Improving the Efficiency of Care for Pediatric Patients Hospitalized With Asthma

Bartlett, Katharine T.; Parente, Victoria; Morales, Vanessa; Hauser, Jillian; McLean, Heather

doi:10.1542/hpeds.2016-0108

Cited by 36 publications

(43 citation statements)

References 15 publications

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“…Based on previous studies, clinical pathways are often implemented with the primary goals of decreasing hospital length of stay and cost [12, 13]. In this paper we provide evidence to suggest an additional goal and benefit of implementing a clinical asthma pathway is its favorable impact on resident education.…”

Section: Resultsmentioning

confidence: 85%

The Impact of a Clinical Asthma Pathway on Resident Education

Talib

Lax

Reznik

2018

BioMed Research International

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Clinical pathways for asthma management decrease hospital cost and length of stay; however little is known about the educational impact of pathways on residents. Pediatric residents at a children's hospital (N = 114) were invited to complete a 22-item computerized, anonymous survey 6 months before and 6 months after asthma pathway implementation. The survey assessed pathway use and residents (1) pathway knowledge, (2) attitudes and experiences with managing asthma, and (3) perceived educational benefits. Mean pathway knowledge score increased from the case before to the case after implementation [1.5 ± 1.0 versus 2.6 ± 1.3, p < 0.001], as did high preparedness to manage asthma [61% versus 91%, p < 0.001] and electronic order set use [28% versus 80%, p < 0.001]. The top three educational benefits of the pathway endorsed by residents were application of evidence-based medicine (57%), ability to assess exacerbations (52%), and skill at communicating respiratory status (47%). After implementation, residents' knowledge and preparedness to manage asthma improved as well as many endorsed educational benefits.

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Section: Resultsmentioning

confidence: 85%

The Impact of a Clinical Asthma Pathway on Resident Education

Talib

Lax

Reznik

2018

BioMed Research International

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“…Respiratory scoring systems for pediatric asthma have streamlined and improved inpatient care, but there is an inconsistent use of any such scoring system in the PICU. Bartlett et al implemented and studied a successful clinical care guideline in the PICU, which included a bronchodilator weaning pathway based on a subjective staff generated respiratory score called the modified pulmonary index score and showed a decreased length of stay in the hospital overall. An automated, quantitative score to replace these respiratory scores is appealing to critical care providers who are concerned about evidence‐based clinical decision making, interrater reliability, and staff efficiency.…”

Section: Discussionmentioning

confidence: 99%

“…Clinical scoring systems appeal to multiple stakeholders because they are quantitative, can be validated and improve patient outcomes . Pediatric asthma is no exception; as the most common chronic disease of childhood, development of clinical scores and guidelines have helped to streamline and improve pediatric asthma care delivery …”

Section: Introductionmentioning

confidence: 99%

“…These scores contain similar elements but are customized to individual hospitals . The use of these scores to guide inpatient treatment of acute asthma exacerbations has improved patient outcomes including reduced length of stay, decreased admission rates, and decreased medication burden in both the emergency department and inpatient wards …”

Section: Introductionmentioning

confidence: 99%

“…[6][7][8] The use of these scores to guide inpatient treatment of acute asthma exacerbations has improved patient outcomes including reduced length of stay, decreased admission rates, and decreased medication burden in both the emergency department and inpatient wards. 5,[9][10][11] Respiratory scores like PAS contain subjective elements like auscultation, have limited interrater reliability, and are less sensitive in older children and adolescents. They are used intermittently and depend on frequent reassessment, increasing the burden on staff.…”

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confidence: 99%

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Novel pediatric‐automated respiratory score using physiologic data and machine learning in asthma

Messinger

Bui

Wagner

et al. 2019

Pediatric Pulmonology

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Objectives Manual clinical scoring systems are the current standard used for acute asthma clinical care pathways. No automated system exists that assesses disease severity, time course, and treatment impact in pediatric acute severe asthma exacerbations. Working hypothesis: machine learning applied to continuous vital sign data could provide a novel pediatric‐automated asthma respiratory score (pARS) by using the manual pediatric asthma score (PAS) as the clinical care standard. Methods Continuous vital sign monitoring data (heart rate, respiratory rate, and pulse oximetry) were merged with the health record data including a provider‐determined PAS in children between 2 and 18 years of age admitted to the pediatric intensive care unit (PICU) for status asthmaticus. A cascaded artificial neural network (ANN) was applied to create an automated respiratory score and validated by two approaches. The ANN was compared with the Normal and Poisson regression models. Results Out of an initial group of 186 patients, 128 patients met inclusion criteria. Merging physiologic data with clinical data yielded >37 000 data points for model training. The pARS score had good predictive accuracy, with 80% of the pARS values within ±2 points of the provider‐determined PAS, especially over the mid‐range of PASs (6‐9). The Poisson and Normal distribution regressions yielded a smaller overall median absolute error. Conclusions The pARS reproduced the manually recorded PAS. Once validated and studied prospectively as a tool for research and for physician decision support, this methodology can be implemented in the PICU to objectively guide treatment decisions.

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Improving the Pediatric Floor Discharge Process Following Tonsillectomy

et al. 2021

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Objectives/Hypothesis Over 300,000 tonsillectomies are performed nationwide every year. In 2017, half of children undergoing tonsillectomy at our institution were admitted to the pediatric floor, with only 10.4% being discharged before 11 AM on postoperative day 1 (POD1). Our primary objective was to increase the percentage of patients discharged before 11 AM on POD1 to at least 50% within 1 year. Study Design Prospective observational (quality improvement). Methods A multidisciplinary quality improvement (QI) team was assembled. The primary outcome was “timely discharges,” defined as percentage of patients discharged before 11 AM on POD1; secondary outcomes were percentage of patients discharged before 1 PM and mean length of stay (hours). Seven‐day readmission rate served as our balancing measure. Prior year data served as baseline. A process map, Ishikawa diagram, and Pareto chart were utilized to identify specific target areas for improvement. Key interventions included announcement of our initiative, an electronic health record‐based handoff text prompt, discharge checklist, automated discharge instructions, encouragement to place discharge orders by 9 AM and implementation of early POD1 rounds. Data were collected on a biweekly basis and the primary and secondary outcomes were plotted on control charts and analyzed using rules for special cause variation. Results Within 12 months, POD1 discharges before 11 AM and before 1 PM increased to 44.9% and 83.8%, respectively, with sustained improvement for the first 6 months of the subsequent year. Mean length of stay decreased, and 7‐day readmission rates were unchanged. Conclusions By understanding the factors influencing timely POD1 discharges after tonsillectomy, key interventions were implemented to achieve an increase in timely discharges. Level of Evidence 3 Laryngoscope, 132:225–233, 2022

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Improving the Efficiency of Care for Pediatric Patients Hospitalized With Asthma

Cited by 36 publications

References 15 publications

The Impact of a Clinical Asthma Pathway on Resident Education

The Impact of a Clinical Asthma Pathway on Resident Education

Novel pediatric‐automated respiratory score using physiologic data and machine learning in asthma

Improving the Pediatric Floor Discharge Process Following Tonsillectomy

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