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.
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http://dx.doi.org/10.1017/ice.2019.184 | DOI Listing |
Age Ageing
January 2025
Centre for Research in Public Health and Community Care (CRIPACC), University of Hertfordshire, College Lane, Hatfield, UK.
Background: We developed a prototype minimum data set (MDS) for English care homes, assessing feasibility of extracting data directly from digital care records (DCRs) with linkage to health and social care data.
Methods: Through stakeholder development workshops, literature reviews, surveys and public consultation, we developed an aspirational MDS. We identified ways to extract this from existing sources, including DCRs and routine health and social care datasets.
Int J Rheum Dis
January 2025
Japan Drug Information Institute in Pregnancy, National Center for Child Health and Development, Tokyo, Japan.
Aim: Uncontrolled chronic inflammatory diseases (CIDs) before, during, and after pregnancy, as well as some CID medications, can increase the risk of impaired fertility in addition to adverse maternal/pregnancy outcomes in women of childbearing age. We report pregnancy outcomes from prospectively reported pregnancies in Japanese women treated with certolizumab pegol (CZP).
Methods: Data from July 2001 to November 2020 on CZP-exposed pregnancies from the CZP Pharmacovigilance safety database were reviewed.
Drug Alcohol Depend Rep
March 2025
Department of Health Promotion and Behavior, College of Public Health, University of Georgia, Athens, GA, United States.
Background: Syringe services programs (SSP) are evidence-based venues offering harm reduction services to persons who inject drugs (PWID), such as sterile syringes, STI/HIV testing, and linkage to care to decrease drug use-related morbidities and mortalities. Adverse childhood experiences (ACEs) have been linked with reduced resilience, while increased resilience can help PWID attend SSPs. This study examined the potential mediating role of resilience between ACEs and SSP attendance among PWID.
View Article and Find Full Text PDFJ R Stat Soc Ser A Stat Soc
January 2025
Division of Cancer Epidemiology & Genetics, National Cancer Institute, Biostatistics Branch, Rockville, USA.
Accurate cancer risk estimation is crucial to clinical decision-making, such as identifying high-risk people for screening. However, most existing cancer risk models incorporate data from epidemiologic studies, which usually cannot represent the target population. While population-based health surveys are ideal for making inference to the target population, they typically do not collect time-to-cancer incidence data.
View Article and Find Full Text PDFJ R Stat Soc Ser A Stat Soc
January 2025
Department of Sociology and Carolina Population Center, University of Carolina at Chapel Hill, 268 Hamilton Hall, Chapel Hill, NC 27516, USA.
Many population surveys do not provide information on respondents' residential addresses, instead offering coarse geographies like zip code or higher aggregations. However, fine resolution geography can be beneficial for characterizing neighbourhoods, especially for relatively rare populations such as immigrants. One way to obtain such information is to link survey records to records in auxiliary databases that include residential addresses by matching on variables common to both files.
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