Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-09T03:53:45.719Z Has data issue: false hasContentIssue false
  • English
  • Français

Using data linkage methodologies to augment healthcare-associated infection surveillance data

Published online by Cambridge University Press:  29 July 2019

Seungwon Lee ,
Paul Ronksley ,
John Conly ,
Stephanie Garies ,
Hude Quan ,
Peter Faris ,
Bing Li  and
Elizabeth Henderson
Seungwon Lee
Affiliation:
Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
Paul Ronksley
Affiliation:
Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada O’Brien Institute of Public Health, University of Calgary, Calgary, Alberta, Canada
John Conly
Affiliation:
Department of Medicine, University of Calgary, Calgary, Alberta, Canada Alberta Health Services Infection Prevention and Control, Calgary, Alberta, Canada O’Brien Institute of Public Health, University of Calgary, Calgary, Alberta, Canada The Calvin, Phoebe and Joan Snyder Institute for Chronic Diseases, University of Calgary, Calgary, Alberta, Canada
Stephanie Garies
Affiliation:
Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada Department of Family Medicine, University of Calgary, Calgary, Alberta, Canada
Hude Quan
Affiliation:
Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada O’Brien Institute of Public Health, University of Calgary, Calgary, Alberta, Canada
Peter Faris
Affiliation:
Alberta Health Services Research Facilitation Analytics (DIMR), Calgary, Alberta, Canada
Bing Li
Affiliation:
Alberta Health Services Research Facilitation Analytics (DIMR), Calgary, Alberta, Canada
Elizabeth Henderson*
Affiliation:
Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
*
Author for correspondence: Dr Elizabeth Henderson, Email: ehenders@ucalgary.ca.
Get access Rights & Permissions [Opens in a new window]

Abstract

Background and objectives:

The landscape of antimicrobial resistance (AMR) surveillance is changing rapidly. The primary objective of this study was to assess the benefit of linking population-based infection prevention and control surveillance data on methicillin-resistant Staphylococcus aureus (MRSA) to hospital discharge abstract data (DAD). We assessed the value of this novel data linkage for the characterization of hospital-acquired (HA) and community-acquired MRSA (CA-MRSA) cases.

Methods:

Incident inpatient MRSA surveillance data for all adults (≥18 years) from 4 acute-care facilities in Calgary, Alberta, between April 1, 2011, and March 31, 2017, were linked to DAD. Personal health number (PHN) and gender were used to identify specific individuals, and specimen collection time-points were used to identify specific hospitalization records. A third common variable on admission date between these databases was used to validate the linkage process. Descriptive statistics were used to characterize HA-MRSA and CA-MRSA cases identified through the linkage process.

Results:

A total of 2,430 surveillance records (94.6%) were successfully linked to the correct hospitalization period. By linking surveillance and administrative data, we were able to identify key differences between patients with HA- and CA-MRSA. These differences are consistent with previously reported findings in the literature. Data linkage to DAD may be a novel tool to enhance and augment the details of base surveillance data.

Conclusion and recommendations:

This is the first Canadian study linking a frontline healthcare-associated infection AMR surveillance database to an administrative population database. This work represents an important methodological step toward complementing traditional AMR surveillance data practices. Data linkage to other data types, such as primary care, emergency, social, and biological data, may be the basis of achieving more precise data focused around AMR.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 40 , Issue 10 , October 2019 , pp. 1144 - 1150
Copyright
© 2019 by The Society for Healthcare Epidemiology of America. All rights reserved. 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

PREVIOUS PRESENTATION. This study was presented at the 2018 International Population Data Linkage Conference on September 13, 2018, in Banff, Alberta, Canada.

