AI driven decision support reduces antibiotic mismatches and inappropriate use in outpatient urinary tract infections
Abstract Urinary tract infections (UTIs) often prompt empiric outpatient antibiotic prescriptions, risking mismatches. This study evaluates the impact of “UTI Smart-Set” (UTIS), an AI-driven decision-support tool, on prescribing patterns and mismatches in a large outpatient organization. UTIS integr...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-024-01400-5 |
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| _version_ | 1832571313104879616 |
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| author | Shirley Shapiro Ben David Roni Romano Daniella Rahamim-Cohen Joseph Azuri Shira Greenfeld Ben Gedassi Uri Lerner |
| author_facet | Shirley Shapiro Ben David Roni Romano Daniella Rahamim-Cohen Joseph Azuri Shira Greenfeld Ben Gedassi Uri Lerner |
| author_sort | Shirley Shapiro Ben David |
| collection | DOAJ |
| description | Abstract Urinary tract infections (UTIs) often prompt empiric outpatient antibiotic prescriptions, risking mismatches. This study evaluates the impact of “UTI Smart-Set” (UTIS), an AI-driven decision-support tool, on prescribing patterns and mismatches in a large outpatient organization. UTIS integrates machine learning forecasts of antibiotic resistance, patient data, and guidelines into a user-friendly order set for UTI management. From 6/1/2021–8/31/2022, 171,010 UTI diagnoses were recorded, with UTIS used in 75,630 cases involving antibiotic prescriptions. Overall acceptance rate of UTIS recommendations was 66.0%. Among 19,287 cases with urine cultures, antibiotic mismatch rate was significantly lower when UTIS recommendations were followed (8.9% vs. 14.2%, p < 0.0001). Among women over 18, mismatch rate was 47.5% lower, and among women over 50, 55.6% lower (p < 0.001). Additionally, an overall reduction of 80.5% in ciprofloxacin usage (6.4% vs 32.9%, p < 0.0001) was observed. UTIS improved prescribing accuracy, reduced mismatches, and minimized quinolone use, highlighting AI’s potential for personalized infection management. |
| format | Article |
| id | doaj-art-879433afd04c4b459be0b61ee17a3a1d |
| institution | Kabale University |
| issn | 2398-6352 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj-art-879433afd04c4b459be0b61ee17a3a1d2025-02-02T12:43:43ZengNature Portfolionpj Digital Medicine2398-63522025-01-018111010.1038/s41746-024-01400-5AI driven decision support reduces antibiotic mismatches and inappropriate use in outpatient urinary tract infectionsShirley Shapiro Ben David0Roni Romano1Daniella Rahamim-Cohen2Joseph Azuri3Shira Greenfeld4Ben Gedassi5Uri Lerner6Maccabi Healthcare ServicesMaccabi Healthcare ServicesMaccabi Healthcare ServicesMaccabi Healthcare ServicesMaccabi Healthcare ServicesMaccabi Healthcare ServicesMaccabi Healthcare ServicesAbstract Urinary tract infections (UTIs) often prompt empiric outpatient antibiotic prescriptions, risking mismatches. This study evaluates the impact of “UTI Smart-Set” (UTIS), an AI-driven decision-support tool, on prescribing patterns and mismatches in a large outpatient organization. UTIS integrates machine learning forecasts of antibiotic resistance, patient data, and guidelines into a user-friendly order set for UTI management. From 6/1/2021–8/31/2022, 171,010 UTI diagnoses were recorded, with UTIS used in 75,630 cases involving antibiotic prescriptions. Overall acceptance rate of UTIS recommendations was 66.0%. Among 19,287 cases with urine cultures, antibiotic mismatch rate was significantly lower when UTIS recommendations were followed (8.9% vs. 14.2%, p < 0.0001). Among women over 18, mismatch rate was 47.5% lower, and among women over 50, 55.6% lower (p < 0.001). Additionally, an overall reduction of 80.5% in ciprofloxacin usage (6.4% vs 32.9%, p < 0.0001) was observed. UTIS improved prescribing accuracy, reduced mismatches, and minimized quinolone use, highlighting AI’s potential for personalized infection management.https://doi.org/10.1038/s41746-024-01400-5 |
| spellingShingle | Shirley Shapiro Ben David Roni Romano Daniella Rahamim-Cohen Joseph Azuri Shira Greenfeld Ben Gedassi Uri Lerner AI driven decision support reduces antibiotic mismatches and inappropriate use in outpatient urinary tract infections npj Digital Medicine |
| title | AI driven decision support reduces antibiotic mismatches and inappropriate use in outpatient urinary tract infections |
| title_full | AI driven decision support reduces antibiotic mismatches and inappropriate use in outpatient urinary tract infections |
| title_fullStr | AI driven decision support reduces antibiotic mismatches and inappropriate use in outpatient urinary tract infections |
| title_full_unstemmed | AI driven decision support reduces antibiotic mismatches and inappropriate use in outpatient urinary tract infections |
| title_short | AI driven decision support reduces antibiotic mismatches and inappropriate use in outpatient urinary tract infections |
| title_sort | ai driven decision support reduces antibiotic mismatches and inappropriate use in outpatient urinary tract infections |
| url | https://doi.org/10.1038/s41746-024-01400-5 |
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