Using best-worst scaling in horizon scanning for hepatocellular carcinoma technologies

Objectives: There is a growing need for efficient procedures for identification of emerging technologies by horizon scanning systems. We demonstrate the value of best-worst scaling (BWS) in exploring clinicians’ views on emerging technologies that will impact outcomes in hepatocellular carcinoma (HCC) in the next 5 to 10 years. Methods: Clinicians in Asia, Europe, and the United States were surveyed and their views about eleven emerging technologies relevant to HCC were explored using BWS (case 1). This involved systematically presenting respondents with subsets of five technologies and asking them to identify those that will have the most and least impact on HCC within 5 to 10 years. Statistical analysis was based on sequential best-worst and analyzed using conditional logistic regression. Results: A total of 120 clinicians uniformly distributed across ten countries completed the survey (37 percent response rate). Respondents were predominately hepatologist (41 percent) who focused on HCC (65 percent) and had national influence in this field (39 percent). Respondents viewed molecular targeted therapy (p < .001) and early detection of HCC (p < .001) as having most potential, while improved surgical techniques (p < .001) and biopsy free HCC diagnostics (p < .001) were viewed upon negatively. Conclusions: We demonstrate that BWS could be an important research tool to facilitate horizon scanning and HTA more broadly. Our research demonstrates the value of including clinicians’ preferences as a source of data in horizon scanning, but such methods could be used to incorporate the opinions of a broad array of stakeholders, including those in advocacy and public policy.