Decision aids as tools to facilitate shared decision making in neonatal care: A standardization analysis

Abstract

Background: Neonatal practice involves complex decision-making that prioritizes different ethical principles than adult care, with a particular focus on beneficence and the best interests standard, while respecting parental autonomy. Prioritizing autonomy and best interests are facilitated through shared decision-making (SDM). Decision aids (DA)s are educational, evidence-based tools designed to facilitate SDM between patients, caregivers, and healthcare professionals. The development and evaluation of existing neonatal DAs have been variable, with as yet unestablished effectiveness and generalizability. The purpose of this review is to examine existing published neonatal DAs with the SUNDAE and SDP frameworks to describe where standards are met and identify opportunities to improve future neonatal SDM using DAs. Methods: Standardized frameworks allow neonatal DAs to be evaluated for completeness and elucidate areas of opportunity to better promote the ethical goals of SDM. DAs were included in analysis based on a comprehensive search strategy focusing on neonatal topics, and then evaluated for compliance with both the Standards for UNiversal reporting of patient Decision Aid Evaluations checklist (SUNDAE) and the Systematic Development Process (SDP). Results: Compliance with SUNDAE and SDP were inconsistent in currently published neonatal DAs. SUNDAE evaluation revealed gaps in visual and numerical probability factors, values clarification exercises, and provision of tailored information to meet parental needs, overall limiting the potential of informed and adaptable SDM. SDP evaluation showed gaps in longitudinal engagement of steering committees, a lack of preliminary alpha testing with clinicians and beta testing with both clinicians and parents. Conclusions: In order to maximize SDM and support ethical decision-making honoring parental autonomy and best interests standard in neonates, a holistic framework for DA development and reporting is needed to maximize their clinical impact.