Quantifying neonatal transport deficiencies: an integrated framework for weighting core KPIs and ranking challenges in resource-limited settings

Abstract

Health systems often struggle to deploy an adequate number of trained healthcare professionals at the right time and place. These constraints underscore the critical role of efficient referral and transport processes, particularly for critically ill neonates. This study aimed to develop a strategic, data-driven framework to guide system-wide improvement within neonatal transfer systems. A mixed-methods approach was adopted. Qualitatively, a literature review and semi-structured interviews with experts experienced in neonatal transfer were conducted to identify contextual challenges and relevant key performance indicators (KPIs). Quantitatively, a structured survey was then administered to elicit weights for the KPIs and to prioritize the challenges. The analysis was supported by three Multi-Criteria Decision-Making (MCDM) Techniques: the Decision-Making Trial and Evaluation Laboratory (DEMATEL), the Analytic Network Process (ANP), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Key performance indicators (KPIs) were weighted as follows: Total Transport Time (0.20), Stabilization Care (0.18), In-Transport or 24-h Mortality (0.16), Patient Arrest During Transport (0.12), Medical Gas Supplies (0.10), Medical Equipment Failure (0.09), Accidental Extubation (0.08), and Hypoglycemia (0.06). Based on these weights, the five most critical challenges were: inadequate equipment, low skill level of the transfer team, lack of a centralized transport unit, unclear exchange of information, and transport models constrained by administrative structures.

Conclusion: The proposed framework enhances transparency and defensibility in neonatal transport decision-making. By directing resources toward high-impact domains, it supports improved patient outcomes and reduced system risks.

What is known: • Previous studies on neonatal transport identify challenges and propose KPIs but often lack prioritization of interventions. • Research relies mainly on qualitative methods with limited quantitative analysis and is highly specific to the country or context of the study.

What is new: • By integrating qualitative and quantitative methods, this study identifies challenges and core KPIs of the neonatal transport system, assesses their relative weight, and ranks challenges to guide evidence-based resource allocation. • It provides policymakers with a framework for prioritizing system improvements in any context, including resource-limited settings.

Keywords: Healthcare system improvement; Interhospital transport of critically ill infants; Multi-Criteria Decision-Making (MCDM); Neonatal transport challenges; Neonatal transport system KPIs.