Frequency of antimicrobial-resistant bloodstream infections in 111 hospitals in Thailand, 2022.

OBJECTIVES: To evaluate the frequency of antimicrobial-resistant bloodstream infections (AMR BSI) in Thailand. METHODS: We analyzed data from 2022, generated by 111 public hospitals in health regions 1 to 12, using the AutoMated tool for Antimicrobial resistance Surveillance System (AMASS), and submitted to the Ministry of Public Health, Thailand. Multilevel Poisson regression models were used. RESULTS: The most common cause of community-origin AMR BSI was third-generation cephalosporin-resistant Escherichia coli (3GCREC, 65.6%; 5101/7773 patients) and of hospital-origin AMR BSI was carbapenem-resistant Acinetobacter baumannii (CRAB, 51.2%, 4968/9747 patients). The percentage of patients tested for BSI was negatively associated with the frequency of community-origin 3GCREC BSI and hospital-origin CRAB BSI (per 100,000 tested patients). Hospitals in health regions 4 (lower central region) had the highest frequency of community-origin 3GCREC BSI (adjusted incidence rate ratio, 2.06; 95% confidence interval: 1.52-2.97). Health regions were not associated with the frequency of hospital-origin CRAB BSI, and between-hospital variation was high, even adjusting for hospital level and size. CONCLUSION: The high between-hospital variation of hospital-origin CRAB BSI suggests the importance of hospital-specific factors. Our approach and findings highlight health regions and hospitals where actions against AMR infection, including antimicrobial stewardship and infection control, should be prioritized.

Frequency and mortality rate following antimicrobial-resistant bloodstream infections in tertiary-care hospitals compared with secondary-care hospitals.

There are few studies comparing proportion, frequency, mortality and mortality rate following antimicrobial-resistant (AMR) infections between tertiary-care hospitals (TCHs) and secondary-care hospitals (SCHs) in low and middle-income countries (LMICs) to inform intervention strategies. The aim of this study is to demonstrate the utility of an offline tool to generate AMR reports and data for a secondary data analysis. We conducted a secondary-data analysis on a retrospective, multicentre data of hospitalised patients in Thailand. Routinely collected microbiology and hospital admission data of 2012 to 2015, from 15 TCHs and 34 SCHs were analysed using the AMASS v2.0 (www.amass.website). We then compared the burden of AMR bloodstream infections (BSI) between those TCHs and SCHs. Of 19,665 patients with AMR BSI caused by pathogens under evaluation, 10,858 (55.2%) and 8,807 (44.8%) were classified as community-origin and hospital-origin BSI, respectively. The burden of AMR BSI was considerably different between TCHs and SCHs, particularly of hospital-origin AMR BSI. The frequencies of hospital-origin AMR BSI per 100,000 patient-days at risk in TCHs were about twice that in SCHs for most pathogens under evaluation (for carbapenem-resistant Acinetobacter baumannii [CRAB]: 18.6 vs. 7.0, incidence rate ratio 2.77; 95%CI 1.72-4.43, p<0.001; for carbapenem-resistant Pseudomonas aeruginosa [CRPA]: 3.8 vs. 2.0, p = 0.0073; third-generation cephalosporin resistant Escherichia coli [3GCREC]: 12.1 vs. 7.0, p<0.001; third-generation cephalosporin resistant Klebsiella pneumoniae [3GCRKP]: 12.2 vs. 5.4, p<0.001; carbapenem-resistant K. pneumoniae [CRKP]: 1.6 vs. 0.7, p = 0.045; and methicillin-resistant Staphylococcus aureus [MRSA]: 5.1 vs. 2.5, p = 0.0091). All-cause in-hospital mortality (%) following hospital-origin AMR BSI was not significantly different between TCHs and SCHs (all p>0.20). Due to the higher frequencies, all-cause in-hospital mortality rates following hospital-origin AMR BSI per 100,000 patient-days at risk were considerably higher in TCHs for most pathogens (for CRAB: 10.2 vs. 3.6,mortality rate ratio 2.77; 95%CI 1.71 to 4.48, p<0.001; CRPA: 1.6 vs. 0.8; p = 0.020; 3GCREC: 4.0 vs. 2.4, p = 0.009; 3GCRKP, 4.0 vs. 1.8, p<0.001; CRKP: 0.8 vs. 0.3, p = 0.042; and MRSA: 2.3 vs. 1.1, p = 0.023). In conclusion, the burden of AMR infections in some LMICs might differ by hospital type and size. In those countries, activities and resources for antimicrobial stewardship and infection control programs might need to be tailored based on hospital setting. The frequency and in-hospital mortality rate of hospital-origin AMR BSI are important indicators and should be routinely measured to monitor the burden of AMR in every hospital with microbiology laboratories in LMICs.

Local and timely antimicrobial resistance data for local and national actions: the early implementation of an automated tool for data analysis at local hospital level in Thailand.

Background: In low- and middle-income countries (LMICs), hospitals can rarely utilize their own antimicrobial resistance (AMR) data in a timely manner. Objectives: To evaluate the utility of local AMR data generated by an automated tool in the real-world setting. Methods: From 16 December 2022 to 10 January 2023, on behalf of the Health Administration Division, Ministry of Public Health (MoPH) Thailand, we trained 26 public tertiary-care and secondary-care hospitals to utilize the AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) with their own microbiology and hospital admission data files via two online meetings, one face-to-face meeting and online support. All meetings were recorded on video, and feedback was analysed. Results: Twenty-five hospitals successfully generated and shared the AMR reports with the MoPH by 28 February 2023. In 2022, the median frequency of hospital-origin bloodstream infections (BSIs) caused by carbapenem-resistant Escherichia coli (CREC) was 129 (range 0-1204), by carbapenem-resistant Klebsiella pneumoniae (CRKP) was 1306 (range 0-5432) and by carbapenem-resistant Acinetobacter baumannii (CRAB) was 4472 (range 1460-11 968) per 100 000 patients tested for hospital-origin BSI. The median number of all-cause in-hospital deaths with hospital-origin AMR BSI caused by CREC was 1 (range 0-18), by CRKP was 10 (range 0-77) and by CRAB was 56 (range 7-148). Participating hospitals found that the data obtained could be used to support their antimicrobial stewardship and infection prevention control programmes. Conclusions: Local and timely AMR data are crucial for local and national actions. MoPH Thailand is inviting all 127 public tertiary-care and secondary-care hospitals to utilize the AMASS. Using any appropriate analytical software or tools, all hospitals in LMICs that have electronic data records should analyse and utilize their data for immediate actions.