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Surveillance Open Access
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Abstract

Background

Timely reporting of microbiology test results is essential for infection management. Automated, machine-to-machine (M2M) reporting of diagnostic and antimicrobial resistance (AMR) data from laboratory information management systems (LIMS) to public health agencies improves timeliness and completeness of communicable disease surveillance.

Aim

We surveyed microbiology data reporting practices for national surveillance of EU-notifiable diseases in European Union/European Economic Area (EU/EEA) countries in 2018.

Methods

European Centre for Disease Prevention and Control (ECDC) National Microbiology and Surveillance Focal Points completed a questionnaire on the modalities and scope of clinical microbiology laboratory data reporting.

Results

Complete data were provided for all 30 EU/EEA countries. Clinical laboratories used a LIMS in 28 countries. LIMS data on EU-notifiable diseases and AMR were M2M-reported to the national level in 14 and nine countries, respectively. In the 14 countries, associated demographic data reported allowed the de-duplication of patient reports. In 13 countries, M2M-reported data were used for cluster detection at the national level. M2M laboratory data reporting had been validated against conventional surveillance methods in six countries, and replaced those in five. Barriers to M2M reporting included lack of information technology support and financial incentives.

Conclusion

M2M-reported laboratory data were used for national public health surveillance and alert purposes in nearly half of the EU/EEA countries in 2018. Reported data on infectious diseases and AMR varied in extent and disease coverage across countries and laboratories. Improving automated laboratory-based surveillance will depend on financial and regulatory incentives, and harmonisation of health information and communication systems.

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2020-10-01
2020-10-27
http://instance.metastore.ingenta.com/content/10.2807/1560-7917.ES.2020.25.39.1900591
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References

