Factorial Analysis Quantifies the Effects of Pediatric Discharge Bundle on Hospital Readmission

• Published in: Pediatrics (Evanston) Vol. 148; no. 4; p. 1
• Main Authors: Osorio, Snezana Nena, Gage, Sandra, Mallory, Leah, Soung, Paula, Satty, Alexandra, Abramson, Erika L., Provost, Lloyd, Cooperberg, David
• Format: Journal Article
• Language: English
• Published: United States American Academy of Pediatrics 01.10.2021
• Subjects: Aftercare; Ambulatory Care; Check lists; Checklist; Child; Child, Hospitalized; Child, Preschool; Chronic illnesses; Complex patients; Discharge; Factor Analysis, Statistical; Factorial experiments; Female; Humans; Male; Patient admissions; Patient Care Bundles - methods; Patient Discharge - statistics & numerical data; Patient Education as Topic; Patient Readmission - statistics & numerical data; Patients; Pediatrics; Retrospective Studies; Risk groups; Teach-Back Communication
• DOI: 10.1542/peds.2021-049926
• ISSN: 0031-4005; 1098-4275

Factorial design of a natural experiment was used to quantify the benefit of individual and combined bundle elements from a 4-element discharge transition bundle (checklist, teach-back, handoff to outpatient providers, and postdischarge phone call) on 30-day readmission rates (RRs). A 2 factorial design matrix of 4 bundle element combinations was developed by using patient data ( = 7725) collected from January 2014 to December 2017 from 4 hospitals. Patients were classified into 3 clinical risk groups (CRGs): no chronic disease (CRG1), single chronic condition (CRG2), and complex chronic condition (CRG3). Estimated main effects of each bundle element and their interactions were evaluated by using Study-It software. Because of variation in subgroup size, important effects from the factorial analysis were determined by using weighted effect estimates. RR in CRG1 was 3.5% ( = 4003), 4.1% in CRG2 ( = 1936), and 17.6% in CRG3 ( = 1786). Across the 3 CRGs, the number of subjects in the factorial groupings ranged from 16 to 674. The single most effective element in reducing RR was the checklist in CRG1 and CRG2 (reducing RR by 1.3% and 3.0%) and teach-back in CRG3 (by 4.7%) The combination of teach-back plus a checklist had the greatest effect on reducing RR in CRG3 by 5.3%. The effect of bundle elements varied across risk groups, indicating that transition needs may vary on the basis of population. The combined use of teach-back plus a checklist had the greatest impact on reducing RR for medically complex patients.