OBJECTIVES: Evaluate data available from a national voluntary reporting system and describe the data processing necessary to enable the development and application of outbreak detection methods in healthcare settings. METHODS: Evaluation was performed on an extract of data reported between March 2007 and May 2012. Reporting delays were calculated and analysed at the trust, regional and national levels. Negative binomial regression analysis was performed to detect any changes in laboratory reporting within this time. RESULTS: 167 hospital laboratories have reported to the voluntary reporting system. 1,705,126 reports were made in the five-year study period. There is large variation in how laboratories report to the system. Under half (44.9%) report in a timely manner, with >90% of infections reported within three weeks of the specimen date. Overall, there was a significant increase of 17.5% in reporting after October 2010 (95% CI 13.8-21.4%, p < 0.001) and an improvement in reporting delay, when new statutory reporting regulations were introduced. CONCLUSIONS: The outbreak detection algorithm used at the national and regional level requires further modification to optimise outbreak detection for individual hospitals. For any prospective outbreak detection system to perform optimally it is imperative that laboratories ensure that the data they submit is complete, consistent and timely.
OBJECTIVES: Evaluate data available from a national voluntary reporting system and describe the data processing necessary to enable the development and application of outbreak detection methods in healthcare settings. METHODS: Evaluation was performed on an extract of data reported between March 2007 and May 2012. Reporting delays were calculated and analysed at the trust, regional and national levels. Negative binomial regression analysis was performed to detect any changes in laboratory reporting within this time. RESULTS: 167 hospital laboratories have reported to the voluntary reporting system. 1,705,126 reports were made in the five-year study period. There is large variation in how laboratories report to the system. Under half (44.9%) report in a timely manner, with >90% of infections reported within three weeks of the specimen date. Overall, there was a significant increase of 17.5% in reporting after October 2010 (95% CI 13.8-21.4%, p < 0.001) and an improvement in reporting delay, when new statutory reporting regulations were introduced. CONCLUSIONS: The outbreak detection algorithm used at the national and regional level requires further modification to optimise outbreak detection for individual hospitals. For any prospective outbreak detection system to perform optimally it is imperative that laboratories ensure that the data they submit is complete, consistent and timely.
Authors: M Gharbi; L S P Moore; M Gilchrist; C P Thomas; K Bamford; E T Brannigan; A H Holmes Journal: Int J Antimicrob Agents Date: 2015-04-23 Impact factor: 5.283
Authors: Kai Cao; Kun Yang; Chao Wang; Jin Guo; Lixin Tao; Qingrong Liu; Mahara Gehendra; Yingjie Zhang; Xiuhua Guo Journal: Int J Environ Res Public Health Date: 2016-05-05 Impact factor: 3.390
Authors: Mark P C Cherrie; Gordon Nichols; Gianni Lo Iacono; Christophe Sarran; Shakoor Hajat; Lora E Fleming Journal: BMC Public Health Date: 2018-08-28 Impact factor: 3.295