Library Header Image
LSE Research Online LSE Library Services

Using a vector autoregression framework to measure the quality of English NHS hospitals

Papanicolas, Irene ORCID: 0000-0002-8000-3185 and McGuire, Alistair (2011) Using a vector autoregression framework to measure the quality of English NHS hospitals. LSE Health working papers (22). LSE Health, London School of Economics and Political Science, London, UK. ISBN 9780853284642

Download (5MB) | Preview


In order to address the problem of poor quality information available to health care providers today, McClellan and Staiger (1999) developed a new method to measure quality, which addresses some key limitations of other approaches. Their method produces quality estimates that reflect different dimensions of quality and are able to eliminate systematic bias and noise inherent in these types of measures. While these measures are promising indicators, they have not been applied to other conditions or health systems since their publication. This paper attempts to replicated their 1999 method by calculating these quality measures for English Hospitals using Hospital Episode Statistics for the years 1996-2008 for Acute Myocardial Infarction (AMI) and Hip Replacement. Using the latent outcome measures calculated previously, Vector Autoregressions (VARs) are used to combine the information from different time periods and across measures within each condition. These measures are then used to compare current and past quality of care within and across NHS Acute Trusts. Our results support that this method is well suited to measure and predict provider quality of care in the English setting using the individual patient level data collected.

Item Type: Monograph (Working Paper)
Official URL:
Additional Information: © 2011 The Authors
Divisions: Social Policy
LSE Health
Subjects: R Medicine > RA Public aspects of medicine
Date Deposited: 13 Jun 2011 13:39
Last Modified: 16 May 2024 11:55

Actions (login required)

View Item View Item


Downloads per month over past year

View more statistics