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...

Full description

Bibliographic Details
Main Authors: John Busby, Sarah Purdy, William Hollingworth
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