Case studies on forecasting for innovative technologies: frequent revisions improve accuracy

Area of Science:

• Health Technology Assessment
• Medical Innovation Forecasting
• Healthcare Economics

Background:

• Health technology forecasting aims to predict costs, utilization, and market realities of new medical technologies before clinical adoption.
• Accurate forecasting is vital for healthcare providers making acquisition decisions and payers establishing coverage policies.

Purpose of the Study:

• To evaluate the accuracy of early health technology forecasts.
• To identify factors contributing to forecast inaccuracies.
• To explore methods for improving forecast accuracy.

Main Methods:

• Analysis of ECRI Institute forecasts published between 2007-2010 for four health technologies.
• Comparison of initial forecasts with revised forecasts published in 2013 and 2014.
• Examination of specific inaccuracies and contributing variables for selected technologies.

Main Results:

• Five out of twenty initial predictions were found to be inaccurate when compared to updated forecasts.
• Inaccuracies were concentrated in two technologies with more time-sensitive variables.
• Forecasts for single-room proton beam radiation therapy, digital breast tomosynthesis, transcatheter aortic valve replacement, and robot-assisted surgery were analyzed.

Conclusions:

• Early health technology forecasts may not always be sufficiently accurate for immediate decision-making.
• Forecast accuracy can be enhanced through frequent revisions, particularly for complex technologies with numerous interactive factors.
• Managing time-sensitive variables is critical for improving the reliability of health technology forecasts.