Epidemiology of Antimicrobial-use and Antimicrobial-resistant Infections in Four Hospitals in Thailand

Rationale:

Despite the availability of guidance documents for implementing antimicrobial stewardship (AMS) programs at both hospital and national levels, there is a lack of robust data to monitor and evaluate the current antimicrobial use practice in low and middle-income countries (LMICs). Evidence on the impact of antibiotic de-escalation on antimicrobial-resistant (AMR) infection is limited. In addition, practical guidelines on how to utilize and analyze routine data for LMICs have not been established.

Objective:

In this study, our primary objective is (a) to evaluate impact of antibiotic de-escalation. Our secondary objectives are (b) to estimate accuracy of automated outbreak detection systems, (c) to evaluate epidemiology of antimicrobial use (AMU) and AMR infections and associations between AMU and AMR infections, and (d) to develop AMS outcome indicators that are applicable for local and national actions in low and middle-income countries (LMICs)

Methodology:

The investigators will conduct a retrospective data analysis using individual-level electronic databases of hospital admission, ward transfer, microbiology laboratory and drug dispensing from four hospitals (including Chiangrai Prachanukroh Hospital, Chiangrai; Sunpasitthiprasong Hospital, Ubon Ratchathani; Phrachomklao Hospital, Phetchaburi; and Chaoprayayommarat Hospital, Suphanburi) from January 2019 to December 2024 in Thailand.

The hospital admission data collected will include hospital number (HN) and admission number (AN), sex, age, admission wards, admission dates, discharge dates, discharge outcomes (discharge type and discharge status) and ICD-10. The ward transfer data collected will include HN, AN, ward, data transfer in and date transfer out. The microbiology laboratory data collected will include HN, AN, ward, specimen type, specimen collection date, report dates, culture results and antimicrobial susceptibility results. The drug dispensing data collected will include, HN, AN, drug name, drug code, route of drug administration, the dosage regimen, drug start dates, drug stop dates, wards and departments of prescribing physicians. The HN and AN will be used to link the three databases together. The ward data will also be used to evaluate the cluster of AMR infection. The department of prescribing physicians will be used to understand AMS and antimicrobial use (AMU) by department because multiple wards are mixed wards (i.e. having patients from multiple departments in the same wards). Infection and Prevention Control (IPC) team's records of cluster will be used to evaluate the accuracy of automated outbreak detection systems. All data will be protected at the highest security.

Inverse Probability of Treatment Weighting (IPTW) will be used to evaluate impact of antibiotic de-escalation on new AMR BSI. Descriptive analysis and regression models will also be used.

Outcomes:

In this study, our primary outcomes are (a1) the relative risk of new AMR BSI in patients who receive antibiotic de-escalation compared to those who do not after a short-course (≤7 days) of parenteral antibiotics, and (a2) the relative risk of in-hospital 30-day mortality. Our secondary outcomes include (b) the accuracy of automated outbreak detection systems, (c) factors associated with AMU and AMR infections, and (d) factors associated with new AMS outcome indicators.

Findings of this study, particularly impact of antibiotic de-escalation on new AMR BSI and new AMS outcome indicators will be used to expand AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) with AMS modules (i.e. AMASS version 4.0), under collaboration with the Ministry of Public Health Thailand. The investigators anticipate that findings of this study will support the monitoring and evaluation of AMS practice at both hospital and national levels in Thailand and other LMICs in the future.

For primary objectives Inclusion Criteria

• All age and gender
• Admitted to four collaborating hospitals from 1 Jan 2019 to 31 Dec 2024
• Received a parenteral antibiotic for at least four consecutive days
• Were still hospitalized on day 8 after starting a parenteral antibiotic

Exclusion criteria

• Admitted as day admissions to four collaborating hospitals from 1 Jan 2019 to 31 Dec 2024
• Had a clinical specimen collected within 2 calendar days of starting a parenteral antibiotic culture positive for an antimicrobial-resistant organism or Staphylococcus aureus

Antimicrobial-resistant (AMR) organism is defined as an organism that is resistant to Access and Low Watch antibiotics, and if the organism is the cause of infection, the recommended antimicrobial therapy involves the use of Medium Watch, High Watch or Reserve antibiotics. The common organisms include methicillin-resistant S. aureus, methicillin-resistant coagulase-negative Staphylococcus spp., ampicillin-resistant Enterococcus spp., vancomycin-resistant Enterococcus spp., 3rd-generation cephalosporin-resistant Gram-negative bacterium and carbapenem-resistant Gram-negative bacterium. The definition of organism includes organisms frequently associated with contamination including coagulase-negative staphylococci, viridans group streptococci, Corynebacterium spp., Bacillus spp., Diptheroid spp., Micrococcus spp. and Propionibacterium spp.. All types of specimens are included (e.g. sputum and tracheal suction). We excluded such patients because the study has no clinical data to differentiate whether the isolated AMR organisms are causing infections or represent colonization.

For secondary objectives

Inclusion criteria

• All age and gender
• Admitted to four collaborating hospitals from 1 Jan 2019 to 31 Dec 2024

Exclusion criteria

• Admitted as day admissions to four collaborating hospitals from 1 Jan 2019 to 31 Dec 2024