Welcome to this edition of the twenty-nineteen National Healthcare Safety Network, or NHSN
Quick Learn series which focuses on understanding and running the Standardized Antimicrobial
Administration Ratio or SAAR.
This Quick Learn is tailored to facilities reporting or interested in reporting data
to the Antimicrobial Use or AU option in NHSN, and group users with access to these data.
Any NHSN user interested in learning about the SAAR metric will benefit from this content.
This is part one of a two-part series on the SAAR.
This presentation will address what a SAAR is and why a SAAR is useful.
We will introduce updates to the SAAR including new drug categories and locations and describe
where to find a SAAR report in NHSN.
This presentation will also compare the 2017 baseline SAAR to the original SAAR metric,
which was calculated using 2014 baseline data.
After this quick learn the learner will be able to describe the components and the utility
of the SAAR metric, summarize the differences between the 2014 baseline and 2017 baseline
SAARs, and identify where to find SAAR reports within the NHSN application.
This Quick Learn will not cover how to run, interpret or modify a SAAR report, these concepts
are covered in part two of this two-part series.
Part two can be found on the NHSN AUR homepage under training materials or at the link provided
on this slide.
This presentation will also not cover details of the SAAR methodology, this information
can be found in the AUR Module protocol at the link provided on this slide.
To help support your understanding of the SAAR, a link to an in-depth statistical explanation
of the SAAR is also included on this slide.
What is a SAAR?
The SAAR is a standardized metric of antimicrobial use available to facilities reporting data
into the NHSN AU option.
The SAAR is a ratio comparing observed or reported antimicrobial use to the antimicrobial
use predicted by a referent or baseline, population.
Let’s look at the ratio a little more closely.
The observed number of antimicrobial days is how many days the facility actually administered
antimicrobial agents to patients in a given location.
The predicted antimicrobial days for that specific location are calculated using statistical
models based on nationally aggregated data.
These models take into account differences in hospital characteristics such as hospital size.
To interpret the SAAR value, consider whether the SAAR is less than, equal to, or greater than one
A SAAR below one point zero indicates less antimicrobial use than predicted and may suggest under-use.
A SAAR the same as one point zero indicates antimicrobial use is equal to the referent
population’s use.
A SAAR above one point zero indicates more antimicrobial use than predicted and may suggest over-use.
Note that a SAAR is not a definitive measure of the appropriateness of antimicrobial use,
and any SAAR value may warrant additional investigation.
SAARs are a valuable metric for a variety of purposes.
SAARs can be used for public health disease surveillance, an organization’s internal
quality improvement efforts, and for benchmarking against external organizations
to aid in quality improvement.
SAAR reports are not used for public reporting, payment programs, or regulatory
and accreditation programs.
A SAAR can be used to prioritize and guide hospital or healthcare system stewardship efforts.
For instance, the SAAR can help determine where to focus resources and stewardship efforts,
such as in a specific unit or with specific class of drugs.
The SAAR can also be used to assess progress of interventions with pre- and post-intervention
data, to understand how units of similar make up may have different antimicrobial use within
a facility or system and to set stewardship goals.
The SAAR was first developed using aggregated 2014 AU data submitted to NHSN from 77 participating
acute care hospitals.
These data were used in statistical models to predict antimicrobial days.
These SAAR calculations cover six location groupings and five antibiotic categories.
They do not include antifungal or anti-influenza agents.
You can refer to the 2014 SAAR document to review the drugs that are included in each
SAAR category.
The six location groupings included in SAARs calculated under the 2014 baseline are listed
here on this slide.
Please take a moment to pause your video and review the location groupings.
Note that AU data for other location types were not included in the 2014 SAARs but can
still be analyzed using other AU report options within the NHSN application.
Since the 2014 baseline, a lot has changed.
As more and more facilities have adopted the AU option there is more diversity in the size
and acuity of submitting hospitals as well as the types of patient care locations.
As of June 2019, over 1300 hospitals participate in the AU option.
Updating the baseline year using data submitted to NHSN in 2017 helps us to account for these changes.
New prediction models allow us to increase the number of patient care locations modeled,
to assess AU risk in more settings and update the antimicrobial groupings.
All of this leads to greater precision when predicting antimicrobial use.
