Feasibility and acceptance of a cloud-based mobile app for antimicrobial stewardship and infection control in Colombian hospitals.

Infection control and antimicrobial stewardship programs (ICASPs) are essential to reduce the emergence and spread of antimicrobial resistance. The primary objective of this study was to assess the feasibility of extending a commercial off-the-shelf (COTS) software for ICASPs in low- and middle-income countries (LMICs). This project involved three hospitals in Colombia, including Centro Médico Imbanaco, Clínica San Francisco, and DIME Clínica Neurocardiovascular. A COTS platform (ILÚM Health Solutions™ Kenilworth, NJ) was extended to function in a range of technology settings, and translatable to almost any language. ICASP features were added, including clinical practice guidelines, hand hygiene (HH) documentation, and isolation precaution (IP) documentation. The platform was delivered as a smartphone mobile application ("app") for both iOS and Android. The app was successfully implemented at all sites, however, full back-end data integration was not feasible at any site. In contrast to the United States, a suite of surveillance tools and physician-focused decision support without patient data proved to be valuable. Language translation processing occurred quickly and incurred minimal costs. HH and IP compliance tracking were the most used features among ICASP staff; treatment guidelines were most often used by physicians. Use of the app streamlined activities and reduced the time spent on ICASP tasks. Users consistently reported positive impressions including simplicity of design, ease of navigation, and improved efficiency. This ICASP app was feasible in limited-resource settings, highly acceptable to users, and represents an innovative approach to antimicrobial resistance prevention.

Predicting Antibiotic Resistance in Gram-Negative Bacilli from Resistance Genes.

We developed a rapid high-throughput PCR test and evaluated highly antibiotic-resistant clinical isolates of Escherichia coli (n = 2,919), Klebsiella pneumoniae (n = 1,974), Proteus mirabilis (n = 1,150), and Pseudomonas aeruginosa (n = 1,484) for several antibiotic resistance genes for comparison with phenotypic resistance across penicillins, cephalosporins, carbapenems, aminoglycosides, trimethoprim-sulfamethoxazole, fluoroquinolones, and macrolides. The isolates originated from hospitals in North America (34%), Europe (23%), Asia (13%), South America (12%), Africa (7%), or Oceania (1%) or were of unknown origin (9%). We developed statistical methods to predict phenotypic resistance from resistance genes for 49 antibiotic-organism combinations, including gentamicin, tobramycin, ciprofloxacin, levofloxacin, trimethoprim-sulfamethoxazole, ertapenem, imipenem, cefazolin, cefepime, cefotaxime, ceftazidime, ceftriaxone, ampicillin, and aztreonam. Average positive predictive values for genotypic prediction of phenotypic resistance were 91% for E. coli, 93% for K. pneumoniae, 87% for P. mirabilis, and 92% for P. aeruginosa across the various antibiotics for this highly resistant cohort of bacterial isolates.