Sequential monitoring of hospital adverse events when control charts fail: the example of fall injuries in hospitals.
OBJECTIVE
To evaluate methods for monitoring monthly aggregated hospital adverse event data that display clustering, non-linear trends and possible autocorrelation.


METHODS
Retrospective audit.


METHODS
The Northern Hospital, Melbourne, Australia.


METHODS
171,059 patients admitted between January 2001 and December 2006.


METHODS
The analysis is illustrated with 72 months of patient fall injury data using a modified Shewhart U control chart, and charts derived from a quasi-Poisson generalised linear model (GLM) and a generalised additive mixed model (GAMM) that included an approximate upper control limit.


RESULTS
The data were overdispersed and displayed a downward trend and possible autocorrelation. The downward trend was followed by a predictable period after December 2003. The GLM-estimated incidence rate ratio was 0.98 (95% CI 0.98 to 0.99) per month. The GAMM-fitted count fell from 12.67 (95% CI 10.05 to 15.97) in January 2001 to 5.23 (95% CI 3.82 to 7.15) in December 2006 (p<0.001). The corresponding values for the GLM were 11.9 and 3.94. Residual plots suggested that the GLM underestimated the rate at the beginning and end of the series and overestimated it in the middle. The data suggested a more rapid rate fall before 2004 and a steady state thereafter, a pattern reflected in the GAMM chart. The approximate upper two-sigma equivalent control limit in the GLM and GAMM charts identified 2 months that showed possible special-cause variation.


CONCLUSIONS
Charts based on GAMM analysis are a suitable alternative to Shewhart U control charts with these data.
Barker
A
A
The Northern Clinical Research Centre, Melbourne, Victoria, Australia.
Morton
A
A
Gatton
M
M
Tong
E
E
Clements
A
A
D000058:Accidental Falls / Q000517:prevention & control / Q000706:statistics & numerical data*; D016001:Confidence Intervals; D005568:Forms and Records Control; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D016014:Linear Models; D008485:Medical Audit; D019300:Medical Errors / Q000517:prevention & control*; D010043:Outcome and Process Assessment, Health Care; D016012:Poisson Distribution; D012189:Retrospective Studies; D014739:Victoria