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Patterns of unit and item nonresponse in the CAHPS Hospital Survey
Marc N Elliott1, Carol Edwards, January Angeles
1Santa Monica, CA 90401, USA.
Insights
Nonresponse weights are generally not recommended for the CAHPS Hospital Survey, especially for hospital comparisons. Case-mix adjustment can effectively reduce nonresponse bias in patient survey data.
Area of Science:
- Health Services Research
- Survey Methodology
- Health Care Quality Measurement
Background:
- The Consumer Assessment of Health Care Providers and Systems (CAHPS) Hospital Survey is crucial for evaluating healthcare quality.
- Understanding and mitigating nonresponse bias is essential for accurate survey results.
Purpose of the Study:
- To identify predictors of unit and item nonresponse in the CAHPS Hospital Survey.
- To assess the impact of nonresponse bias on survey ratings and reports.
- To determine the necessity and utility of nonresponse weights.
Main Methods:
- Multivariate models were employed to predict unit and item nonresponse using 11 administrative variables.
- Descriptive statistics were utilized to analyze the influence of nonresponse on CAHPS Hospital Survey data.
- Correlations between nonresponse weights and survey ratings were examined.
Main Results:
- Unit nonresponse was higher among younger patients and non-Hispanic white patients.
- Item nonresponse showed a positive correlation with patient age.
- Nonresponse weights demonstrated small negative correlations with most care ratings and did not significantly improve precision for sample sizes below 1,000.
- Case-mix adjustment effectively reduced nonresponse bias in certain scenarios.
Conclusions:
- Nonresponse weights are not advised for between-hospital comparisons using the CAHPS Hospital Survey.
- Nonresponse weights may offer minor benefits for overall estimates or demographic comparisons, particularly when case-mix adjustment is absent.
Objective:
To examine the predictors of unit and item nonresponse, the magnitude of nonresponse bias, and the need for nonresponse weights in the Consumer Assessment of Health Care Providers and Systems (CAHPS) Hospital Survey.
Methods:
A common set of 11 administrative variables (41 degrees of freedom) was used to predict unit nonresponse and the rate of item nonresponse in multivariate models. Descriptive statistics were used to examine the impact of nonresponse on CAHPS Hospital Survey ratings and reports.
Results:
Unit nonresponse was highest for younger patients and patients other than non-Hispanic whites (p<.001); item nonresponse increased steadily with age (p<.001). Fourteen of 20 reports of ratings of care had significant (p<.05) but small negative correlations with nonresponse weights (median -0.06; maximum -0.09). Nonresponse weights do not improve overall precision below sample sizes of 300-1,000, and are unlikely to improve the precision of hospital comparisons. In some contexts, case-mix adjustment eliminates most observed nonresponse bias.
Conclusions:
Nonresponse weights should not be used for between-hospital comparisons of the CAHPS Hospital Survey, but may make small contributions to overall estimates or demographic comparisons, especially in the absence of case-mix adjustment.
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