The utility of clinical microbiology data for Antimicrobial Resistance (AMR) surveillance is increasingly recognized, although the availability and quality of these data can vary broadly. Troubleshooting the core technical issues related to the use of routine data at different action levels is fundamental to leverage this rich data source. There has been a surge in the development of open-source integrated solutions that enable efficient data collection, organization, and distribution at the hospital level.
However, to enhance usability and compatibility, there is a prerequisite to define data standards and establish tools supporting facility-level and public health surveillance. A political declaration aimed at reducing deaths associated with bacterial AMR by 10% by 2030 was set by the United Nations General Assembly in 2024. Achieving this target lies in better access to microbiological diagnostics and AMR surveillance.
Routine microbiological data, especially from high-income countries, has shown great promise in enriching AMR surveillance. When these detailed clinical data sets are aggregated effectively, they can unveil critical trends useful for guiding local empiric therapy and antibiotics procurement, highlighting infection control issues and even elucidating AMR prevalence at higher levels. Particularly, by merging routine microbiology data with clinical and pharmacy data, the understanding of AMR can be greatly refined, informing national surveillance and various action plans.
The value of blood culture data from hospitals has been highlighted as playing a crucial role in surveillance across varied settings. Much as the routine clinical microbiology data provides a wealth of information for AMR surveillance, the differential availability of these across countries and the logistical, ethical, and legal challenges associated with its use for secondary purposes need to be tactfully addressed. Realizing the full potential of these data sources is paramount to AMR control that is target-based and geared towards both quantifying and reducing the AMR burden.
Approaches such as incorporating LIMS and EHR at the facility level have proven to be robust. By facilitating a more efficient data management from different diagnostics and clinical care, these systems enable laboratory staff to play a more integral part in patient management and clinical decision-making. Moreover, digitalizing these data not only enhances local patient care but also aligns local data utility with broader public health objectives.
Importantly, the transmission of data beyond the facility and data aggregation from multiple facilities need to follow specific and universally recognized standards and fit-for-purpose formats. More so, addressing variable encoding for patient and clinical data, standardizing key variables such as species name, specimen types, and drug names, and establishing a balance between granularity and privacy protection raises a lot for consideration and focus.
In conclusion, the eventful journey from hospital labs to national and international surveillance systems can drastically benefit from open source software tools catering to specific steps in data collection, analysis and sharing. The Laboratory Information Management System (LIMS) for example, is software designed to support data collection and storage within a laboratory.