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Utility elicitation using single-item questions compared with a computerized interview.

L A Lenert1, C D Sherbourne, V Reyna

  • 1Veterans Affairs San Diego Healthcare System and the University of California, 92161, USA. llenert@ucsd.edu

Medical Decision Making : an International Journal of the Society for Medical Decision Making
|April 20, 2001
PubMed
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Simpler methods for measuring patient utilities can lead to less precise and upwardly biased results compared to complex computerized procedures. These simpler utility measures may not be suitable for population studies of preferences.

Area of Science:

  • Health Economics
  • Decision Analysis
  • Patient-Reported Outcomes

Background:

  • Assessing patient preferences, or utilities, is crucial for health economic evaluations.
  • Simpler utility measurement methods may impact the mean, variance, or both, affecting their suitability for population studies.

Purpose of the Study:

  • To compare utility elicitation using single-item questions versus a computerized Ping-Pong search procedure.
  • To evaluate the impact of different elicitation methods on the precision and bias of utility measurements.

Main Methods:

  • A convenience sample of 149 primary care patients with depression symptoms participated.
  • Standard gamble (SG) utilities were elicited using a single-item question and a computerized interview.
  • Elicitations were conducted 1-2 weeks apart to minimize recall bias.

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Main Results:

  • Over 90% of participants with a utility of 1.0 on the single-item SG had utilities < 1.0 on the computer SG.
  • Mean utilities were significantly lower with the computer interview (0.80) compared to the single-item question (0.90).
  • Within-subject correlation between the two methods was only fair (r = 0.54).

Conclusions:

  • Single-item questions yield less precise utility estimates.
  • Utility estimates from single-item questions are upwardly biased compared to those from a more complex search procedure.
  • The findings suggest caution when using simpler methods for population-based preference studies.