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A Pilot Study of a Computerized Decision Support System to Detect Invasive Fungal Infection in Pediatric Hematology/Oncology Patients

Published online by Cambridge University Press:  17 August 2015

Adam Bartlett*
Affiliation:
Department of Immunology and Infectious Diseases, Sydney Children’s Hospital, Randwick, NSW, Australia School of Women’s and Children’s Health, University of New South Wales, Sydney, NSW, Australia
Emma Goeman
Affiliation:
Department of Immunology and Infectious Diseases, Sydney Children’s Hospital, Randwick, NSW, Australia
Aditi Vedi
Affiliation:
School of Women’s and Children’s Health, University of New South Wales, Sydney, NSW, Australia Kids Cancer Centre, Sydney Children’s Hospital, Randwick, NSW, Australia
Mona Mostaghim
Affiliation:
University of Technology, Sydney, Australia
Toby Trahair
Affiliation:
Kids Cancer Centre, Sydney Children’s Hospital, Randwick, NSW, Australia University of New South Wales, Sydney, NSW, Australia
Tracey A. O’Brien
Affiliation:
Kids Cancer Centre, Sydney Children’s Hospital, Randwick, NSW, Australia University of New South Wales, Sydney, NSW, Australia
Pamela Palasanthiran
Affiliation:
Department of Immunology and Infectious Diseases, Sydney Children’s Hospital, Randwick, NSW, Australia School of Women’s and Children’s Health, University of New South Wales, Sydney, NSW, Australia
Brendan McMullan
Affiliation:
Department of Immunology and Infectious Diseases, Sydney Children’s Hospital, Randwick, NSW, Australia School of Women’s and Children’s Health, University of New South Wales, Sydney, NSW, Australia
*
Address correspondence to Adam Bartlett, Department of Immunology and Infectious Diseases, Sydney Children’s Hospital, High Street, Randwick, NSW, Australia, 2031 ([email protected]).

Abstract

OBJECTIVE

Computerized decision support systems (CDSSs) can provide indication-specific antimicrobial recommendations and approvals as part of hospital antimicrobial stewardship (AMS) programs. The aim of this study was to assess the performance of a CDSS for surveillance of invasive fungal infections (IFIs) in an inpatient hematology/oncology cohort.

METHODS

Between November 1, 2012, and October 31, 2013, pediatric hematology/oncology inpatients diagnosed with an IFI were identified through an audit of the CDSS and confirmed by medical record review. The results were compared to hospital diagnostic-related group (DRG) coding for IFI throughout the same period.

RESULTS

A total of 83 patients were prescribed systemic antifungals according to the CDSS for the 12-month period. The CDSS correctly identified 19 patients with IFI on medical record review, compared with 10 patients identified by DRG coding, of whom 9 were confirmed to have IFI on medical record review.

CONCLUSIONS

CDSS was superior to diagnostic coding in detecting IFI in an inpatient pediatric hematology/oncology cohort. The functionality of CDSS lends itself to inpatient infectious diseases surveillance but depends on prescriber adherence.

Infect. Control Hosp. Epidemiol. 2015;36(11):1313–1317

Type
Original Articles
Copyright
© 2015 by The Society for Healthcare Epidemiology of America. All rights reserved 

