Identifying National Projections of Drug-resistant Pathogens
NOV 13, 2016 | CONTAGION EDITORIAL STAFF
Vikas Gupta, PharmD, BCPS, director of Clinical Strategy at Becton Dickinson, explains how his team identified national projections of drug-resistant pathogens.
Interview Transcript (slightly modified for readability)
“Really it’s important to note the national projections [of drug-resistant pathogens]. One [reason] is that there may be regional differences that we may not be aware of. This helps the acute facilities’ health systems mobilize resources that they may need to combat the spread of some of the resistances in their own areas. Also, [it’s important] for public health agencies, as well, to really mobilize their resources, whether it’s at local county levels, state levels, or at national levels.
This type of data really helps provide a glimpse as to how much [we’re seeing of] healthcare-associated infections, which [would be solved by] a set of resources you would allocate in the acute-care setting; [however] if we’re seeing resistance in the non-acute–care setting then it’s a different type of perspective that one may need to approach from a healthcare facility perspective, as well as overall from public health as well.
We used our BD microbiology research database, and that’s a Becton Dickinson database, and the reason for this is we have very rich and robust data in our database. [The BD] database has not just data on hospital onset isolates, but also overall from an admission period, and also from an ambulatory perspective. There [are] very few databases out there that really provide a comprehensive view of how many pathogens are collected, what the results of those pathogens are, in these types of different settings, overall. So this afforded us an opportunity to really look at the data to be able to not just observe cases but also use statistical methodological techniques such as ranking methodology that we use to [get] national projections.
The other aspect that’s unique to the database is that microbiology data can be very textual; [therefore, there are] many, many different ways that these pathogens can be called pathogens. For example, [with] Staph. aureus, [there] can be over a 100,000 ways [that] Staph. aureus is called Staph. aureus. The uniqueness in the BD database is that all those pathogens and susceptibilities are mapped and organized to a common standard, so it allows us to query much more readily, to do these types of analyses.”
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