2006
DOI: 10.1097/01.mlr.0000215815.70506.b6
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Administrative Versus Clinical Data for Coronary Artery Bypass Graft Surgery Report Cards

Abstract: Unique properties of the California administrative data, including the ability to distinguish acute preoperative risk factors from complications of surgery, permitted construction of an administrative risk model that predicts mortality on par with most published clinical models. Despite this, the administrative model identified slightly different hospital outliers, which may indicate somewhat biased assessments of hospital patient risk.

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Cited by 57 publications
(41 citation statements)
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“…Nevertheless, for analysis of hospital volume influence in specific conditions, we choose DRG, for which coding was expected to be robust, as a way to limit this bias. In addition, earlier work showed that administrative databases performed relatively well compared to clinical databases, being capable of identifying outlying hospitals with slight [30] or major [31] differences. Finally, our findings may not apply to other countries.…”
Section: Discussionmentioning
confidence: 99%
“…Nevertheless, for analysis of hospital volume influence in specific conditions, we choose DRG, for which coding was expected to be robust, as a way to limit this bias. In addition, earlier work showed that administrative databases performed relatively well compared to clinical databases, being capable of identifying outlying hospitals with slight [30] or major [31] differences. Finally, our findings may not apply to other countries.…”
Section: Discussionmentioning
confidence: 99%
“…The coding comorbidity algorithm for the index event allowed analysis only of patient factors on admission or close to admission as case mix predictors, excluding events potentially on the causal pathway between hospital and outcome. Even if detailed clinical data on patient risk factors collected from chart reviews is considered the ''gold standard'', several comparative studies demonstrated a good correlation between risk-adjusted outcomes obtained from clinical data versus administrative datasets [25,26]. The empirical approach we used to define severity and adjust for it allowed the identification and control of confounding factors according to their specific relationship with the outcome in the population.…”
Section: Discussionmentioning
confidence: 99%
“…Finally, administrative data did not allow insight into clinical or physiological factors. However, important clinical determinants of outcomes after COPD were found to explain only 15% of the variability in mortality across institutions [12], and we trust the known good performance of administrative data for studies on outcomes [26,27]. Residual confounding bias for unmeasured factors should be considered as a potential limitation of the study [30].…”
Section: Discussionmentioning
confidence: 99%
“…This is currently the practice in at least 2 states, New York and California. 4,52 • Outlier determination. Several studies have shown differences in the outliers determined using administrative versus clinical data, even when the administrative databases were relatively sophisticated.…”
Section: Discussionmentioning
confidence: 99%