Published in:
Open Access
01-12-2016 | Research article
Testing the construct validity of hospital care quality indicators: a case study on hip replacement
Authors:
Claudia Fischer, Hester F. Lingsma, Helen A. Anema, Job Kievit, Ewout W. Steyerberg, Niek Klazinga
Published in:
BMC Health Services Research
|
Issue 1/2016
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Abstract
Background
Quality indicators are increasingly used to measure the quality of care and compare quality across hospitals. In the Netherlands over the past few years numerous hospital quality indicators have been developed and reported. Dutch indicators are mainly based on expert consensus and face validity and little is known about their construct validity. Therefore, we aim to study the construct validity of a set of national hospital quality indicators for hip replacements.
Methods
We used the scores of 100 Dutch hospitals on national hospital quality indicators looking at care delivered over a two year period. We assessed construct validity by relating structure, process and outcome indicators using chi-square statistics, bootstrapped Spearman correlations, and independent sample t-tests. We studied indicators that are expected to associate as they measure the same clinical construct.
Result
Among the 28 hypothesized correlations, three associations were significant in the direction hypothesized. Hospitals with low scores on wound infections had high scores on scheduling postoperative appointments (p-value = 0.001) and high scores on not transfusing homologous blood (correlation coefficient = -0.28; p-value = 0.05). Hospitals with high scores on scheduling complication meetings, also had high scores on providing thrombosis prophylaxis (correlation coefficient = 0.21; p-value = 0.04).
Conclusion
Despite the face validity of hospital quality indicators for hip replacement, construct validity seems to be limited. Although the individual indicators might be valid and actionable, drawing overall conclusions based on the whole indicator set should be done carefully, as construct validity could not be established. The factors that may explain the lack of construct validity are poor data quality, no adjustment for case-mix and statistical uncertainty.