Anomalous Antimicrobial Susceptibility Trend Identification
| Autor: | ML Tlachac, Shira Doron, T. Scott Troppy, Kerri Barton, Elke A. Rundensteiner, Kirthana Beaulac |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Bacteria
medicine.drug_class business.industry Antibiotics Antimicrobial susceptibility Drug Resistance Microbial 02 engineering and technology Drug resistance Microbial Sensitivity Tests 030501 epidemiology Disease cluster Antibiotic prescribing Anti-Bacterial Agents 03 medical and health sciences Identification (information) Antibiotic resistance Massachusetts 020204 information systems Environmental health 0202 electrical engineering electronic engineering information engineering medicine Global health 0305 other medical science business |
| Zdroj: | EMBC |
| ISSN: | 2694-0604 |
| Popis: | Antibiotic resistant bacterial infections are a growing global health crisis. Antibiograms, aggregate antimicrobial resistance reports, are critical for tracking antibiotic susceptibility and prescribing antibiotics. This research leverages fifteen years of the expansive Massachusetts statewide antibiogram dataset curated by the Massachusetts Department of Public Health. Given the lengthy annual antibiogram creation process, data are not timely. Our prior research involved forecasting the current antimicrobial susceptibility given historic antibiograms. The objective for this research is to expand upon this prior work by identifying which antibiotic-bacteria combinations have resistance trends that are not well forecasted. For that, our proposed Previous Year Anomalous Trend Identification (PYATI) strategy employs a cluster driven outlier detection solution to identify the trends to remove before forecasting. Employing PYATI to remove antibiotic-bacteria combinations with anomalous trends statistically significantly reduces the forecasting error for the remaining combinations. As antibiotic resistance is furthered by prescribing ineffective antibiotics, PYATI can be leveraged to improve antibiotic prescribing. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|