Stability of response characteristics of a Delphi panel: application of bootstrap data expansion

TLDR

Delphi surveys are widely used across clinical medicine, nursing, medical education, and healthcare services, yet the number of participants needed for stable results remains unclear. The study examined the first round of a Delphi survey with 23 healthcare quality experts, augmenting the data via bootstrap sampling to generate two larger synthetic samples (1,000 and 2,000 iterations) and compared mean, trimmed mean, standard deviation, and 95% confidence intervals across 54 items. The analysis showed that response characteristics of a small, well‑trained expert panel are stable when augmented by bootstrap sampling, supporting the reliability of such panels for developing decision‑making criteria.

Abstract

Abstract Background Delphi surveys with panels of experts in a particular area of interest have been widely utilized in the fields of clinical medicine, nursing practice, medical education and healthcare services. Despite this wide applicability of the Delphi methodology, there is no clear identification of what constitutes a sufficient number of Delphi survey participants to ensure stability of results. Methods The study analyzed the response characteristics from the first round of a Delphi survey conducted with 23 experts in healthcare quality and patient safety. The panel members had similar training and subject matter understanding of the Malcolm Baldrige Criteria for Performance Excellence in Healthcare. The raw data from the first round sampling, which usually contains the largest diversity of responses, were augmented via bootstrap sampling to obtain computer-generated results for two larger samples obtained by sampling with replacement. Response characteristics (mean, trimmed mean, standard deviation and 95% confidence intervals) for 54 survey items were compared for the responses of the 23 actual study participants and two computer-generated samples of 1000 and 2000 resampling iterations. Results The results from this study indicate that the response characteristics of a small expert panel in a well-defined knowledge area are stable in light of augmented sampling. Conclusion Panels of similarly trained experts (who possess a general understanding in the field of interest) provide effective and reliable utilization of a small sample from a limited number of experts in a field of study to develop reliable criteria that inform judgment and support effective decision-making.