3 AMR data sources

You should by now understand the importance of data for AMR decision-making, but where do AMR data come from?

There are three broad classifications of data sources: primary, secondary and tertiary. All types are relevant sources of AMR data, and each type has distinct advantages and disadvantages, which are summarised in Table 5.

Table 6 presents some examples of primary, secondary and tertiary AMR, AMU and AMC data.

Finally, you may have also noticed that some of these data sources reflect ‘routine’ data collection activities, such as medical and customs records, whereas other data sources represent activities conducted periodically or sporadically, such as annual surveys, and still others only when an outbreak occurs.

Routine health data are collected at the service delivery level – for example, a health facility, veterinary practice, pharmacy, farm, or laboratory. These data are collected on a regular, continuous basis through individual records, registers and electronic systems. They relate to vital events, patient demographic and clinical characteristics, laboratory results, infrastructure, the health and veterinary workforce, commodities and finances. These sources provide data that inform service delivery, progress towards program objectives and national policy. Routine health data can also be reported in a summarised form on a monthly or quarterly basis and then aggregated at district, regional and national levels – when accessed in this form, they represent secondary data.

A major advantage of routine data collection is that it captures data on large populations and reflects what happens under real-world conditions – for example, antimicrobial prescribing practices in day-to-day work might be different from self-reported prescribing practices whilst participating in an antimicrobial stewardship program. Once the data have been collected, they are much cheaper to access and use compared to conducting a survey or starting a new surveillance program. However, there are limitations, including that the data are not collected for the purpose of the research or analysis of interest, which means that important variables might be missing. Routinely collected data are often of poorer quality than data collected specifically for research purposes, and might not be representative of the entire patient or animal population. For example, sometimes only patients who have failed first-line treatment have samples collected and submitted for culture and susceptibility testing, particularly in low-resource settings. Where this is the case there will be limited data available on patients with uncomplicated infections.

Non-routine health data sources are data collected through activities such as surveys, which may comprise questionnaires, collection of biological samples, or both. People, animals and the environment can all be surveyed. These surveys are conducted periodically or on a one-off basis and provide data meant to answer specific questions. Surveys can be large-scale and population-based (such as a census), sample-based (such as behavioural surveys) and/or focused on specific entities or institutions (such as program evaluations, veterinary facility assessments, or patient satisfaction questionnaires). A major disadvantage is that these data sources can be costly to collect as they may require additional staff and may be difficult to repeat. For example, a single survey is useful for understanding AMR at a particular time point, but unless a survey is repeated every year it will lose relevance as time goes on. You will learn more about different types of samples in the Sampling module.