A Demonstration of the Impact of Response Bias on the Results of Patient Satisfaction Surveys

Objectives. The purposes of the present study were to examine patient satisfaction survey data for evidence of response bias, and to demonstrate, using simulated data, how response bias may impact interpretation of results. Data Sources. Patient satisfaction ratings of primary care providers (family...

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Bibliographic Details
Published in:	Health services research Vol. 37; no. 5; pp. 1403 - 1417
Main Authors:	Mazor, KathleenM, Clauser, BrianE, Field, Terry, Yood, RobertA, Gurwitz, JerryH
Format:	Journal Article
Language:	English
Published:	Oxford, UK Blackwell Science Ltd 01-10-2002 Health Research and Educational Trust Blackwell Publishing Ltd Blackwell Science Inc
Subjects:	Bias Correlation analysis Customer satisfaction Data Interpretation, Statistical Family Practice - standards Health Care Surveys - methods Health Care Surveys - statistics & numerical data Health Maintenance Organizations - organization & administration Health Maintenance Organizations - standards Humans Internal Medicine - standards Massachusetts Methods Patient satisfaction Patient Satisfaction - statistics & numerical data Patients Primary Health Care - standards Random Allocation Reproducibility of Results response bias response rate Sampling Studies Simulation Survey response rates Surveys United States > US
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Summary:	Objectives. The purposes of the present study were to examine patient satisfaction survey data for evidence of response bias, and to demonstrate, using simulated data, how response bias may impact interpretation of results. Data Sources. Patient satisfaction ratings of primary care providers (family practitioners and general internists) practicing in the context of a group‐model health maintenance organization and simulated data generated to be comparable to the actual data. Study Design. Correlational analysis of actual patient satisfaction data, followed by a simulation study where response bias was modeled, with comparison of results from biased and unbiased samples. Principal Findings. A positive correlation was found between mean patient satisfaction rating and response rate in the actual patient satisfaction data. Simulation results suggest response bias could lead to overestimation of patient satisfaction overall, with this effect greatest for physicians with the lowest satisfaction scores. Conclusions. Findings suggest that response bias may significantly impact the results of patient satisfaction surveys, leading to overestimation of the level of satisfaction in the patient population overall. Estimates of satisfaction may be most inflated for providers with the least satisfied patients, thereby threatening the validity of provider‐level comparisons.
Bibliography:	ark:/67375/WNG-NVGK8VL6-X ArticleID:HESR011194 istex:A54DD26E73AE974195C0F4960EC34F90348A6485 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0017-9124 1475-6773
DOI:	10.1111/1475-6773.11194