Objective:To determine the best nursing home facility characteristics for aggregating antibiotic susceptibility testing results across nursing homes to produce a useful annual antibiogram that nursing homes can use in their antimicrobial stewardship programs.Design:Derivation cohort study.Setting:Center for Medicare and Medicaid Services (CMS) certified skilled nursing facilities in Georgia (N = 231).Participants:All residents of eligible facilities submitting urine culture specimens for microbiologic testing at a regional referral laboratory.Methods:Crude and adjusted metrics of antibiotic resistance prevalence (percent of isolates testing susceptible) for 5 bacterial species commonly recovered from urine specimens were calculated using mixed linear models to determine which facility characteristics were predictive of testing antibiotic susceptibility.Results:In a single year, most facilities had an insufficient number of isolates tested to create facility-specific antibiograms: 49% of facilities had sufficient Escherichia coli isolates tested, but only about 1 in 10 had sufficient isolates of Klebsiella pneumoniae, Proteus mirabilis, Enterococcus faecalis, or Pseudomonas aeruginosa. After accounting for antibiotic tested and age of the patient, facility characteristics predictive of susceptibility were: E. coli, region, year, average length of stay; K. pneumoniae, region, bed size; P. mirabilis, region; and for E. faecalis or P. aerginosa no facility parameter remained in the model.Conclusions:Nursing homes often have insufficient data to create facility-specific antibiograms; aggregating data across nursing homes in a region is a statistically sound approach to overcoming data shortages in nursing home stewardship programs.

BackgroundUS skilled nursing facilities (SNFs) must have antibiotic stewardship programs to receive Medicare; this requires access to summary susceptibility data (antibiograms). Most SNFs test too few clinical samples to generate antibiograms by CLSI standards. We evaluated approaches to combining data across SNFs.MethodsUnsuppressed susceptibility testing results from pathogens recovered from urine specimens submitted in 2015–2016 to a regional referral laboratory servicing SNFs in GA were accessed. Study facilities were limited to GA SNFs (via linkage to CMS nursing home compare). No. and % testing susceptible (no. T, %S) of K. pneumoiae, E. coli, and P. mirabilis to cefazolin, levofloxacin, nitrofurantoin, TMP/Sulfa, and ceftriaxone were pooled overall, by geographic area, year, and other facility-characteristics. P. aeruginosa testing to cefazidime, imipenem, and piperacillin/tazobactam (P/T) were also evaluated. Differences in %S between stratum were considered clinically important if difference were >10 percentage points.ResultsOf 345 providers, 233 were confirmed as GA SNFs and were categorized by geography as Central (87 SNFs), eight metro-Atlanta counties (Atlanta Area, 56 SNFs), North (46 SNFs), or Southern (44 SNFs). No. T did not vary by year, but varied slightly by region: range for E. coli was 275–1,010, K. pneumonia was 101–409, P. mirabilis 133–439, and P. aeruginosa 35–160. No. T was lowest in North and highest in Atlanta Area. Overall %S was poor to levofloxacin, better for TMP/Sulfa and cefazolin (table). %S did not vary by year. Regional differences were minor: of 17 drug–bug combinations, only five has clinically important differences, three of which were among P. aeuginosa when testing was limited to 67 isolates in outlier region. Only the South had clinically worse susceptibility of K. pneumoniae to nitrofurantoin (36% vs. 47%). ConclusionOverall, SNFs in Georgia had remarkably similar susceptibility patterns when grouped by geography among common urinary pathogens, except when <75 isolates were tested. Antibiogram data can be combined across facilities in a region to provide SNFs with a reasonable antibiograms for stewardship. Further study is ongoing to assess benefits of bedsize or length of stay based antibiograms.Disclosures J. Pack, Clinical Laboratory Services: Employee, Salary. S. Price, Clinical Laboratory Services: Employee, Salary. M. Camp Jr., Clinical Laboratory Services: Employee, Salary. S. Fridkin, Pfizer Inc.: Grant Investigator, Research support.