OBJECTIVE We sought to understand the impact of the coronavirus disease 2019 (COVID-19) pandemic on the clinical exposure of pediatric interns to common pediatric inpatient diagnoses. METHODS We analyzed electronic medical record data to compare intern clinical exposure during the COVID-19 pandemic from June 2020 through February 2021 with the same academic blocks from 2017 to 2020. We attributed patients to each pediatric intern on the basis of notes written during their pediatric hospital medicine rotation to compare intern exposures with common inpatient diagnoses before and during the pandemic. We compared the median number of notes written per intern per block overall, as well as for each common inpatient diagnosis. RESULTS Median counts of notes written per intern per block were significantly reduced in the COVID-19 group compared with the pre–COVID-19 group (96 [interquartile range (IQR): 81–119)] vs 129 [IQR: 110–160]; P < .001). Median intern notes per block was lower in the COVID-19 group for all months except February 2021. Although the median number of notes for many common inpatient diagnoses was significantly reduced, they were higher for mental health (4 [IQR: 2–9] vs 2 [IQR: 1–6]; P < .001) and suicidality (4.5 [IQR: 2–8] vs 0 [IQR: 0–2]; P < .001). Median shifts worked per intern per block was also reduced in the COVID-19 group (22 [IQR: 21–23] vs 23 [IQR: 22–24]; P < .001). CONCLUSIONS Our findings reveal a significant reduction in resident exposure to many common inpatient pediatric diagnoses during the COVID-19 pandemic. Residency programs and pediatric hospitalist educators should consider curricular interventions to ensure adequate clinical exposure for residents affected by the pandemic.

Background and Objectives Clinical decision support (CDS) and computerized provider order entry have been shown to improve health care quality and safety, but may also generate previously unanticipated errors. We identified multiple CDS tools for platelet transfusion orders. In this study, we sought to evaluate and improve the effectiveness of those CDS tools while creating and testing a framework for future evaluation of other CDS tools. Methods Using a query of an enterprise data warehouse at a tertiary care pediatric hospital, we conducted a retrospective analysis to assess baseline use and performance of existing CDS for platelet transfusion orders. Our outcome measure was the percentage of platelet undertransfusion ordering errors. Errors were defined as platelet transfusion volumes ordered which were less than the amount recommended by the order set used. We then redesigned our CDS and measured the impact of our intervention prospectively using statistical process control methodology. Results We identified that 62% of all platelet transfusion orders were placed with one of two order sets (Inpatient Service 1 and Inpatient Service 2). The Inpatient Service 1 order set had a significantly higher occurrence of ordering errors (3.10% compared with 1.20%). After our interventions, platelet transfusion order error occurrence on Inpatient Service 1 decreased from 3.10 to 0.33%. Conclusion We successfully reduced platelet transfusion ordering errors by redesigning our CDS tools. We suggest that the use of collections of clinical data may help identify patterns in erroneous ordering, which could otherwise go undetected. We have created a framework which can be used to evaluate the effectiveness of other similar CDS tools.

OBJECTIVES: Increased focus on health care quality and safety has generally led to additional resident supervision by attending physicians. At our children’s hospital, residents place orders overnight that are not explicitly reviewed by attending physicians until morning rounds. We aimed to categorize the types of orders that are added or discontinued on morning rounds the morning after admission to a resident team and to understand the rationale for these order additions and discontinuations. METHODS: We used our hospital’s data warehouse to generate a report of orders placed by residents overnight that were discontinued the next morning and orders that were added on rounds the morning after admission to a resident team from July 1, 2017 to June 29, 2018. Retrospective chart review was performed on included orders to determine the reason for order changes. RESULTS: Our report identified 5927 orders; 538 were included for analysis after exclusion of duplicate orders, administrative orders, and orders for patients admitted to non-Pediatric Hospital Medicine services. The reason for order discontinuation or addition was medical decision-making (n = 357, 66.4%), change in patient trajectory (n = 151, 28.1%), and medical error (n = 30, 5.6%). Medical errors were most commonly related to medications (n = 24, 80%) and errors of omission (n = 19, 63%). CONCLUSIONS: New or discontinued orders commonly resulted from evolving patient management decisions or changes in patient trajectory; medical errors represented a small subset of identified orders. Medical errors were often errors of omission, suggesting an area to direct future safety initiatives.

No abstract