Association of population and practice factors with potentially avoidable admission rates for chronic diseases in London: cross sectional analysis

Saxena, Sonia; George, Julie; Barber, Julie; Fitzpatrick, Justine; Majeed, Azeem

doi:10.1258/jrsm.99.2.81

Cited by 77 publications

(67 citation statements)

References 22 publications

(22 reference statements)

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“…Decreased socioeconomic status is consistently associated with increased ED attendance7 33 35 39 40 43 44 and increased EHA 8 16 17 21 22 25 36 45. A similar effect is seen with social isolation and lack of social support for ED attendance35 40 and EHA 8 35 41…”

Section: Resultsmentioning

confidence: 98%

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Which features of primary care affect unscheduled secondary care use? A systematic review

et al. 2014

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ObjectivesTo conduct a systematic review to identify studies that describe factors and interventions at primary care practice level that impact on levels of utilisation of unscheduled secondary care.SettingObservational studies at primary care practice level.ParticipantsStudies included people of any age of either sex living in Organisation for Economic Co-operation and Development (OECD) countries with any health condition.Primary and secondary outcome measuresThe primary outcome measure was unscheduled secondary care as measured by emergency department attendance and emergency hospital admissions.Results48 papers were identified describing potential influencing features on emergency department visits (n=24 studies) and emergency admissions (n=22 studies). Patient factors associated with both outcomes were increased age, reduced socioeconomic status, lower educational attainment, chronic disease and multimorbidity. Features of primary care affecting unscheduled secondary care were more complex. Being able to see the same healthcare professional reduced unscheduled secondary care. Generally, better access was associated with reduced unscheduled care in the USA. Proximity to healthcare provision influenced patterns of use. Evidence relating to quality of care was limited and mixed.ConclusionsThe majority of research was from different healthcare systems and limited in the extent to which it can inform policy. However, there is evidence that continuity of care is associated with reduced emergency department attendance and emergency hospital admissions.

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Section: Resultsmentioning

confidence: 98%

“…However, Cowling 2013 found no effect of the prevalence of asthma, obesity and hypertension in English practice on ED visits 39. Age-standardised patient increased mortality rates are also associated with increased EHA 8 35…”

Section: Resultsmentioning

confidence: 99%

Which features of primary care affect unscheduled secondary care use? A systematic review

et al. 2014

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“…32 Provision of diabetes clinics in primary care was significantly associated with reduced admission rates for diabetes, but the provision of asthma clinics was not associated with a similar reduction in admissions. 33 Conversely, a systematic review showed that high standards of diabetes care in primary care did not necessarily lead to reduced hospital admissions. 34 General practitioners are incentivised through the NHS Outcomes Framework to improve quality of care and outcomes for patients, with a stronger emphasis on mental health.…”

Section: Fundingmentioning

confidence: 99%

Do higher primary care practice performance scores predict lower rates of emergency admissions for persons with serious mental illness? An analysis of secondary panel data

Jacobs

Gutacker

Mason

et al. 2015

Health Services and Delivery Research

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BackgroundSerious mental illness (SMI) is a set of chronic enduring conditions including schizophrenia and bipolar disorder. SMIs are associated with poor outcomes, high costs and high levels of disease burden. Primary care plays a central role in the care of people with a SMI in the English NHS. Good-quality primary care has the potential to reduce emergency hospital admissions, but also to increase elective admissions if physical health problems are identified by regular health screening of people with SMIs. Better-quality primary care may reduce length of stay (LOS) by enabling quicker discharge, and it may also reduce NHS expenditure.ObjectivesWe tested whether or not better-quality primary care, as assessed by the SMI quality indicators measured routinely in the Quality and Outcomes Framework (QOF) in English general practice, is associated with lower rates of emergency hospital admissions for people with SMIs, for both mental and physical conditions and with higher rates of elective admissions for physical conditions in people with a SMI. We also tested the impact of SMI QOF indicators on LOS and costs.DataWe linked administrative data from around 8500 general practitioner (GP) practices and from Hospital Episode Statistics for the study period 2006/7 to 2010/11. We identified SMI admissions by a mainInternational Classification of Diseases, 10th revision (ICD-10) diagnosis of F20–F31. We included information on GP practice and patient population characteristics, area deprivation and other potential confounders such as access to care. Analyses were carried out at a GP practice level for admissions, but at a patient level for LOS and cost analyses.MethodsWe ran mixed-effects count data and linear models taking account of the nested structure of the data. All models included year indicators for temporal trends.ResultsContrary to expectation, we found a positive association between QOF achievement and admissions, for emergency admissions for both mental and physical health. An additional 10% in QOF achievement was associated with an increase in the practice emergency SMI admission rate of approximately 1.9%. There was no significant association of QOF achievement with either LOS or cost. All results were robust to sensitivity analyses.ConclusionsPossible explanations for our findings are (1) higher quality of primary care, as measured by QOF may not effectively prevent the need for secondary care; (2) patients may receive their QOF checks post discharge, rather than prior to admission; (3) people with more severe SMIs, at a greater risk of admission, may select into practices that are better organised to provide their care and which have better QOF performance; (4) better-quality primary care may be picking up unmet need for secondary care; and (5) QOF measures may not accurately reflect quality of primary care. Patient-level data on quality of care in general practice is required to determine the reasons for the positive association of QOF quality and admissions. Future research should also aim to identify the non-QOF measures of primary care quality that may reduce unplanned admissions more effectively and could potentially be incentivised.FundingThe National Institute for Health Research Health Services and Delivery Research programme.

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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%

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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Association of population and practice factors with potentially avoidable admission rates for chronic diseases in London: cross sectional analysis

Cited by 77 publications

References 22 publications

Which features of primary care affect unscheduled secondary care use? A systematic review

Which features of primary care affect unscheduled secondary care use? A systematic review

Do higher primary care practice performance scores predict lower rates of emergency admissions for persons with serious mental illness? An analysis of secondary panel data

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

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