How do population, general practice and hospital factors influence ambulatory care sensitive admissions: a cross sectional study
Abstract Background Reducing unplanned hospital admissions is a key priority within the UK and other healthcare systems, however it remains uncertain how this can be achieved. This paper explores the relationship between unplanned ambulatory care sensitive condition (ACSC) admission rates and popula...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2017-05-01
|
Series: | BMC Family Practice |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s12875-017-0638-9 |
id |
doaj-b96ce4bfdeed4b278616030f41faa130 |
---|---|
record_format |
Article |
spelling |
doaj-b96ce4bfdeed4b278616030f41faa1302020-11-25T03:41:36ZengBMCBMC Family Practice1471-22962017-05-011811910.1186/s12875-017-0638-9How do population, general practice and hospital factors influence ambulatory care sensitive admissions: a cross sectional studyJohn Busby0Sarah Purdy1William Hollingworth2Centre for Public Health, Queen’s University BelfastSchool of Social and Community Medicine, University of BristolSchool of Social and Community Medicine, University of BristolAbstract Background Reducing unplanned hospital admissions is a key priority within the UK and other healthcare systems, however it remains uncertain how this can be achieved. This paper explores the relationship between unplanned ambulatory care sensitive condition (ACSC) admission rates and population, general practice and hospital characteristics. Additionally, we investigated if these factors had a differential impact across 28 conditions. Methods We used the English Hospital Episode Statistics to calculate the number of unplanned ACSC hospital admissions for 28 conditions at 8,029 general practices during 2011/12. We used multilevel negative binomial regression to estimate the influence of population (deprivation), general practice (size, access, continuity, quality, A&E proximity) and hospital (bed availability, % day cases) characteristics on unplanned admission rates after adjusting for age, sex and chronic disease prevalence. Results Practices in deprived areas (at the 90th centile) had 16% (95% confidence interval: 14 to 18) higher admission rates than those in affluent areas (10th centile). Practices with poorer care continuity (9%; 8 to 11), located closest to A&E (8%; 6 to 9), situated in areas with high inpatient bed availability (14%; 10 to 18) or in areas with a larger proportion of day case admissions (17%; 12 to 21) had more admissions. There were smaller associations for primary care access, clinical quality, and practice size. The strength of associations varied by ACSC. For example, deprivation was most strongly associated with alcohol related diseases and COPD admission rates, while continuity of primary care was most strongly associated with admission rates for chronic diseases such as hypertension and iron-deficiency anaemia. Conclusions The drivers of unplanned ACSC admission rates are complex and include population, practice and hospital factors. The importance of these varies markedly across conditions suggesting that multifaceted interventions are required to avoid hospital admissions and reduce costs. Several of the most important drivers of admissions are largely beyond the control of GPs. However, strategies to improve primary care continuity and avoid unnecessary short-stay admissions could lead to improved efficiency.http://link.springer.com/article/10.1186/s12875-017-0638-9Primary health careGeneral practiceAmbulatory carePatient admission |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
John Busby Sarah Purdy William Hollingworth |
spellingShingle |
John Busby Sarah Purdy William Hollingworth How do population, general practice and hospital factors influence ambulatory care sensitive admissions: a cross sectional study BMC Family Practice Primary health care General practice Ambulatory care Patient admission |
author_facet |
John Busby Sarah Purdy William Hollingworth |
author_sort |
John Busby |
title |
How do population, general practice and hospital factors influence ambulatory care sensitive admissions: a cross sectional study |
title_short |
How do population, general practice and hospital factors influence ambulatory care sensitive admissions: a cross sectional study |
title_full |
How do population, general practice and hospital factors influence ambulatory care sensitive admissions: a cross sectional study |
title_fullStr |
How do population, general practice and hospital factors influence ambulatory care sensitive admissions: a cross sectional study |
title_full_unstemmed |
How do population, general practice and hospital factors influence ambulatory care sensitive admissions: a cross sectional study |
title_sort |
how do population, general practice and hospital factors influence ambulatory care sensitive admissions: a cross sectional study |
publisher |
BMC |
series |
BMC Family Practice |
issn |
1471-2296 |
publishDate |
2017-05-01 |
description |
Abstract Background Reducing unplanned hospital admissions is a key priority within the UK and other healthcare systems, however it remains uncertain how this can be achieved. This paper explores the relationship between unplanned ambulatory care sensitive condition (ACSC) admission rates and population, general practice and hospital characteristics. Additionally, we investigated if these factors had a differential impact across 28 conditions. Methods We used the English Hospital Episode Statistics to calculate the number of unplanned ACSC hospital admissions for 28 conditions at 8,029 general practices during 2011/12. We used multilevel negative binomial regression to estimate the influence of population (deprivation), general practice (size, access, continuity, quality, A&E proximity) and hospital (bed availability, % day cases) characteristics on unplanned admission rates after adjusting for age, sex and chronic disease prevalence. Results Practices in deprived areas (at the 90th centile) had 16% (95% confidence interval: 14 to 18) higher admission rates than those in affluent areas (10th centile). Practices with poorer care continuity (9%; 8 to 11), located closest to A&E (8%; 6 to 9), situated in areas with high inpatient bed availability (14%; 10 to 18) or in areas with a larger proportion of day case admissions (17%; 12 to 21) had more admissions. There were smaller associations for primary care access, clinical quality, and practice size. The strength of associations varied by ACSC. For example, deprivation was most strongly associated with alcohol related diseases and COPD admission rates, while continuity of primary care was most strongly associated with admission rates for chronic diseases such as hypertension and iron-deficiency anaemia. Conclusions The drivers of unplanned ACSC admission rates are complex and include population, practice and hospital factors. The importance of these varies markedly across conditions suggesting that multifaceted interventions are required to avoid hospital admissions and reduce costs. Several of the most important drivers of admissions are largely beyond the control of GPs. However, strategies to improve primary care continuity and avoid unnecessary short-stay admissions could lead to improved efficiency. |
topic |
Primary health care General practice Ambulatory care Patient admission |
url |
http://link.springer.com/article/10.1186/s12875-017-0638-9 |
work_keys_str_mv |
AT johnbusby howdopopulationgeneralpracticeandhospitalfactorsinfluenceambulatorycaresensitiveadmissionsacrosssectionalstudy AT sarahpurdy howdopopulationgeneralpracticeandhospitalfactorsinfluenceambulatorycaresensitiveadmissionsacrosssectionalstudy AT williamhollingworth howdopopulationgeneralpracticeandhospitalfactorsinfluenceambulatorycaresensitiveadmissionsacrosssectionalstudy |
_version_ |
1724529327145484288 |