The Telemedicine Demand Index and its Utility in Managing COVID-19 Case Surges

Area of Science:

• Public Health
• Health Informatics
• Epidemiology

Background:

• Telemedicine was crucial for Singapore's COVID-19 management, with proactive and ad hoc consultations for different patient risk groups.
• Accurate forecasting of telemedicine demand is essential for effective resource allocation during pandemics.
• The Telemedicine Demand Index (TDI) was developed to predict telemedicine service utilization.

Purpose of the Study:

• To develop and evaluate the Telemedicine Demand Index (TDI) for estimating population-level telemedicine demand during the COVID-19 pandemic.
• To assess the accuracy of the TDI by comparing its estimates with real-world telemedicine consultation data.

Main Methods:

• The TDI was formulated using three key factors: variant characteristics, healthcare policies, and public healthcare-seeking behavior, yielding 11 coefficients.
• Demand was calculated as the product of the TDI and the number of new COVID-19 cases.
• Real-world data from two distinct periods (Jan-Mar 2022 and Mar-May 2022) were used to validate TDI estimates against actual tele-consultation numbers.

Main Results:

• During the first evaluation period, the TDI overestimated telemedicine demand by an average of 11.4%.
• Following adjustments based on a policy change, the TDI underestimated demand by an average of 7.2% in the subsequent period.
• These results indicate the TDI's potential but highlight the need for ongoing refinement.

Conclusions:

• The Telemedicine Demand Index (TDI) demonstrates initial effectiveness in rapidly estimating telemedicine demand at a population level.
• The index aids in assessing current healthcare capacity and future needs by utilizing historical data and informed assumptions.
• Further research is recommended to enhance the TDI's components and broaden its applicability across diverse populations and contexts.