A Trial of Automated Outbreak Detection to Reduce Hospital Pathogen Spread.

View Abstract

BACKGROUND

Detection and containment of hospital outbreaks currently depend on variable and personnel-intensive surveillance methods. Whether automated statistical surveillance for outbreaks of health care-associated pathogens allows earlier containment efforts that would reduce the size of outbreaks is unknown.

METHODS

We conducted a cluster-randomized trial in 82 community hospitals within a larger health care system. All hospitals followed an outbreak response protocol when outbreaks were detected by their infection prevention programs. Half of the hospitals additionally used statistical surveillance of microbiology data, which alerted infection prevention programs to outbreaks. Statistical surveillance was also applied to microbiology data from control hospitals without alerting their infection prevention programs. The primary outcome was the number of additional cases occurring after outbreak detection. Analyses assessed differences between the intervention period (July 2019 to January 2022) versus baseline period (February 2017 to January 2019) between randomized groups. A post hoc analysis separately assessed pre-coronavirus disease 2019 (Covid-19) and Covid-19 pandemic intervention periods.

RESULTS

Real-time alerts did not significantly reduce the number of additional outbreak cases (intervention period versus baseline: statistical surveillance relative rate [RR]=1.41, control RR=1.81; difference-in-differences, 0.78; 95% confidence interval [CI], 0.40 to 1.52; P=0.46). Comparing only the prepandemic intervention with baseline periods, the statistical outbreak surveillance group was associated with a 64.1% reduction in additional cases (statistical surveillance RR=0.78, control RR=2.19; difference-in-differences, 0.36; 95% CI, 0.13 to 0.99). There was no similarly observed association between the pandemic versus baseline periods (statistical surveillance RR=1.56, control RR=1.66; difference-in-differences, 0.94; 95% CI, 0.46 to 1.92).

CONCLUSIONS

Automated detection of hospital outbreaks using statistical surveillance did not reduce overall outbreak size in the context of an ongoing pandemic. (Funded by the Centers for Disease Control and Prevention; ClinicalTrials.gov number, NCT04053075. Support for HCA Healthcare's participation in the study was provided in kind by HCA.).

Investigators
Abbreviation
NEJM Evid
Publication Date
2024-04-23
Volume
3
Issue
5
Page Numbers
EVIDoa2300342
Pubmed ID
38815164
Medium
Print-Electronic
Full Title
A Trial of Automated Outbreak Detection to Reduce Hospital Pathogen Spread.
Authors
Baker MA, Septimus E, Kleinman K, Moody J, Sands KE, Varma N, Isaacs A, McLean LE, Coady MH, Blanchard EJ, Poland RE, Yokoe DS, Stelling J, Haffenreffer K, Clark A, Avery TR, Sljivo S, Weinstein RA, Smith KN, Carver B, Meador B, Lin MY, Lewis SS, Washington C, Bhattarai M, Shimelman L, Kulldorff M, Reddy SC, Jernigan JA, Perlin JB, Platt R, Huang SS