Improving Short Course Treatment of Pediatric Infections: A Randomized Quality Improvement Trial.

BACKGROUND AND OBJECTIVES: Short courses of antibiotic treatment are effective for pediatric community-acquired pneumonia (CAP) and skin and soft tissue infections (SSTI). We compared the effectiveness of education with performance feedback, clinical decision support (CDS), and the combination in encouraging appropriately short treatment courses by primary care clinicians. METHODS: We designed a site-randomized, quality improvement trial within a large pediatric primary care network. Each practice was randomly assigned to 1 of 4 groups: education and feedback; CDS; both interventions ("combined group"); and control. We performed difference-in-differences analysis to compare the proportion of cases with short course treatment before and after intervention among the 4 groups. RESULTS: For all cases of CAP and SSTI, the proportion in the control group treated with the recommended duration did not change from the baseline period (26.1% [679 of 2603]) to the intervention period (25.8% [196 of 761]; P = .9). For the education and feedback group, the proportion rose from 22.3% (428 of 1925) to 45.0% (239 of 532; P < .001); for the CDS group, from 26.6% (485 of 1824) to 52.3% (228 of 436; P < .001); and for the combined group, from 26.2% (491 of 1875) to 67.8% (314 of 463; P < .001). A difference-in-differences analysis showed that all 3 intervention groups improved performance compared with the control group (P < .001); the combined group had greater improvement than the education and feedback group or the CDS group (P < .001). CONCLUSIONS: In this quality improvement project to encourage shorter duration treatment of CAP and SSTI, both education with performance feedback and CDS were effective in modifying clinician behavior; however, the combination of the two was substantially more effective than either strategy alone.

The Antibiotic Likelihood Index: A New Measure of Antimicrobial Stewardship for Pediatric Primary Care Based on Reason for Visit.

BACKGROUND: Quality metrics for antibiotic prescribing by pediatricians are limited. We sought to define a novel measure that assesses clinicians' overall antibiotic prescribing. METHODS: Using electronic health record (EHR) data from 2018 to 2019 for children 3 months to 17 years of age from 53 practices within a large pediatric network, we grouped encounters into Reason for Visit categories using the classification system of the National Ambulatory Medical Care Survey and analyzed the proportion of encounters with an antibiotic prescription. Categories were sorted according to the attributable proportion of encounters with an antibiotic prescribed. The proposed metric-the Antibiotic Likelihood Index (ALI)-was defined as the proportion of encounters with an antibiotic prescribed among categories that accounted for >80% of all encounters with an antibiotic prescribed. The ALI was calculated for the entire network and for individual prescribers, and the distribution among prescribers was described. RESULTS: Six Reason for Visit categories-cough, ear complaints, fever, sore throat, rash, and congestion/upper respiratory infection-accounted for 82.4% of all antibiotics prescribed. Among the 222 682 encounters for the top 6 categories combined, 67 368 (30.3%) had an antibiotic prescribed, defined as the ALI for the entire sample. The index among individual prescribers ranged from 7.5% to 57.2% (interquartile range 24.3% to 34.9%). The correlation for individual prescribers between 2018 and 2019 was high (R2 = 0.80). CONCLUSIONS: The ALI, a proposed new metric of pediatric antibiotic prescribing, can be readily calculated from EHR data and captures the range of antibiotic prescribing among pediatricians for common clinical scenarios.

Pediatric Primary Care Billing Trends After the 2021 Evaluation and Management Coding Changes.

This cross-sectional study examines the differences in billing trends for pediatric patient care compared with adult care after the 2021 evaluation and management (E/M) policy changes.