Identifying the Factors Influencing Patients' Telehealth Visit Satisfaction: Survey Validation Through a Structural Equation Modeling Approach.

Abstract

Introduction: The COVID-19 pandemic accelerated the adoption of telehealth as an alternative to in-person hospital visits. To understand the factors impacting the quality of telehealth services, there is a need for validated survey instruments and conceptual frameworks. The objective of this study is to validate a telehealth patient satisfaction survey by structural equation modeling (SEM) and determine the relationship between the factors in the proposed telehealth patient satisfaction model (TPSM). Methods: We conducted a cross-sectional survey of pediatric patients and families receiving care from a comprehensive pediatric hospital in the Midwest between September 2020 and January 2021. In total, 2,039 usable responses were collected. We used an SEM approach by performing confirmatory factor analysis with Diagonally Weighted Least Squares modeling and Partial Least Squares-Path Modeling to establish the structural validity and examined the relationships among the constructs of "Admission Process" (AP), "Perceived Quality of Service" (PQS), and "Telehealth Satisfaction" (TS). Results: Participants were predominantly White (75%) and English-speaking (95%) parents (85%) of patients (mean age of patients was 10.2 years old). The survey responses were collected from patients visiting 43 department specialties, whereas 50% were behavioral and occupational therapy patients. The structural model showed that the admission process (AP) had a strong positive impact on perceived quality of service (PQS) (p = 0.67, t = 36.1, p < 0.001). The PQS had a strong positive impact on telehealth satisfaction (TS) (p = 0.66, t = 31.8, p < 0.001). The AP had a low positive direct impact on TS (p = 0.16, t = 7.46, p < 0.05). Overall, AP and PQS explained 61% variances (R²) of TS. Conclusions: We validated a newly proposed TS assessment model by using SEM. The TPSM will inform researchers to better understand the influencing factors in TS and help health care systems to improve telehealth patient satisfaction through a validated model.