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

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

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