Investigating the association of alerts from a national mortality surveillance system with subsequent hospital mortality in England: an interrupted time series analysis
File(s)bmjqs-2017-007495.full.pdf (865.98 KB)
Published version
Author(s)
Type
Journal Article
Abstract
OBJECTIVE: To investigate the association between alerts from a national hospital mortality surveillance system and subsequent trends in relative risk of mortality. BACKGROUND: There is increasing interest in performance monitoring in the NHS. Since 2007, Imperial College London has generated monthly mortality alerts, based on statistical process control charts and using routinely collected hospital administrative data, for all English acute NHS hospital trusts. The impact of this system has not yet been studied. METHODS: We investigated alerts sent to Acute National Health Service hospital trusts in England in 2011-2013. We examined risk-adjusted mortality (relative risk) for all monitored diagnosis and procedure groups at a hospital trust level for 12 months prior to an alert and 23 months post alert. We used an interrupted time series design with a 9-month lag to estimate a trend prior to a mortality alert and the change in trend after, using generalised estimating equations. RESULTS: On average there was a 5% monthly increase in relative risk of mortality during the 12 months prior to an alert (95% CI 4% to 5%). Mortality risk fell, on average by 61% (95% CI 56% to 65%), during the 9-month period immediately following an alert, then levelled to a slow decline, reaching on average the level of expected mortality within 18 months of the alert. CONCLUSIONS: Our results suggest an association between an alert notification and a reduction in the risk of mortality, although with less lag time than expected. It is difficult to determine any causal association. A proportion of alerts may be triggered by random variation alone and subsequent falls could simply reflect regression to the mean. Findings could also indicate that some hospitals are monitoring their own mortality statistics or other performance information, taking action prior to alert notification.
Date Issued
2018-05-04
Date Acceptance
2018-04-07
Citation
BMJ Quality and Safety, 2018, 27 (12), pp.965-973
ISSN
2044-5415
Publisher
BMJ Publishing Group
Start Page
965
End Page
973
Journal / Book Title
BMJ Quality and Safety
Volume
27
Issue
12
Copyright Statement
© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/
Sponsor
National Institute for Health Research
National Institute for Health Research
Dr Foster Intelligence
National Institute for Health Research
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/29728447
PII: bmjqs-2017-007495
Grant Number
12/178/22
12/178/22
N/A
n/a
Subjects
health services research
healthcare quality improvement
statistical process control
Publication Status
Published
Coverage Spatial
England
Date Publish Online
2018-05-04