Management of Discharge Instructions for Children With Medical Complexity: A Systematic Review

Abstract

CONTEXT Children with medical complexity (CMC) are at risk for adverse outcomes after discharge. Difficulties with comprehension of and adherence to discharge instructions contribute to these errors. Comprehensive reviews of patient-, caregiver-, provider-, and system-level characteristics and interventions associated with discharge instruction comprehension and adherence for CMC are lacking. OBJECTIVE To systematically review the literature related to factors associated with comprehension of and adherence to discharge instructions for CMC. DATA SOURCES PubMed/Medline, Embase, Cochrane Central Register of Controlled Trials, PsycInfo, Cumulative Index to Nursing and Allied Health Literature, Web of Science (database initiation until March 2023), and OAIster (gray literature) were searched. STUDY SELECTION Original studies examining caregiver comprehension of and adherence to discharge instructions for CMC (Patient Medical Complexity Algorithm) were evaluated. DATA EXTRACTION Two authors independently screened titles/abstracts and reviewed full-text articles. Two authors extracted data related to study characteristics, methodology, subjects, and results. RESULTS Fifty-one studies were included. More than half were qualitative or mixed methods studies. Few interventional studies examined objective outcomes. More than half of studies examined instructions for equipment (eg, tracheostomies). Common issues related to access, care coordination, and stress/anxiety. Facilitators included accounting for family context and using health literacy-informed strategies. LIMITATIONS No randomized trials met inclusion criteria. Several groups (eg, oncologic diagnoses, NICU patients) were not examined in this review. CONCLUSIONS Multiple factors affect comprehension of and adherence to discharge instructions for CMC. Several areas (eg, appointments, feeding tubes) were understudied. Future work should focus on design of interventions to optimize transitions.