'Online' monitoring and retrospective analysis of hospital outcomes based on a scan statistic.
Statistical tests based on the scan statistic are introduced for detecting possible increases in the occurrence of hospital events. The tests use a moving window and the theoretical aspects of the tests are investigated using Markov chain theory. The main objective of this study is to provide a statistical technique to assist hospital staff in deciding whether the variation they observe is greater than usually expected under random variation. In this paper we develop the test for Poisson data and apply the theory to monitor the occurrence of orthopaedic wound infection and Methicillin-resistant Staphylo- coccus aureus colonization. We find that this method is sensitive in detecting the change in the process parameter which may not be detected by standard control chart methods. Both online and retrospective analyses are considered.
Ismail
Noor Azina
NA
Centre in Statistical Science and Industrial Mathematics, School of Mathematical Sciences, Queensland University of Technology, Brisbane, Qld 4001, Australia. nazina@um.edu.my
Pettitt
A N
AN
Webster
R A
RA
D001315:Australia / Q000453:epidemiology; D003428:Cross Infection / Q000453:epidemiology; D006753:Hospital Records / Q000706:statistics & numerical data*; D006801:Humans; D008390:Markov Chains; D016106:Methicillin Resistance; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D016012:Poisson Distribution; D011159:Population Surveillance / Q000379:methods; D012189:Retrospective Studies; D013203:Staphylococcal Infections / Q000453:epidemiology; D013530:Surgical Wound Infection / Q000453:epidemiology