The Coronavirus disease 2019 (COVID‐19) pandemic profoundly impacted health care utilization. We evaluated asthma‐related emergency department (ED) and inpatient health care utilization by a county‐specific Medicaid population, ages 2–18, during the COVID‐19 pandemic and compared it to utilization from a 3‐year average including 2017–2019. All‐cause ED utilization and asthma medication fill rates were evaluated during the same timeframes. Relative to the 2017–2019 3‐year average, cumulative asthma‐related ED visits from January through June decreased by 45.8% (p = .03) and inpatient admission rates decreased by 50.5% (p = .03). The decline in asthma‐related ED utilization was greater than the reduction of overall ED use during the same time period, suggesting that the decline involved factors specific to asthma and was not due solely to avoidance of health care facilities. Fill rates for asthma controller medications decreased during this time (p = .03) and quick relief medication fill rates had no significant change (p = .31). Multiple factors may have contributed to the decrease in acute asthma health care visits. Locally, decreased air pollution and viral exposures coincided with the “Stay‐at‐home” order in Ohio, and increased utilization of telehealth for assessment during exacerbations may have impacted outcomes. Identification of the cause of the decline in visit rates could spur new interventions to limit the need for ED and inpatient visits for asthma patients, leading to both economic and health‐associated benefits.

BACKGROUND AND OBJECTIVES Sleep is an essential part of the recovery process, yet inpatient sleep quality is poor. Patients and families report that vital signs are the most bothersome overnight disruption. Obtaining vital signs every 4 hours (Q4H) is not evidence-based and is frequently ordered indiscriminately. We aimed to decrease the percentage of patient nights with vital sign checks between 12 am and 6 am in a low-risk population from 98% to 70% within 12 months to minimize overnight sleep disruptions and improve inpatient sleep. METHODS We conducted a quality improvement project on 3 pediatric hospital medicine teams at a large free-standing children’s hospital. Our multidisciplinary team defined low-risk patients as those admitted for hyperbilirubinemia and failure to thrive. Interventions were focused around education, electronic health record decision support, and patient safety. The outcome measure was the percentage of patient nights without a vital sign measurement between 12 am and 6 am and was analyzed by using statistical process control charts. Our process measure was the use of an appropriate vital sign order. Balancing measures included adverse patient events, specifically code blues outside the ICU and emergent transfers. RESULTS From March 2020 to April 2021, our pediatric hospital medicine (PHM) services admitted 449 low-risk patients for a total of 1550 inpatient nights. The percentage of patient nights with overnight vital signs decreased from 98% to 38%. There were no code blues or emergent transfers. CONCLUSION Our improvement interventions reduced the frequency of overnight vital sign monitoring in 2 low-risk groups without any adverse events.

BACKGROUND AND OBJECTIVES: The problem list (PL) is a meaningful use-incentivized criterion for electronic health record documentation. Inconsistent use or inaccuracy of the PL can create communication gaps among providers, potentially leading to diagnostic delays and serious safety events. The objective of the study was to increase the rate of PL review by attending physicians for inpatients discharged from hospital pediatrics and infectious disease services from a baseline of 70% to 80% by June 2018 and to sustain the rate for 6 months. The secondary aim was to improve PL accuracy by decreasing the rate of duplicate codes and red code diagnoses that should resolve before discharge from a baseline of 12% and 11%, respectively, to 5% and sustaining the rate for 6 months. METHODS: A quality improvement team used the Institute for Healthcare Improvement Model for Improvement. We tracked duplicate codes and red codes as surrogate markers of PL quality. Rates of PL review and PL quality were analyzed monthly via statistical process control charts (p-charts) with 3-s control limits to identify special cause variation. RESULTS: PL review improved from a baseline of 70% to 90%, and the change was sustained for 1 year. PL quality improved as duplicate codes at the time of discharge decreased from 12% to 6% and as red codes decreased from a baseline of 11% to 6%. CONCLUSIONS: The PL is an important communication tool that is underused. By engaging and educating stakeholders, incentivizing compliance, standardizing PL management, leveraging electronic health record enhancements, and providing physician feedback, we improved PL meaningful use and quality.

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Introduction: Delays in hospital discharge can negatively impact patient care, bed availability, and patient satisfaction. There are limited studies examining how the electronic health record (EHR) can be used to improve discharge timeliness. This study aimed to implement an EHR discharge optimization tool (DOT) successfully and achieve a discharge before noon (DBN) percentage of 25%. Methods: We conducted a single-center quality improvement study of patients discharged from 3 pediatric hospital medicine teaching service teams at a quaternary care academic children’s hospital. The multidisciplinary team created a DOT centrally embedded within the care team standard workflow to communicate anticipated time until discharge. The primary outcome was the monthly percentage of patients discharged before noon. Secondary outcomes included provider utilization of the DOT, tool accuracy, and patient length of stay. Balancing measures were 7- and 30-day readmission rates. Results: The DBN percentage increased from 16.4% to an average of 19.3% over the 13-month intervention period (P = 0.0005). DOT utilization was measured at 87.2%, and the overall accuracy of predicting time until discharge was 75.6% (P < 0.0001). Median length of stay declined from 1.75 to 1.68 days (P = 0.0033), and there was no negative impact on 7- or 30-day readmission rates. Conclusion: This initiative demonstrated that a highly utilized and accurate discharge tool could be created in the EHR to assist medical care teams with improving DBN percentage on busy, academic teaching services.