  1. Enki DG, Noufaily A, Garthwaite PH, Andrews NJ, Charlett A, Lane C, et al. Automated biosurveillance data from England and Wales, 1991-2011. Emerg Infect Dis. 2013;19(1):35-42.  https://doi.org/10.3201/eid1901.120493  PMID: 23260848 
  2. Colson P, Rolain JM, Abat C, Charrel R, Fournier PE, Raoult D. EPIMIC: A Simple Homemade Computer Program for Real-Time EPIdemiological Surveillance and Alert Based on MICrobiological Data. PLoS One. 2015;10(12):e0144178.  https://doi.org/10.1371/journal.pone.0144178  PMID: 26658293 
  3. Dessau RB, Espenhain L, Mølbak K, Krause TG, Voldstedlund M. Improving national surveillance of Lyme neuroborreliosis in Denmark through electronic reporting of specific antibody index testing from 2010 to 2012. Euro Surveill. 2015;20(28):21184.  https://doi.org/10.2807/1560-7917.ES2015.20.28.21184  PMID: 26212143 
  4. Condell O, Gubbels S, Nielsen J, Espenhain L, Frimodt-Møller N, Engberg J, et al. Corrigendum to ‘Automated surveillance system for hospital-acquired urinary tract infections in Denmark’ [Journal of Hospital Infection 93 (2016) 290-296]. J Hosp Infect. 2016;94(4):410.  https://doi.org/10.1016/j.jhin.2016.09.001  PMID: 27665312 
  5. Ridgway JP, Sun X, Tabak YP, Johannes RS, Robicsek A. Performance characteristics and associated outcomes for an automated surveillance tool for bloodstream infection. Am J Infect Control. 2016;44(5):567-71.  https://doi.org/10.1016/j.ajic.2015.12.044  PMID: 26899530 
  6. Huart M, Bedubourg G, Abat C, Colson P, Rolain JM, Chaudet H, et al. Implementation and Initial Analysis of a Laboratory-Based Weekly Biosurveillance System, Provence-Alpes-Côte d’Azur, France. Emerg Infect Dis. 2017;23(4):582-9.  https://doi.org/10.3201/eid2304.161399  PMID: 28322712 
  7. O’Brien TF, Clark A, Peters R, Stelling J. Why surveillance of antimicrobial resistance needs to be automated and comprehensive. J Glob Antimicrob Resist. 2019;17:8-15.  https://doi.org/10.1016/j.jgar.2018.10.011  PMID: 30326273 
  8. Stachel A, Pinto G, Stelling J, Fulmer Y, Shopsin B, Inglima K, et al. Implementation and evaluation of an automated surveillance system to detect hospital outbreak. Am J Infect Control. 2017;45(12):1372-7.  https://doi.org/10.1016/j.ajic.2017.06.031  PMID: 28844384 
  9. Effler P, Ching-Lee M, Bogard A, Ieong MC, Nekomoto T, Jernigan D. Statewide system of electronic notifiable disease reporting from clinical laboratories: comparing automated reporting with conventional methods. JAMA. 1999;282(19):1845-50.  https://doi.org/10.1001/jama.282.19.1845  PMID: 10573276 
  10. Samoff E, Fangman MT, Fleischauer AT, Waller AE, Macdonald PD. Improvements in timeliness resulting from implementation of electronic laboratory reporting and an electronic disease surveillance system. Public Health Rep. 2013;128(5):393-8.  https://doi.org/10.1177/003335491312800510  PMID: 23997286 
  11. Gubbels S, Nielsen J, Voldstedlund M, Kristensen B, Schønheyder HC, Ellermann-Eriksen S, et al. National Automated Surveillance of Hospital-Acquired Bacteremia in Denmark Using a Computer Algorithm. Infect Control Hosp Epidemiol. 2017;38(5):559-66.  https://doi.org/10.1017/ice.2017.1  PMID: 28274300 
  12. Chaine M, Gubbels S, Voldstedlund M, Kristensen B, Nielsen J, Andersen LP, et al. Description and validation of a new automated surveillance system for Clostridium difficile in Denmark. Epidemiol Infect. 2017;145(12):2594-602.  https://doi.org/10.1017/S0950268817001315  PMID: 28689506 
  13. Abat C, Chaudet H, Colson P, Rolain JM, Raoult D. Real-Time Microbiology Laboratory Surveillance System to Detect Abnormal Events and Emerging Infections, Marseille, France. Emerg Infect Dis. 2015;21(8):1302-10.  https://doi.org/10.3201/eid2108.141419  PMID: 26196165 
  14. European Centre for Disease Prevention and Control (ECDC). EU Laboratory Capability Monitoring System (EULabCap) - Report on 2016 survey of EU/EEA country capabilities and capacities. Stockholm: ECDC; 2018. Available from: https://ecdc.europa.eu/sites/portal/files/documents/2016_EULabCap_EUreport_web_300418_final.pdf
  15. European Centre for Disease Prevention and Control (ECDC). ECDC public health microbiology strategy 2018–2022. Stockholm: ECDC; 2017. Available from: https://ecdc.europa.eu/sites/portal/files/documents/ECDC-public-health-microbiology-strategy-2018-2022.pdf
  16. European Centre for Disease Prevention and Control (ECDC). Coordinating Competent Bodies: structures, interactions and terms of reference. Stockholm: ECDC; 7 Dec 2012 Available from: https://www.ecdc.europa.eu/sites/portal/files/media/en/aboutus/governance/competent-bodies/Documents/coordinating-competent-bodies-structures-terms-of-reference-and-interactions-w-Annexes.pdf
