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Headline
The study found that most of the variation in avoidable admission rates is explained by deprivation but some is explained by differing practices in a range of emergency and urgent care services including ambulance services, hospitals and emergency departments.
Abstract
Background:
Recent increases in emergency admission rates have caused concern. Some emergency admissions may be avoidable if services in the emergency and urgent care system are available and accessible. A set of 14 conditions, likely to be rich in avoidable emergency admissions, was identified by expert consensus.
Objective:
We aimed to understand variation in avoidable emergency admissions between different emergency and urgent care systems in England.
Methods:
The design was a sequential mixed-methods study in three phases. In phase 1 we calculated an age- and sex-adjusted avoidable admission rate for 2008–11. We located routine data on characteristics of emergency and urgent care systems and used linear regression to explain variation in avoidable admissions rates in 150 systems. In phase 2 we undertook in-depth case studies in six systems to identify further factors. A key part of these case studies was interviews with commissioners, service providers and patient representatives, totalling 82 interviews. In phase 3 we returned to the linear regression to test further factors identified in the case studies.
Results:
The 14 conditions accounted for 3,273,395 admissions in 2008–11 (22% of all emergency admissions). The mean age- and sex-adjusted admission rate was 2258 per year per 100,000 population, with a 3.4-fold variation between systems (1268–4359). Characteristics of the population explained the majority of variation: deprivation explained 72% of variation, with urban/rural status explaining 3% more. Systems serving populations with high levels of deprivation and in urban areas had high rates of potentially avoidable admissions. Interviewees described the complexity of deprivation, representing high levels of morbidity, low awareness of alternative services to emergency departments and high expressed need for immediate access to urgent care. Factors related to emergency departments (EDs), hospitals, emergency ambulance services and general practice explained a further 10% of variation in avoidable admissions. Systems with high, potentially avoidable, admission rates had high rates of acute beds (suggesting supply-induced demand), high rates of attendance at EDs (which have been associated with poor perceived access to general practice), high rates of conversion from ED attendances to admissions, and low rates of non-transport to emergency departments by emergency ambulances. The six case studies revealed further possible explanations of variation: there was variation in how hospitals coded admissions; some systems focused proactively on admission avoidance whereas others were more interested in hospital discharge, for example use of multidisciplinary teams based at acute trusts; there were different levels of integration between different services such as health and social care, and acute and community trusts; and some systems faced more challenging problems around geographical boundaries operating for different services in the system. Interviewees often described admission as the easy or safe option.
Conclusions:
Deprivation explained most of the variation in avoidable admission rates. Research is needed to understand the complex relationship between deprivation and avoidable admission, and to develop interventions tailored to avoid admissions from deprived communities. Standardisation of coding of admissions would reduce variation.
Funding:
The National Institute for Health Research Health Service and Research Delivery programme.
Contents
- Plain English summary
- Scientific summary
- Chapter 1. Background
- Chapter 2. Overview of methods
- Chapter 3. Calculation of potentially avoidable admission rate
- Chapter 4. Phase 1: explaining variation in potentially avoidable admissions rates for geographically based systems
- Chapter 5. Phase 1: explaining variation in potentially avoidable admissions rates for acute trust-based systems
- Chapter 6. Phase 2: case studies of six emergency and urgent care systems – methods and overarching themes
- Chapter 7. Individual case studies
- Chapter 8. Comparison of multiple cases
- Population characteristics have not been adequately adjusted for in phase 1
- Acute trusts have different coding practices for admissions which affect variation in the standardised avoidable admissions rate
- Integrated systems have lower standardised avoidable admissions rates
- Proactive approach to admission avoidance gives low standardised avoidable admissions rate
- Hospital-centric systems have higher standardised avoidable admissions rates
- Systems with support services out of hours have lower standardised avoidable admissions rates
- Well-functioning emergency departments can help to avoid admissions
- The conversion variable in the geographically based system phase 1 regression may be incorrect
- Systems which are not the primary population for an acute trust struggle with integration and therefore have high standardised avoidable admissions rates
- Systems with low resources cannot fund services to avoid admissions
- Conclusions
- Factors to test in phase 3
- Chapter 9. Phase 3 integration of regression and case studies
- Chapter 10. Discussion
- Summary of findings
- Comparison with other research
- Strengths and limitations
- Generalisability, transferability and reflexivity
- Patient and public involvement
- Challenging the conceptual framework
- Impact on national reviews of emergency care
- Conclusions
- Implications for health care
- Recommendations for research (in order of priority)
- Acknowledgements
- References
- Appendix 1 Sources of information for regressions
- Appendix 2 Performance of regressions
- Appendix 3 Topic guide for interviews
- List of abbreviations
Article history
The research reported in this issue of the journal was funded by the HS&DR programme or one of its proceeding programmes as project number 10/1010/08. The contractual start date was in August 2011. The final report began editorial review in February 2014 and was accepted for publication in July 2014. The authors have been wholly responsible for all data collection, analysis and interpretation, and for writing up their work. The HS&DR editors and production house have tried to ensure the accuracy of the authors’ report and would like to thank the reviewers for their constructive comments on the final report document. However, they do not accept liability for damages or losses arising from material published in this report.
Declared competing interests of authors
Steve Goodacre is Deputy Chairperson of the National Institute for Health Research Health Technology Assessment Clinical Trials Evaluation and Trials Board.
- NLM CatalogRelated NLM Catalog Entries
- Explaining variation in emergency admissions: a mixed-methods study of emergency...Explaining variation in emergency admissions: a mixed-methods study of emergency and urgent care systems
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