An eConsultant versus a hospital-based outpatient consultation for general (internal) medicine: a costing analysis

Abstract

Background: The eConsultant model of care is an outpatient substitution approach which has been evaluated and implemented extensively internationally. It provides an asynchronous, digital, clinician-to-clinician advice service, giving primary care physicians remote access to specialist support for patient care within 3 business days. Results from initial trials of the eConsultant model in Australia support international evidence of reduced wait times and improved access to specialist input, avoidance of face-to-face hospital outpatient visits, and better integrated care. This study compared the cost of delivery of an eConsultant episode of care with that of a hospital-based outpatient appointment. Methods: A cost-minimisation analysis, using a decision analytic model, was used to compare the two approaches. eConsultant costs were calculated from specialist reported data (minutes spent preparing the response; the number of patients referred subsequently for a hospital-based outpatient appointment) and administration staff data (time spent recording the occasion-of-service). Outpatient costs were calculated using finance data and information from outpatient clinic managers at the hospital-based outpatient clinic. The primary outcome was incremental cost saving per patient from a hospital system perspective. Uncertainty was explored using one-way sensitivity analyses and characterised with probabilistic sensitivity analysis using 10,000 Monte Carlo simulations. Results: The traditional referral pathway cost estimate was $587.20/consult compared to $226.13/consult for an eConsultant episode: an efficiency saving of $361.07 per patient. The incremental difference between eConsultant and traditional care was most sensitive to the cost estimate of an outpatient attendance, the time for a specialist to complete an eConsult, and the probability of a patient requiring a face-to-face hospital-based attendance following an eConsult. However, at the upper bounds of each of these estimates, an eConsult remained the most cost-efficient model. In 96.5% of the Monte Carlo simulations eConsult was found to be more cost efficient than the traditional approach. Conclusions: The eConsultant model of care was associated with a 61.5% efficiency gain, allowing diversion of support to hospital-based outpatient appointments.