The calculations for SAARs using the 2017 baseline cover 15 antimicrobial categories.
These categories now include narrow spectrum beta-lactam agents, antifungals, grouping
categories specific to pediatric populations and antibiotics posing the highest risk for
Clostridioides difficile infections.
In addition, we updated all SAAR antibiotic categories, adding or removing drugs from
the categories as needed.
A complete list of the antimicrobial categories is available in the AUR module protocol.
While the original, 2014 baseline SAARs were developed for six location groupings, 2017
baseline SAARs include 13 separately modeled locations.
Unlike the 2014 baseline SAAR, the 2017 baseline SAARs model adult and pediatric locations separately.
These include the 8 adult and 5 pediatric locations listed here.
Among these location types, two, general hematology-oncology and adult step-down units,
were added in the 2017 models.
Please take a moment to pause your video and review the locations.
Shown here is an overview of which variables were included in the 2014 and 2017 models.
An X indicates that one or more SAAR models in that baseline time period include that
factor as a risk adjustment.
In the 2017 baseline models, new factors were included as risk adjustment variables, including
the percentage of ICU beds and average length of stay.
A summary of the differences between 2014 baseline- and 2017 baseline- SAARs are shown here.
As you’ll see, the referent group (or baseline population) differs.
The 2017 baseline SAAR has a greater number and type of antimicrobial categories as well
as locations modeled than the original, 2014 baseline SAAR.
For what years can SAARs be calculated?
2014 baseline SAAR reports are available for 2014 through 2018 data.
2017 baseline SAAR reports are available for 2017 data moving forward.
Please note, because of the differences in the SAAR models, SAARs calculated under the
2014 baseline cannot be directly compared with 2017 baseline SAAR values.
Now that we’ve reviewed some of the differences between the original, 2014 baseline SAAR and
the 2017 baseline SAAR – let’s look at where to find the SAAR reports in NHSN.
Prior to running any NHSN analysis report, we need to generate new data sets.
After logging into NHSN, navigate to Analysis on the left-hand navigation bar.
Select Generate Data Sets and click the Generate New button.
It can take several minutes to generate data sets.
After generating a new dataset, navigate to Analysis on the left-hand navigation bar and select reports.
Select the antimicrobial use and resistance module drop down option and navigate to the
“antimicrobial use data” folder to access 2017 baseline SAAR reports.
Notice that next to the available SAAR reports in the Antimicrobial Use Data folder, the
baseline year – 2017 is listed in the title.
If you’re interested in SAAR reports calculated using the original, 2014 baseline, navigate
to analysis on the left-hand navigation bar and select reports.
Select the antimicrobial use and resistance module folder and navigate to the antimicrobial
use data – 2014 baseline SAARs folder to access 2014 baseline SAAR reports.
You may wonder which baseline should be used to meet your individual AU needs.
The first consideration when choosing a baseline is the time period of interest.
As previously discussed, 2014 baseline reports are available for 2014 through 2018 data.
2017 baseline reports are available for 2017 data moving forward.
In general, we recommend using the 2017 baseline SAAR reports when available because of their
increased precision, updated drug categories and additional locations.
However, the original, 2014 baseline SAAR reports may still be used.
For example, if you were assessing change over time for data from January 2016 to December
2017, you would use the 2014 baseline SAAR reports since 2016 data are not included in
the 2017 baseline SAAR reports.
Please note that reports generated in the NHSN application will always have the referent
population in the title.
Now that you understand the SAAR in greater detail, the next objective is to learn how
to generate a SAAR report within NHSN.
For more information on how to run, interpret and modify SAAR reports within the NHSN application
listen to part two of this quick learn series at the webpage provided.
This slide provides some additional NHSN Resources.
On the NHSN Antimicrobial Use and Resistance Module webpage, you can access the AUR Module
Protocol for detailed information on reporting; the SAAR Quick Reference Guides, or QRGs;
and other training webinars.
Additionally, CDC has put together a document called Strategies to Assess Antibiotic Use
to Drive Improvements in Hospitals available at the webpage provided.
This slide contains links to the resources referenced throughout this quick learn presentation.
Thank you for taking the time to watch this CDC NHSN Quick Learn.
If you have additional questions about SAAR reports or NHSN in general the email address
for the NHSN mailbox is nhsn@cdc dot gov.