<p><strong>BACKGROUND: </strong>Inappropriate antibiotic prescribing is common in primary care (PC), particularly for respiratory tract diagnoses (RTDs). However, the optimal approach for improving prescribing remains unknown.</p>

<p><strong>METHODS: </strong>We conducted a stepped-wedge study in PC practices within a health system to assess the impact of a provider-targeted intervention on antibiotic prescribing for RTDs. RTDs were grouped into tiers based on appropriateness of antibiotic prescribing: tier 1 (almost always indicated), tier 2 (may be indicated), and tier 3 (rarely indicated). Providers received education on appropriate RTD prescribing followed by monthly peer comparison feedback on antibiotic prescribing for (1) all tiers and (2) tier 3 RTDs. Chi-squared testing was used to compare the proportion of visits with antibiotic prescriptions before and during the intervention. Mixed-effects multivariable logistic regression analysis was performed to assess the association between the intervention and antibiotic prescribing.</p>

<p><strong>RESULTS: </strong>Across 30 PC practices and 185,755 total visits, overall antibiotic prescribing was reduced with the intervention, from 35.2% to 23.0% of visits (p&lt;0.001). In multivariable analysis, the intervention was associated with a reduced odds of antibiotic prescription for tiers 2 (OR 0.57; 95% CI 0.52 - 0.62) and 3 (OR 0.57; 95% CI 0.53 - 0.61), but not for tier 1 (OR 0.98; 95% CI 0.83 - 1.16).</p>

<p><strong>CONCLUSION: </strong>A provider-focused intervention reduced overall antibiotic prescribing for RTDs without affecting prescribing for infections that likely require antibiotics. Future research should examine the sustainability of such interventions, potential unintended adverse effects on patient health or satisfaction, and provider perceptions and acceptability.</p>

<p><strong>OBJECTIVES: </strong>The objective was to compare the effectiveness of physician judgment and an electronic algorithmic alert to identify pediatric patients with severe sepsis/septic shock in a pediatric emergency department (ED).</p>

<p><strong>METHODS: </strong>This was an observational cohort study of patients older than 56 days with fever or hypothermia. All patients were evaluated for potential sepsis in real time by the ED clinical team. An electronic algorithmic alert was retrospectively applied to identify patients with potential sepsis independent of physician judgment. The primary outcome was the proportion of patients correctly identified with severe sepsis/septic shock defined by consensus criteria. Test characteristics were determined and receiver operating characteristic (ROC) curves were compared.</p>

<p><strong>RESULTS: </strong>Of 19,524 eligible patient visits, 88 patients developed consensus-confirmed severe sepsis or septic shock. Physician judgment identified 159 and the algorithmic alert identified 3,301 patients with potential sepsis. Physician judgment had sensitivity of 72.7% (95% confidence interval [CI] = 72.1% to 73.4%) and specificity of 99.5% (95% CI = 99.4% to 99.6%); the algorithmic alert had sensitivity of 92.1% (95% CI = 91.7% to 92.4%) and specificity of 83.4% (95% CI = 82.9% to 83.9%) for severe sepsis/septic shock. There was no significant difference in the area under the ROC curve for physician judgment (0.86, 95% CI = 0.81 to 0.91) or the algorithm (0.88, 95% CI = 0.85 to 0.91; p = 0.54). A combination method using either positive physician judgment or an algorithmic alert improved sensitivity to 96.6% and specificity to 83.3%. A sequential approach, in which positive identification by the algorithmic alert was then confirmed by physician judgment, achieved 68.2% sensitivity and 99.6% specificity. Positive and negative predictive values for physician judgment versus algorithmic alert were 40.3% versus 2.5% and 99.88% versus 99.96%, respectively.</p>

<p><strong>CONCLUSIONS: </strong>The electronic algorithmic alert was more sensitive but less specific than physician judgment for recognition of pediatric severe sepsis and septic shock. These findings can help to guide institutions in selecting pediatric sepsis recognition methods based on institutional needs and priorities.</p>