Though many data on the experience of care of patients and caregivers are collected, they are rarely used to improve the quality of health care delivery. One of the main causes is the widespread struggle in interpreting and enhancing these data, requiring the introduction of new techniques to extract intelligible, meaningful, and actionable information. This research explores the potentiality of the latent class analysis (LCA) statistical model in studying experience data. A cross-sectional survey was administered to 482 parents of infants hospitalized in several Italian neonatal intensive care units. Through a 3-step LCA, four subgroups of parents with specific experience profiles, sociodemographic characteristics, and levels of satisfaction were identified. These were composed of parents who reported (1) a positive experience (36%), (2) problematic communication with unit staff (30%), (3) limited access to the unit and poor participation in their baby's care (26%), and (4) a negative experience (8%). Through its explorative segmentation, LCA can provide valuable information to design quality improvement interventions tailored to the specific needs and concerns of each subgroup.
Keywords: Italy; experience of care; family-centered care; latent class analysis; neonatal intensive care unit; parent experience; patient experience.
© The Author(s) 2022.