result was below the 25 ng/L ‘normal’ cut-off, 9.7% for a troponin result ≥25 and <50 ng/L, 14.5% for a troponin result ≥50 and <100 ng/L, 34.4% for a troponin result ≥100 and <1000 ng/L, and 58.3% for a troponin result >1000 ng/L. The OR for an in-hospital death for troponin-positive patients was 2.02 (95% CI 1.84 to 2.21); when adjusted for other mortality predictors including illness severity, the OR remained significant at 2.83 (95% CI 2.20 to 3.64). The incorporation of troponin into a multivariate logistic predictive algorithm resulted in an area under the receiver operating characteristic curve to predict an in-hospital death of 0.87 (95% CI 0.85 to 0.88). Conclusions An increase in troponin carries prognostic information in acutely ill medical patients; the extent of the risk conferred justifies incorporation of this information into predictive algorithms for hospital mortality.

Consultant experience as a determinant of outcomes in emergency medical admissions.

BACKGROUND There are little data on the experiential learning of certified consultant specialists and outcomes in acute medicine. We have examined the 30-day in-hospital mortality and hospital length of stay (LOS) in relation to practice duration, using a database of emergency admissions. METHODS All emergency admissions (60,864 episodes in 35,168 patients) over eleven years (January 2002 to December 2012) were evaluated. Consultant staff were categorised by duration of clinical practice as <15 years, 15-20 years, >20≤25 years and >25 years. We used a stepwise logistic regression model to predict 30-day in-hospital death, adjusting risk estimates for major predictor variables. Marginal analysis used adjusted predictions to test for interactions of key predictors, while controlling for other variables. RESULTS Thirty-day in-hospital mortality correlated with time in clinical practice; decreasing from 8.9% and 9.1% with <15 and 15-20 years to 7.7% for each of the categories of >20≤25 years and >25 years. There was a progressive shortening of LOS with extent of clinical practice - from a median 5.0 days (IQR 1.8, 10.3) for consultants within 15 years of registration to 4.6 (IQR 1.7-8.9; p<0.05) at >20≤25 years and 4.4 (IQR 1.7-9.0; p<0.01) with >25 years. Duration of clinical practice predicted mortality in the univariable analysis - odds ratio (OR) 0.85 (95% CI: 0.78, 0.91; p<0.001); when adjusted in a multivariable model, it remained independently predictive--OR 0.87 (95% CI: 0.79, 0.96; p<0.001) for 30-day in-hospital mortality. CONCLUSION Certified specialists appear to continue with experiential learning with evidence of improved outcome after 20 years in clinical practice.

Do consultants differ? Inferences drawn from hospital in-patient enquiry (HIPE) discharge coding at an Irish teaching hospital

Objective: To find out if there was a difference between hospital consultants, all trained in acute general medicine, in length of stay (LOS), re-admission rates, resource utilisation, and diagnostic coding, among patients admitted as emergencies to St James’ Hospital (SJH) Dublin. Methods: A retrospective analysis was performed of data on discharges from hospital, recorded in the hospital in-patient enquiry (HIPE) system, relating to 9204 episodes among 6968 emergency medical patients admitted to SJH between 1 January 2002 and 31 October 2003. For comparative analysis, four physician groups were defined consisting of gastroenterology (GI, n = 4), respiratory (n = 3), general internal medicine (GIM, n = 2), or specialty (n = 5). Results: GIM consultants had the shortest LOS (median 5 days); GIM and respiratory consultants were less likely to have long stay patients (> 30 days, p<0.0001). Patients re-admitted under the same consultant had a longer LOS than those re-admitted under a different consultant (p<0.0001). Endoscopy and GI radiology investigations were used most by GI consultants, computed tomography of the thorax by respiratory, ECHO by respiratory and specialty, and computed tomography of brain by GIM and specialty consultants. GI diagnostic codings were more frequent with GI consultants (p<0.0001), respiratory diagnoses and malignancy with respiratory (p<0.0001 for both), diabetes and hypertension with specialty (p = 0.0017), and heart failure more with GIM consultants (p = 0.001). Conclusions: This study found that the HIPE database was very powerful in predicting differences between hospital consultants in LOS, re-admission rates, resource utilisation, and disease coding. It would be of interest to examine the extent to which protocols and guidelines could reduce such variations.

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.

Air Quality Impacts Mortality in Acute Medical Admissions

BACKGROUND Air quality degraded by black smoke (particulate matter, PM10), sulphur dioxide (SO2) and nitrogen oxide (NO(x)) affects human health. Improvements following national legislation have lowered death rates. Whether background air pollution levels continue to affect human health remains unclear. AIM To determine impact of air pollutant concentrations (PM10, SO2 and NO(x)) on in-hospital mortality for acute medical admissions to St Jamess Hospital over a decade (2002-11). DESIGN All emergency admissions (55,596 episodes in n = 32,581 patients) were tracked prospectively and mortality assessed. Daily levels of PM10, SO2 and NO(x) were obtained from monitoring stations in our catchment area. METHODS Univariate and multivariate logistic regression was employed to examine relationships between pollutant concentration and odds ratio (OR) for death following adjustment for other mortality predictors. RESULTS Mortality related to each pollutant variable assessed (as quintiles of increasing atmospheric concentration) was significantly predictive. For PM10 and SO2, mortality in the highest three quintile concentrations (compared with base quintile) was significantly increased (P < 0.001) with univariate ORs of 1.24, 1.36 and 1.25 for PM10 and 1.43, 1.54 and 1.58 for SO2, respectively. Mortality in all quintile concentrations (compared with base quintile) was significantly increased (P < 0.05) for NO(x) with univariate ORs of 1.14, 1.18, 1.28 and 1.35, respectively. Following adjustment for other mortality predictors such as acute illness severity, all three air pollutants were independently predictive of mortality. CONCLUSION Despite improvement to air quality in Dublin, the prevailing background pollutant concentrations continue to affect human health at levels considered safe and below that previously recognized.