BackgroundMany emergency admissions are deemed to be potentially avoidable in a well-performing health system.ObjectiveTo measure the impact of population and health system factors on county-level variation in potentially avoidable emergency admissions in Ireland over the period 2014–2016.MethodsAdmissions data were used to calculate 2014–2016 age-adjusted emergency admission rates for selected conditions by county of residence. Negative binomial regression was used to identify which a priori factors were significantly associated with emergency admissions for these conditions and whether these factors were also associated with total/other emergency admissions. Standardised incidence rate ratios (IRRs) associated with a 1 SD change in risk factors were reported.ResultsNationally, potentially avoidable emergency admissions for the period 2014–2016 (266 395) accounted for 22% of all emergency admissions. Of the population factors, a 1 SD change in the county-level unemployment rate was associated with a 24% higher rate of potentially avoidable emergency admissions (IRR: 1.24; 95% CI 1.04 to 1.41). Significant health system factors included emergency admissions with length of stay equal to 1 day (IRR: 1.20; 95% CI 1.11 to 1.30) and private health insurance coverage (IRR: 0.92; 95% CI 0.89 to 0.96). The full model accounted for 50% of unexplained variation in potentially avoidable emergency admissions in each county. Similar results were found across total/other emergency admissions.ConclusionThe results suggest potentially avoidable emergency admissions and total/other emergency admissions are primarily driven by socioeconomic conditions, hospital admission policy and private health insurance coverage. The distinction between potentially avoidable and all other emergency admissions may not be as useful as previously believed when attempting to identify the causes of regional variation in emergency admission rates.

BackgroundIn the past decade, the Republic of Ireland has undertaken significant reconfiguration programmes to improve emergency services. During this time the public healthcare system experienced a large real decrease in resources. This study assesses national and regional population outcomes over the period 2002–2014, and whether changes coincide with system reconfiguration and the financial restrictions imposed by the 2008 recession.MethodsCase fatality ratios (CFRs) were constructed for emergency conditions for 2002–2014. Total emergency conditions and individual condition trends were analysed nationally using joinpoint analysis. National results informed the investigation of trends at a regional and county level using an inverse standard error weighted generalised linear model with a log link to construct funnel plots. County-level CFRs were compared for the first and last 3 years of the period to further investigate the changes to county results over the 13 year period, specifically in comparison to the national-level CFR.ResultsNationally, there was an annual fall in CFRs (2.1%). The decline was faster from 2002 to 2007 (annual percentage change = − 3.4; 95% CI-4.4, − 2.4), compared to 2007–2014 (annual percentage change = − 1.2; 95% CI -1.9, − 0.5). The South-East had a lower rate of decrease and the West had a higher rate. Cross sectional analysis of two periods (2002–2004 and 2012–2014) showed high consistency in the counties performance relative to the national CFR in both periods.ConclusionChange in the national trend coincided with the onset of economic stress on the public health system. Attributing the decline in CFR improvement to economic factors is weakened by the uneven nature of the trend change. No distinct pattern of change was identified among regions which underwent substantial reconfiguration of emergency services.Electronic supplementary materialThe online version of this article (10.1186/s12913-018-3260-1) contains supplementary material, which is available to authorized users.

ObjectivesTo understand the impact of emergency department (ED) reconfiguration on the number of patients waiting for hospital beds on trolleys in the remaining EDs in four geographical regions in Ireland using time-series analysis.SettingEDs in four Irish regions; the West, North-East, South and Mid-West from 2005 to 2015.ParticipantsAll patients counted as waiting on trolleys in an ED for a hospital bed in the study hospitals from 2005 to 2015.InterventionThe system intervention was the reconfiguration of ED services, as determined by the Department of Health and Health Service Executive. The timing of these interventions varied depending on the hospital and region in question.ResultsThree of the four regions studied experienced a significant change in ED trolley numbers in the 12-month post-ED reconfiguration. The trend ratio before and after the intervention for these regions was as follows: North-East incidence rate ratio (IRR) 2.85 (95% CI 2.04 to 3.99, p<0.001), South IRR 0.68 (95% CI 0.51 to 0.89, p=0.006) and the Mid-West IRR 0.03 (95% 1.03 to 2.03, p=0.03). Two of these regions, the South and the Mid-West, displayed a convergence between the observed and expected trolley numbers in the 12-month post-reconfiguration. The North-East showed a much steeper increase, one that extended beyond the 12-month period post-ED reconfiguration.ConclusionsFindings suggest that the impacts of ED reconfiguration on regional level ED trolley trends were either non-significant or caused a short-term shock which converged on the pre-reconfiguration trend over the following 12 months. However, the North-East is identified as an exception due to increased pressures in one regional hospital, which caused a change in trend beyond the 12-month post reconfiguration.

Background A key challenge for most systems is how to provide effective access to urgent and emergency care across rural and urban populations. Tensions about the placement and scope of hospital emergency services are longstanding in Irish political life and there has been recent reform to centralise hospital services in some regions. The focus of this paper is a system approach to examine the geographic variation in resourcing and utilisation of such care across GP practices, out-of-hours care, ambulance services, Emergency Departments and Local Injury Units in Ireland. Methods We used a cross-sectional study design to evaluate variation in resource allocation by aggregating geographic funding to various elements of the urgent and emergency care system and assessing patterns in hospital resource utilisation across the population. Expenditure, staffing, access and activity data were gathered from government sources, individual facilities and service providers, health professional bodies, private firms and central statistics. Data on costs and activity in 2014 are collated and presented at both county and regional levels. Analyses focus on resources spent on urgent and emergency care across geographic areas, the role of population concentration in allocation, the relationship between pre-hospital spending and in-hospital spending, and the utilisation of hospital-based emergency care resources by residents of each county. Results An array of funding mechanisms exists, resulting in a fragmented approach to the resourcing of urgent and emergency care. There are large differences in spending per capita at the county-level, ranging from between €50 and €200 per capita; however, these are less pronounced regionally. Distribution of hospital emergency care resources is highly skewed to the North East of the country, and away from the recently reconfigured South and Mid-West regions. Conclusions This analysis advances the traditional approach of evaluating individual services or hospital resourcing. There are notable differences in utilisation of hospital-based emergency care resources at the regional level, indicating that populations within those regions which have been reconfigured have lower utilisation of hospital resources. There is a clear case for more integration in decision-making around funding and consideration of key principles, such as equity, to guide that process.

There is evidence to suggest that acute hospital reconfiguration of hospital services impacts on patterns of patient flow. Findings have implications for those implementing reconfiguration of acute services.