Impact of an Innovative Smartphone “App” on Intensive Care Unit (ICU) Antimicrobial Utilization Across a Large Metropolitan Health Region in Canada: An Interrupted Time Series Analysis
Notice bibliographique
Résumé
Background. Spectrum MD is a customizable stewardship smartphone app that offers algorithmic decision support based on clinical guidelines and local microbiology data. The app was introduced to all ICU prescribers across a large metropolitan health region followed by an interrupted time series analysis (ITSA) to evaluate the impact on ICU antimicrobial utilization (AMU). Methods. Spectrum MD was launched 11 January 2013 to ICU prescribers with monthly educational sessions. Penetration of the app was tracked with Flurry Analytics, a post-intervention survey, and via session attendance. An uncontrolled before-after intervention ITSA (SPSS v19.0) was performed to compare AMU in the 12 months pre- and post-intervention (allowing a 3 month wash-in period) using daily defined doses/100 patient days. Patient demographics, central line associated bloodstream infection (CLABSI) and influenza rates were analyzed for both time periods. Student's t-test was used for continuous variables and two-tailed χ2 or Fishers exact as appropriate for categorical variables. Results. Patient characteristics were similar between the pre- (n = 2867) and post-intervention (n = 2717) groups, including age (x 56.9 versus 56.3 years), admission APACHE (19.7 versus 19.6), and immunosuppression (15% versus 16%), as were rates of CLABSI and influenza. Post wash-in there were 634 active Spectrum MD users within the health region, which increased to 1145 during the post-intervention period, and 76% (54/71; response rate 34%) of survey respondents reported using the app during their ICU rotation. There was no statistically significant change in overall AMU between the time periods. Agent-specific analysis revealed a trend toward decreased anti-pseudomonal utilization (slope change parameter −0.983; p = 0.07). Of 64 respondents, 70% agreed this app changed their antimicrobial prescribing practices while 89% would recommend it to colleagues. Conclusion. Spectrum MD was a widely accepted intervention that yielded positive user feedback. Though there was no significant reduction in overall AMU, a trend toward decreased anti-pseudomonal agent use may represent more appropriate antimicrobial prescribing. Further longitudinal analysis is required to assess the impact of this promising app. Disclosures. J. Conly, Alberta Health Services (AHS): Employee, John Conly receives a stipend from AHS for his medical role in antimicrobial stewardship; B. Dalton, Alberta Health Services (AHS): Employee, Bruce Dalton had roles in both implementation and evaluation of this program and receives remuneration for antimicrobial stewardship activities. Potential risk of bias exists in this evaluation as positive results could also be career advancing.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».