scholarly journals Using geographic variation in unplanned ambulatory care sensitive condition admission rates to identify commissioning priorities: an analysis of routine data from England

2016 ◽  
Vol 22 (1) ◽  
pp. 20-27 ◽  
Author(s):  
John Busby ◽  
Sarah Purdy ◽  
William Hollingworth

Objectives To use geographic variation in unplanned ambulatory care sensitive condition admission rates to identify the clinical areas and patient subgroups where there is greatest potential to prevent admissions and improve the quality and efficiency of care. Methods We used English Hospital Episode Statistics data from 2011/2012 to describe the characteristics of patients admitted for ambulatory care sensitive condition care and estimated geographic variation in unplanned admission rates. We contrasted geographic variation across admissions with different lengths of stay which we used as a proxy for clinical severity. We estimated the number of bed days that could be saved under several scenarios. Results There were 1.8 million ambulatory care sensitive condition admissions during 2011/2012. Substantial geographic variation in ambulatory care sensitive condition admission rates was commonplace but mental health care and short-stay (<2 days) admissions were particularly variable. Reducing rates in the highest use areas could lead to savings of between 0.4 and 2.8 million bed days annually. Conclusions Widespread geographic variations in admission rates for conditions where admission is potentially avoidable should concern commissioners and could be symptomatic of inefficient care. Further work to explore the causes of these differences is required and should focus on mental health and short-stay admissions.

BMJ Open ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. e028744 ◽  
Author(s):  
Geraldine McDarby ◽  
Breda Smyth

BackgroundIn 2016, the Irish acute hospital system operated well above internationally recommended occupancy targets. Investment in primary care can prevent hospital admissions of ambulatory care sensitive conditions (ACSCs).ObjectiveTo measure the impact of ACSCs on acute hospital capacity in the Irish public system and identify specific care areas for enhanced primary care provision.DesignNational Hospital In-patient Enquiry System data were used to calculate 2011–2016 standardised bed day rates for selected ACSC conditions. A prioritisation exercise was undertaken to identify the most significant contributors to bed days within our hospital system. Poisson regression was used to determine change over time using incidence rate ratios (IRR).ResultsIn 2016 ACSCs accounted for almost 20% of acute public hospital beds (n=871 328 bed days) with adults over 65 representing 69.1% (n=602 392) of these. Vaccine preventable conditions represented 39.1% of ACSCs. Influenza and pneumonia were responsible for 99.8% of these, increasing by 8.2% (IRR: 1.02; 95% CI 1.02 to 1.03) from 2011 to 2016. Pyelonephritis represented 47.6% of acute ACSC bed days, increasing by 46.5% (IRR: 1.07; 95% CI 1.06 to 1.08) over the 5 years examined.ConclusionsPrioritisation for targeted investment in integrated care programmes is enabled through analysis of ACSC’s in terms of acute hospital bed days. This analysis demonstrates that primary care investment in integrated care programmes for respiratory ACSC’s from prevention to rehabilitation at scale could assist with bed capacity in acute hospitals in Ireland. In adults 65 years and over, including chronic obstructive pulmonary disease patients, the current analysis supports targeting community based pulmonary rehabilitation including pneumococcal and influenza vaccination programmes in order to reduce the burden of infection and hospitalisations. Further exploration of pyelonephritis is necessary in order to ascertain patient profile and appropriateness of admissions.


Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 1074-P
Author(s):  
TEG S. UPPAL ◽  
GAIL FERNANDES ◽  
JEEHEA SONYA HAW ◽  
MEGHA K. SHAH ◽  
SARA TURBOW ◽  
...  

Medical Care ◽  
2020 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Markku Satokangas ◽  
Martti Arffman ◽  
Harri Antikainen ◽  
Alastair H. Leyland ◽  
Ilmo Keskimäki

2013 ◽  
Vol 29 (11) ◽  
pp. 1462-1469 ◽  
Author(s):  
Robin L. Walker ◽  
Guanmin Chen ◽  
Finlay A. McAlister ◽  
Norm R.C. Campbell ◽  
Brenda R. Hemmelgarn ◽  
...  

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
M Satokangas ◽  
M Arffman ◽  
A Leyland ◽  
I Keskimäki

Abstract Background Geographic variation is common in ambulatory care sensitive conditions (ACSCs) - used as a proxy indicator for primary care quality. Its use is debated as it is more strongly associated with individual socioeconomic position (SEP) and health status than factors related to primary care. While most earlier studies have been cross-sectional, this study aims to observe if these associations change over time. Finland offers a good possibility for this due to its extensive registers and unexplained over time convergence of geographic variation in ACSC. Methods This observational study obtained ACSCs in 2011-2017 from the Finnish Hospital Discharge Register and divided them into subgroups of acute, chronic and vaccine-preventable causes. In these subgroups we analysed geographic variations with a three-level multilevel logistic regression model - individuals, health centre areas (HC) and hospital districts (HD) - and estimated the proportion of the variance at each level explained by individual SEP and comorbidities, as well as both primary care and hospital supply and spatial access at three time points. Results In the preliminary results of the baseline geographic variation in total ACSCs in 2011-2013 - the model with age and sex - the variance between HDs was nearly twice that between HCs. Individual SEP and comorbidities explained 46% of the variance between HDs and 29% between HCs; and area-level proportion of ACSC periods in primary care inpatient wards a further 12% and 5%. This evened out the unexplained variance between HDs and HCs. Conclusions Geographic variation in ACSCs was more pronounced in hospital districts than in the smaller health centre areas. The excess variance between HDs was explained by individual SEP and health status as well as by use of primary care inpatient wards. Our findings suggest that not only hospital bed supply, but also the national structure of hospital services affects ACSCs. This challenges international ACSC comparisons. Key messages Geographic variation in ACSCs concentrated in larger areas with differing population characteristics. The national structure of hospital services, such as use of primary care inpatient wards, affects ACSCs.


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