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References

REFERENCES

1. Ozsevik, SN, Sensoy, G, Karli, A, et al. Invasive fungal infections in children with hematologic and malignant diseases. J Pediatr Hematol Oncol 2014; epub ahead of print.Google Scholar
2. Ananda-Rajah, MR, Martinez, D, Slavin, MA, et al. Facilitating surveillance of pulmonary invasive mold diseases in patients with haematological malignancies by screening computed tomography reports using natural language processing. PLoS One 2014;9:e107797.CrossRefGoogle ScholarPubMed
3. De Pauw, B, Walsh, TJ, Donnelly, P, et al. Revised definitions of invasive fungal disease from the European Organization for Research and Treatment of Cancer/Invasive Fungal Infections Cooperative Group and the National Institute of Allergy and Infectious Diseases Mycoses Study Group (EORTC/MSG) Consensus Group. Clin Infect Dis 2008;46:18131821.CrossRefGoogle Scholar
4. Society for Healthcare Epidemiology of America (SHEA), Infectious Diseases Society of America (IDSA), Pediatric Infectious Diseases Society (PIDS). Policy statement on antimicrobial stewardship by the Society for Healthcare Epidemiology of America (SHEA), the Infectious Diseases Society of America (IDSA), and the Pediatric Infectious Diseases Society (PIDS). Infect Control Hosp Epidemiol 2012;33:322327.CrossRefGoogle Scholar
5. Buising, KL, Thursky, KA, Robertson, MB, et al. Electronic antibiotic stewardship-reduced consumption of broad-spectrum antibiotics using a computerized antimicrobial approval system in a hospital setting. J Antimicrob Chemother 2008;62:608616.CrossRefGoogle ScholarPubMed
6. Ruhnke, M. Antifungal stewardship in invasive Candida infections. Clin Microbiol Infect 2014;20(Suppl. 6):1118.CrossRefGoogle ScholarPubMed
7. Davey, P, Brown, E, Charani, E, et al. Interventions to improve antibiotic prescribing practices for hospital inpatients. Cochrane Database Syst Rev 2013;4:CD003543.Google Scholar
8. Mondain, V, Lieutier, F, Hasseine, L, et al. A 6-year antifungal stewardship programme in a teaching hospital. Infection 2013;41:621628.CrossRefGoogle ScholarPubMed
9. Ananda-Rajah, MR, Slavin, MA, Thursky, KT. The case for antifungal stewardship. Curr Opin Infect Dis 2012;25:107115.CrossRefGoogle ScholarPubMed
10. The International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Australian Modification (ICD-10-AM) – Tabular List of Diseases. National Casemix and Classification Centre, Australian Health Services Research Institute, University of Wollongong, July 2013.Google Scholar
11. Ananda-Rajah, MR, Cheng, A, Morrisey, CO, et al. Attributable hospital cost and antifungal treatment of invasive fungal diseases in high-risk hematology patients: an economic modelling approach. Antimicrob Agents Chemother 2011;55:19531960.CrossRefGoogle Scholar
12. Yong, MK, Buising, KL, Cheng, AC, Thursky, KA. Improved susceptibility of gram-negative bacteria in an intensive care unit following implementation of a computerized antibiotic decision support system. J Antimicrob Chemother 2010;65:10621069.CrossRefGoogle Scholar
13. Thursky, KA, Buising, KL, Bak, N, et al. Reduction of broad-spectrum antibiotic use with computerized decision support in an intensive care unit. Int J Qual Health Care 2006;18:224231.CrossRefGoogle Scholar
14. Shojania, KG, Yokoe, D, Platt, R, Fiskio, J, Ma’luf, N, Bates, DW. Reducing vancomycin use utilizing a computer guideline: results of a randomized controlled trial. J Am Med Inform Assoc 1998;5:554562.CrossRefGoogle ScholarPubMed
15. Evans, RS, Pestonik, SL, Classen, DC, et al. A computer-assisted management program for antibiotics and other antiinfective agents. N Engl J Med 1998;338:232238.CrossRefGoogle ScholarPubMed
16. Thomas, KE, Owens, CM, Veys, PA, Novelli, V, Costoli, V. The radiological spectrum of invasive aspergillosis in children: a 10-year review. Pediatr Radiol 2003;33:453460.Google Scholar
17. Oren, I, Paul, M. Up to date epidemiology, diagnosis and management of invasive fungal infections. Clin Microbiol Infect 2014;20(Suppl. 6):14.CrossRefGoogle ScholarPubMed
18. Alanio, A, Bretagne, S. Difficulties with molecular diagnostic tests for mould and yeast infections: where do we stand? Clin Microbiol Infect 2014;20(Suppl. 6):3641.CrossRefGoogle ScholarPubMed