Trends and geographic variation of potentially avoidable hospitalizations in the veterans health-care system

Finegan, Michael S; Gao, Jian; Pasquale, Donald; Campbell, James

doi:10.1258/hsmr.2009.009023

Cited by 28 publications

(45 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…An indicator widely used as a measure of primary care quality and effectiveness is represented by admission rates of hospitalization for ambulatory care sensitive conditions (ACSC) (Finegan et al 2010;Schiøtz et al, 2011;Pelone et al 2012). The conditions chosen are those for which timely and effective primary care could be expected to reduce the risk of admission to hospital by preventing the onset of illness, controlling an acute episode of illness or better long term management (Giuffrida et al, 1999).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Particularly, in making an efficiency assessment of primary health care units these variables are mainly represented by the characteristics of the population demanding care. Many previous studies recommend adjusting for case-mix when making comparisons between healthcare organizations on the basis of ACSC hospitalization rates (Finegan et al, 2010), which are also found to be influenced by other clinical and socioeconomic factors such as age, health status and co-morbidities, deprivation or income level (Caminal et al, 2004;Rosano et al, 2012;Gibson et al, 2013).…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Efficiency assessment of primary care providers: A conditional nonparametric approach

Ferrera

Alonso-Morán

Nuño-Solinís

et al. 2015

European Journal of Operational Research

View full text Add to dashboard Cite

This paper uses a fully nonparametric approach to estimate efficiency measures for primary care units incorporating the effect of environmental factors. This methodology allows us to account for different types of variables (continuous and discrete) regarding the main characteristics of patients served by those providers. In addition, we use an extension of this nonparametric approach to deal with the presence of undesirable outputs in data, represented by the number of readmissions and hospitalization rates of ambulatory care sensitive condition (ASCS). The empirical results of our application show that all the exogenous variables considered have a significant and negative effect on efficiency estimates.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Efficiency assessment of primary care providers: A conditional nonparametric approach

Ferrera

Alonso-Morán

Nuño-Solinís

et al. 2015

European Journal of Operational Research

View full text Add to dashboard Cite

show abstract

“…24,25 Factors explaining variation were related to the population, particularly in terms of deprivation and health ( Table 1). 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.…”

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%

See 1 more Smart Citation

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

View full text Add to dashboard Cite

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.

show abstract

Geographic Variation in Obesity, Behavioral Treatment, and Bariatric Surgery for Veterans

Maciejewski

Arterburn

Berkowitz

et al. 2018

Obesity

View full text Add to dashboard Cite

Objective This study aims to describe geographic variation in veterans’ prevalence of obesity, participation in Veterans Health Administration’s behavioral weight management program (MOVE!), and receipt of bariatric surgery in fiscal year (FY) 2016. Methods In this retrospective cohort study of veterans with obesity who received Veterans Health Administration care in FY2016, electronic health record data were obtained on weight, height, outpatient visits to the MOVE! program, and bariatric surgeries. For each Veterans Integrated Service Network (VISN) region, the prevalence rate of veterans with obesity (BMI ≥ 30 kg/m2), MOVE! participation rates, and bariatric surgery rates are presented. Results The prevalence of obesity in veterans ranged from 30.5% to 40.5% across VISNs in FY2016. MOVE! participation among veterans with obesity was low (2.8%‐6.9%) across all VISNs, but veterans with class II and III obesity (BMI ≥ 35) had higher MOVE! participation rates (4.3%‐10.8%) than veterans with class I obesity. There was 20‐fold variation across VISNs in receipt of bariatric surgery among veterans with BMI ≥ 35, ranging from 0.01% to 0.2%. Among veterans with BMI ≥ 35 participating in MOVE!, there was 46‐fold variation in bariatric surgery provision, ranging from 0.07% to 3.27%. Conclusions Despite veterans’ high prevalence of obesity, behavioral and surgical weight management participation is low and varies across regions.

show abstract

Trends and geographic variation of potentially avoidable hospitalizations in the veterans health-care system

Cited by 28 publications

References 34 publications

Efficiency assessment of primary care providers: A conditional nonparametric approach

Efficiency assessment of primary care providers: A conditional nonparametric approach

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

Geographic Variation in Obesity, Behavioral Treatment, and Bariatric Surgery for Veterans

Contact Info

Product

Resources

About