Emergency Respiratory Admissions: Influence of Practice, Population and Hospital Factors

Purdy, Sarah; Griffin, TP; Salisbury, Chris; Sharp, Deborah

doi:10.1258/jhsrp.2010.010013

Cited by 42 publications

(55 citation statements)

References 19 publications

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“…In studies of the UK Quality and Outcomes Framework, in which incentives were directly tied to measured quality of care, any observed decreases in hospital admissions accompanying observed changes in quality were small, [25][26][27] and some studies found no association between measured quality and hospital admissions. 28,29 Research to date, largely from the United Kingdom and United States, has provided mixed evidence of the effectiveness of these programs. 24,[30][31][32][33][34] Studies of Ontario's pay-forperformance initiatives showed modest improvements in delivery of some preventive services 35,36 and no change in management of patients with diabetes.…”

Section: Discussionmentioning

confidence: 99%

“…39 Most research in this area focuses on care for individual diseases, using the delivery of specific services as indicators of quality. 24,[30][31][32][33][34] Evidence of the effect of incentive-based programs on broader outcomes such as access to primary care, continuity of care, 40 hospital admissions [25][26][27][28][29]41,42 and overall resource use 30,34,43 has been inconclusive.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

A population-based analysis of incentive payments to primary care physicians for the care of patients with complex disease

Lavergne

Law

Peterson

et al. 2016

CMAJ

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

A population-based analysis of incentive payments to primary care physicians for the care of patients with complex disease

Lavergne

Law

Peterson

et al. 2016

CMAJ

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“…Many researchers have explored the factors affecting emergency admission rates overall, or for specific conditions, through studying variation between general practices in the UK [10][11][12][13][14][15][16][17][18][19] and internationally, 20 commissioning organisations in the UK 12,[21][22][23] or hospitals internationally. 24,25 Factors explaining variation were related to the population, particularly in terms of deprivation and health ( Table 1).…”

Section: Factors Affecting Emergency Admissionsmentioning

confidence: 99%

“…Much of the focus on health service-related factors affecting variation in emergency admissions has been on primary care ( Table 2), for example the quality and supply of, 10,12,14,17 and access to, primary care. 10,12,15,16 There is some evidence that factors within hospitals can affect emergency admissions, such as bed numbers and availability, 16 physical space 24 and clinical decision-making. 25 Research has also been undertaken on factors affecting variation in use of a common gateway to emergency admission -EDs.…”

Section: Factors Affecting Emergency Admissionsmentioning

confidence: 99%

Explaining variation in emergency admissions: a mixed-methods study of emergency and urgent care systems

O’Cathain

Knowles

Turner

et al. 2014

Health Services and Delivery Research

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BackgroundRecent 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.ObjectiveWe aimed to understand variation in avoidable emergency admissions between different emergency and urgent care systems in England.MethodsThe 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.ResultsThe 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.ConclusionsDeprivation 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.FundingThe National Institute for Health Research Health Service and Research Delivery programme.

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“…4,12,13 This study contrasts with the findings of other research that reported decreased emergency admission with increasing distance from hospital and with higher deprivation. [31][32][33] The study differs from those in that a multilevel analysis was used clustering at the primary care trust level. The study concurs with others that reported increased emergency admissions with an increasing proportion of the population who are white.…”

Section: Comparison With Existing Literaturementioning

confidence: 99%

Emergency hospital admissions for asthma and access to primary care: cross-sectional analysis

Fleetcroft¹,

Noble²,

Martin³

et al. 2016

Br J Gen Pract

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Background: Access to general practices may be an important determinant of emergency admissions for asthma, as early treatment of exacerbations has been shown to prevent deterioration. Aim: To determine whether access to primary care is associated with emergency admissions for asthma. Design and Setting: Cross-sectional analysis of data from English practices in 2010/11. Method: Negative binomial regression was used to explore the associations between emergency admissions for asthma and seven measures of patient-reported access to general practice services taken from GP Patient Survey, controlled for the characteristics of practice populations. Incidence rate ratios (IRR) were calculated for each association. Results: 7806 (95%) of practices had data for all variables. There were 3,134,106 patients with asthma, and there were 55,570 emergency admissions with asthma. Admission rates were lower in practices with a higher composite access score (adjusted IRR for 10% change in variable 0.679 (95%CI 0.665 to 0.708)). Admissions were higher in those practices with higher proportions of the practice population who were white, and in practices with lower performance in the Quality and Outcomes Framework indicator ‘asthma review in past 15 months’ (Asthma 6). Assuming these associations were causal, a higher access score of 10% was associated with a decrease of 17,837 admissions per year for these practices. Conclusion: Practices with higher patient reported access had lower rates of emergency admissions for asthma. Policy makers should consider improving access to primary care as one potential way to help prevent emergency hospital admissions for asthma

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Emergency Respiratory Admissions: Influence of Practice, Population and Hospital Factors

Cited by 42 publications

References 19 publications

A population-based analysis of incentive payments to primary care physicians for the care of patients with complex disease

A population-based analysis of incentive payments to primary care physicians for the care of patients with complex disease

Explaining variation in emergency admissions: a mixed-methods study of emergency and urgent care systems

Emergency hospital admissions for asthma and access to primary care: cross-sectional analysis

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