References

Wilson, APR, Livermore, DM, Otter, JA, et al. Prevention and control of multi-drug-resistant gram-negative bacteria: recommendations from a Joint Working Party. J Hosp Infect 2016;92:S1–S44.CrossRefGoogle ScholarPubMed
Vasoo, S, Barreto, JN, Tosh, PK. Emerging issues in gram-negative bacterial resistance: an update for the practicing clinician. Mayo Clin Proc 2015;90:395–403.CrossRefGoogle ScholarPubMed
Tornimbene, B, Eremin, S, Escher, M, Griskeviciene, J, Manglani, S, Pessoa-Silva, CL. WHO global antimicrobial resistance surveillance system early implementation. Lancet Infect Dis 2018;18:241–242.CrossRefGoogle ScholarPubMed
WHO publishes list of bacteria for which new antibiotics are urgently needed. World Health Organization website. https://www.who.int/news-room/detail/27-02-2017-who-publishes-list-of-bacteria-for-which-new-antibiotics-are-urgently-needed. Published 2017. Accessed March 16, 2018.Google Scholar
Antibiotic/antimicrobial resistance (AR/AMR)—biggest threats and data. Centers for Disease Control and Prevention website. https://www.cdc.gov/drugresistance/biggest_threats.html. Published 2018. Accessed April 14, 2019.Google Scholar
Amaratunga, K, Tarasuk, J, Tsegaye, L, Archibald, CP. Advancing surveillance of antimicrobial resistance: summary of the 2015 CIDSC report. Can Commun Dis Rep 2016;42:232–237.CrossRefGoogle ScholarPubMed
Drees, M, Gerber, JS, Morgan, DJ, Lee, GM. Research methods in healthcare epidemiology and antimicrobial stewardship: use of administrative and surveillance databases. Infect Control Hosp Epidemiol 2016;37:1278–1287.CrossRefGoogle ScholarPubMed
Census profile, 2016 census: Alberta profile. Statistics Canada website. https://www12.statcan.gc.ca/census-recensement/2016/dp-pd/prof/details/Page.cfm?Lang=E%26Geo1=PR%26Code1=48%26Geo2=%26Code2=%26Data=Count%26SearchText=Alberta%26SearchType=Begins%26SearchPR=01%26B1=All%26GeoLevel=PR%26GeoCode=48. Published 2017. Accessed March 16, 2018.Google Scholar
Provincial wide surveillance. Alberta Health Services website. https://www.albertahealthservices.ca/assets/healthinfo/ipc/hi-ipc-provincial-surveillance.pdf. Published 2018. Accessed March 17, 2018.Google Scholar
Methicillin-resistant Staphylococcus aureus (MRSA) culture. Calgary Laboratory Services website. http://www.calgarylabservices.com/lab-services-aguide/microbiology/Test/Tests/MethicillinResistantStaphylococcusAureusMRSA.aspx. Published 2018. Accessed October 22, 2018.Google Scholar
Discharge abstract database (DAD) metadata. Canadian Institute for Health Information website. https://www.cihi.ca/en/discharge-abstract-database-metadata. Published 2018. Accessed April 5, 2018.Google Scholar
Alberta health care insurance plan (AHCIP). Government of Alberta website. https://www.alberta.ca/ahcip.aspx. Published 2019. Accessed April 6, 2019.Google Scholar
Naimi, TS, LeDell, KH, Como-Sabetti, K, et al. Comparison of community and health care–associated methicillin-resistant Staphylococcus aureus infection. JAMA 2003;290:2976–2984.CrossRefGoogle ScholarPubMed
Morrison, MA, Hageman, JC, Klevens, RM. Case definition for community-associated methicillin-resistant Staphylococcus aureus. J Hosp Infect 2006;62:241.CrossRefGoogle ScholarPubMed
MRSA: information for clinicians. Centers for Disease Control and Prevention website. https://www.cdc.gov/mrsa/community/clinicians/index.html. Published 2016. Accessed April 5, 2018.Google Scholar
Methicillin-resistant Staphylococcus aureus (MRSA) provincial surveillance protocol. Alberta Health Services website. https://www.albertahealthservices.ca/assets/healthinfo/ipc/hi-ipc-sr-mrsa-surveillance-protocol.pdf. Published 2018. Accessed April 5, 2018.Google Scholar
Andreassen, AES, Jacobsen, CM, de Blasio, BF, White, R, Kristiansen, IS, Elstrøm, P. The impact of methicillin-resistant S. aureus on length of stay, readmissions and costs: a register based case-control study of patients hospitalized in Norway. Antimicrob Resist Infect Control 2017;6:74.CrossRefGoogle ScholarPubMed
Quan, H, Sundararajan, V, Halfon, P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005;43:1130–1139.CrossRefGoogle ScholarPubMed
Tackling antimicrobial resistance and antimicrobial use: a pan-Canadian framework for action. Government of Canada website. https://www.canada.ca/en/health-canada/services/publications/drugs-health-products/tackling-antimicrobial-resistance-use-pan-canadian-framework-action.html#a3.1. Published 2017. Accessed April 6, 2018.Google Scholar
Dusetzina, SB, Tyree, S, Meyer, AM, et al. Linking data for health services research: a framework and instructional guide, an overview of record linkage methods. Agency for Healthcare Research and Quality (US) website. https://www.ncbi.nlm.nih.gov/books/NBK253312/. Published 2014. Accessed April 6, 2019.Google Scholar
Virnig, BA, McBean, M. Administrative data for public health surveillance and planning. Annu Rev Public Health 2001;22:213–230.CrossRefGoogle ScholarPubMed
Lukovac, E, Koluder-Cimic, N, Hadzovic-Cengic, M, Baljic, R, Hadzic, A, Gojak, R. Analysis of comorbidity of the patients affected by Staphylococcal bacteremia/sepsis in the last ten years. Materia Socio Medica 2012;24:13.CrossRefGoogle Scholar
Campbell, KM, Vaughn, AF, Russell, KL, et al. Risk factors for community-associated methicillin-resistant Staphylococcus aureus infections in an outbreak of disease among military trainees in San Diego, California; 2002. J Clin Microbiol 2004;42:4050–4053.CrossRefGoogle Scholar
Supplementary material: File

Lee et al. supplementary material

Tables S1-S3 and Figures S1-S2

Download Lee et al. supplementary material(File)
File 186.2 KB