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Title: Understanding the potential (and limitations) for avoiding secondary care through management of ambulatory care sensitive conditions
Author: Beales, Stephen
ISNI:       0000 0004 5367 5482
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2015
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Background and Aim: There is a subset of conditions - Ambulatory Care Sensitive Conditions (ACSCs) - for which emergency admission into secondary care is thought to be avoidable through better primary care. This research aims to: develop a model to predict ACSC-admission rates by GP practice; determine whether ACSC-admission rates are a viable performance metric; identify how much inefficiency exists among practices; and identify interventions that reduce ACSC admissions. Methods: The work uses routine administrative datasets (e.g. HES and Attribution Dataset), linked at the level of the general practice, for all practices in England providing NHS care. It uses techniques including multiple linear regression, corrected ordinary least squares, stochastic frontier analysis and propensity score matching to test its hypotheses. Results: Adjusting for population characteristics (e.g. deprivation and disease prevalence), some QOF indicators and GP patient survey results were associated with lower admissions rates. Aggregating admission rates across more practices improved the accuracy of predicted rates; at average CCG size (33 practices), the 95% confidence interval is ± 8.6%. If all GP practices in England became as efficient as those that were top performing, allowing for practices' population characteristics, there would be a 20.4% reduction in the number of ACSC admissions, based on 2010/11 data. Two interventions were found to lower admission rates. Patient advice and liaison service led to 5.9% fewer admissions for diabetes and 6.5% fewer admissions for hypertension. Information and support for diabetes led to 4.1% fewer admissions for diabetes. Conclusions: Improving the efficiency of practices to best-practice levels would mean 242,143 fewer admissions per year - a £411m annual saving - however a metric for judging practices' quality based on ACSC-admission rates would need a degree of leniency. Interventions can be found that reduce ACSC admissions and commissioners should consider expanding them. ACSC-impact assessments should be carried out before commissioning such interventions.
Supervisor: Darzi, Ara ; Smith, Pete Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available