Assessment of utilization of automated systems and laboratory information management systems in clinical microbiology laboratories in Thailand

Introduction: Clinical microbiology laboratories are essential for diagnosing and monitoring antimicrobial resistance (AMR). Here, we assessed the systems involved in generating, managing and analyzing blood culture data in these laboratories in an upper-middle-income country. Methods: From October 2023 to February 2024, we conducted a survey on the utilization of automated systems and laboratory information management systems (LIMS) for blood culture specimens in 2022 across 127 clinical microbiology laboratories (one each from 127 public referral hospitals) in Thailand. We categorized automated systems for blood culture processing into three steps: incubation, bacterial identification, and antimicrobial susceptibility testing (AST). Results: Of the 81 laboratories that completed the questionnaires, the median hospital bed count was 450 (range, 150-1,387), and the median number of blood culture bottles processed was 17,351 (range, 2,900-80,330). All laboratories (100%) had an automated blood culture incubation system. Three-quarters of the laboratories (75%, n = 61) had at least one automated system for both bacterial identification and AST, about a quarter (22%, n = 18) had no automated systems for either step, and two laboratories (3%) outsourced both steps. The systems varied and were associated with the hospital level. Many laboratories utilized both automated systems and conventional methods for bacterial identification (n = 54) and AST (n = 61). For daily data management, 71 laboratories (88%) used commercial microbiology LIMS, three (4%) WHONET, three (4%) an in-house database software and four (5%) did not use any software. Many laboratories manually entered data of incubation (73%, n = 59), bacterial identification (27%, n = 22) and AST results (25%, n = 20) from their automated systems into their commercial microbiology LIMS. The most common barrier to data analysis was ‘lack of time’, followed by ‘lack of staff with statistical skills’ and ‘difficulty in using analytical software’. Conclusion: In Thailand, various automated systems for blood culture and LIMS are utilized. However, barriers to data management and analysis are common. These challenges are likely present in other upper-middle-income countries. We propose that guidance and technical support for automated systems, LIMS and data analysis are needed

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, p0.20). 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

Cyclical cervical function in the mare involves remodelling of collagen content, which is correlated with modification of oestrogen

This study was conducted to elucidate mare cervical dilation mechanisms by testing two hypotheses: (i) the proportion of collagen staining in histological samples of mare cervices and (ii) the abundance of hormone receptors in the equine cervix differ with stage of the oestrous cycle and site within the cervix. Tissues and jugular vein blood samples were collected from 15 mares. Collagen content was assessed using Masson's Trichome staining. Receptor abundance was assessed using RT-PCR, qRT-PCR and immunohistochemistry. In sub-epithelial stroma, there was less collagen during the follicular than luteal phase, in the caudal- (P =  0.029), mid- (P =  0.0000) and cranial (P =  0.001) cervical tissue. In the deep stroma, there was less collagen staining during the follicular stage in the mid- (P =  0.004) and cranial- (P =  0.041) cervical regions. There were PTGER2, PTGER3, PGR and ESR1 mRNA transcripts in the cervix. A greater proportion of cells were positive for ESR1 protein during the follicular phase in sub-epithelial (P =  0.019) and deep (P =  0.013) stroma. The abundance of ESR1 in the epithelium was negatively correlated with collagen staining in sub-epithelial (P =  0.007) and deep (P =  0.005) stroma. The results of the study provide new information about the cervical biology of mares by increasing the knowledge about collagen content and the relationship between collagen content and ESR1 protein abundance during the oestrous cycle which indicates the ESR1 receptor is a candidate for involvement in control of cervical dilation.</p

Using economic levers to change behaviour: The case of Thailand's universal coverage health care reforms

Thailand's universal coverage health care policy has been presented as a knowledge-based reform involving substantial pre-planning, including expert economic analysis of the financing mechanism. This paper describes the new financing system introduced from 2001 in which the Ministry of Public Health allocated monies to local Contracted Units for Primary Care (CUPs) on the basis of population. It discusses the policy intention to use capitation funding to change incentive structures and engineer a transfer of professional staff from over-served urban areas to under-served rural areas. The paper utilises qualitative data from national policy makers and health service staff in three north-eastern provinces to tell the story of the reforms. We found that over time government moved away from the original capitation funding model as the result of (a) a macro-allocation problem arising from system disturbance and professional opposition, and (b) a micro-allocation problem that emerged when local budgets were not shared equitably. In many CUPs, the hospital directors controlling resource allocation channelled funds more towards curative services than community facilities. Taken together the macro and micro problems led to the dilution of capitation funding and reduced the re-distributive effects of the reforms. This strand of policy foundered in the face of structural and institutional barriers to change.Universal coverage Economic incentives Health care reforms Thailand 30 baht Scheme Policy implementation