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BMC Med Res Methodol. 2005 Dec 1;5:37.

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

Author information

1
Quality and Patient Safety Initiatives, Rural and Community Health Institute, The Texas A&M University System Health Science Center, College Station, Texas, USA. ralitsa_akins@yahoo.com

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.

PMID:
16321161
PMCID:
PMC1318466
DOI:
10.1186/1471-2288-5-37
[Indexed for MEDLINE]
Free PMC Article

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