  17. European Commission (EC). Commission Implementing Decision (EU) 2018/945 of 22 June 2018 on the communicable diseases and related special health issues to be covered by epidemiological surveillance as well as relevant case definitions. Brussels: Official Journal of the European Union. 6.72018:L 170. Available from: https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32018D0945&from=EN
  18. Directorate-General for Health ad Food Safety, European Commission (EC). The new EU one health action plan against antimicrobial resistance. Luxembourg: Publications Office of the European Union;19 Oct 2018. Available from: https://op.europa.eu/en/publication-detail/-/publication/d6e681ca-d66d-11e8-9424-01aa75ed71a1
  19. European Centre for Disease Prevention and Control (ECDC), European Food Safety Authority (EFSA) Panel on Biological Hazards (BIOHAZ), European Medicines Agency (EMA) Committee for Medicinal Products for Veterinary Use (CVMP). ECDC, EFSA and EMA Joint Scientific Opinion on a list of outcome indicators as regards surveillance of antimicrobial resistance and antimicrobial consumption in humans and food-producing animals. EFSA J. 2017;15(10):e05017. PMID: 32625307 
  20. Technopedia. Laboratory Information Management System (LIMS). [Accessed 20 Sep 2020]. Available from: https://www.techopedia.com/definition/8085/laboratory-information-management-system-lims
  21. IoT agenda. Definition: machine-to-machine (M2M). [Accessed 20 Sep 2020]. Available from: https://internetofthingsagenda.techtarget.com/definition/machine-to-machine-M2M
  22. Wurtz R, Cameron BJ. Electronic laboratory reporting for the infectious diseases physician and clinical microbiologist. Clin Infect Dis. 2005;40(11):1638-43.  https://doi.org/10.1086/429904  PMID: 15889362 
  23. European Committee on Antimicrobial Susceptibility Testing (EUCAST). EUCAST Breakpoint tables v 8.0. Basel: European Society of Clinical Microbiology and Infectious Diseases (ECMID). 1 Jan 2018. Available from: http://www.eucast.org/eucast_news/news_singleview/?tx_ttnews%5Btt_news%5D=248&cHash=91e3ef09a79b333746462d8854ee016d
  24. Kahlmeter G. Clinical microbiology and infectious diseases working together. An ESCMID perspective. Presentation at Ulusal Klinik Mikrobiyoloji Kongresi; 2011; Antalya, Turkey. Available from: https://www.klimud.org/public/uploads/dosya/1352555609.pdf
  25. European Centre for Disease Prevention and Control (ECDC). Surveillance systems overview for 2016. Stockholm: ECDC; 4 May 2018. Available from: https://www.ecdc.europa.eu/en/publications-data/surveillance-systems-overview-2016
  26. Lamb E, Satre J, Hurd-Kundeti G, Liscek B, Hall CJ, Pinner RW, et al. Update on progress in electronic reporting of laboratory results to public health agencies - United States, 2014. MMWR Morb Mortal Wkly Rep. 2015;64(12):328-30. PMID: 25837244 
  27. Centers for Disease Control and Prevention (CDC). Surveillance Strategy Report – Pulse Check. Atlanta: CDC. [Accessed 20 Sep 2019]. Available from: https://www.cdc.gov/surveillance/initiatives/pulseCheck-our-progress.html
  28. Jernigan DB. Electronic laboratory-based reporting: opportunities and challenges for surveillance. Emerg Infect Dis. 2001;7(3) Suppl;538.  https://doi.org/10.3201/eid0707.017717  PMID: 11485655 
  29. Gluskin RT, Mavinkurve M, Varma JK. Government leadership in addressing public health priorities: strides and delays in electronic laboratory reporting in the United States. Am J Public Health. 2014;104(3):e16-21.  https://doi.org/10.2105/AJPH.2013.301753  PMID: 24432922 
  30. Voldstedlund M, Haarh M, Mølbak K, MiBa Board of Representatives. The Danish Microbiology Database (MiBa) 2010 to 2013. Euro Surveill. 2014;19(1):20667.  https://doi.org/10.2807/1560-7917.ES2014.19.1.20667  PMID: 24434175 
  31. European Commission (EC). Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation). 4.5.2016:L 119. Available from: https://eur-lex.europa.eu/eli/reg/2016/679/oj
  32. Bragstad K, Emborg H, Fischer TK, Voldstedlund M, Gubbels S, Andersen B, et al. Low vaccine effectiveness against influenza A(H3N2) virus among elderly people in Denmark in 2012/13--a rapid epidemiological and virological assessment. Euro Surveill. 2013;18(6):20397. PMID: 23410258 
  33. Moore KM, Reddy V, Kapell D, Balter S. Impact of electronic laboratory reporting on hepatitis A surveillance in New York City. J Public Health Manag Pract. 2008;14(5):437-41.  https://doi.org/10.1097/01.PHH.0000333877.78443.f0  PMID: 18708886 
  34. European Centre for Disease Prevention and Control (ECDC). ECDC strategic framework for the integration of molecular and genomic typing into European surveillance and multi-country outbreak investigations. Stockholm: ECDC; 4 Apr 2019. Available from: https://ecdc.europa.eu/en/publications-data/ecdc-strategic-framework-integration-molecular-and-genomic-typing-european
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