Antibiograms: Overview and Challenges
An antibiogram is a profile that summarizes the susceptibility of pathogens to certain antibiotics. The report is a culmination of vast amounts of historical data collected from electronic medical records (EMRs), laboratory information software (LIS), and other data silos across a network. Microbiology laboratories and pharmacists work in collaboration with ID departments and relevant clinicians to gather the necessary data to discover resistance trends. The antibiogram is a critical pillar to any AMS program as it’s used by clinicians to make well-informed, data-driven decisions on therapy.
However, the creation of even a single antibiogram—which is often done manually—is an incredibly laborious and tedious process. Hospital and lab staff are overworked as it is, and shortages are becoming more dire. Often, there’s as little as one person responsible for compiling stewardship reports for an entire hospital. The burden of training replacements—which can take weeks or months—falls on these individuals as well since they are the sole keepers of the relevant expertise.
That’s why it can take some labs up to six months to compile an antibiogram, by which point the data would be outdated—when trying to capture a snapshot of an ever-evolving antimicrobial landscape, six months is six months too late.
Traditional antibiograms can also be severely limiting since they generally present a susceptibility profile for an entire hospital rather than a particular demographic, location, hospital unit, etc. While useful, general antibiograms can be less effective. Would a certain antibiotic affect a senior patient the same way it would a pediatric patient? What if one patient was African American and the other Hispanic? Each question would require a separate antibiogram, or more months of work.
For an antibiogram to be effective within the context of AMS, it must reflect current data and be tailored to the case at hand to ensure that patients get the correct treatment. Current methods do not achieve this and instead take time and resources that labs and hospitals don’t have.
